Machine Learning Week Speakers

May 24-28, 2021 – Livestream

First Speakers Are Below – Many More to Come!

 

PAW Business

Dean Abbott
Dean Abbott

Co-Founder and Chief Data Scientist

Dean Abbott is Co-Founder and Chief Data Scientist of SmarterHQ, and President of Abbott Analytics, in San Diego, California. Mr. Abbott is an internationally recognized data science and predictive analytics expert with over three decades of experience. Abbott is the author of Applied Predictive Analytics (Wiley, 2014, 2nd edition forthcoming in 2020. He has a B.S. in Mathematics of Computation from Rensselaer (1985) and a Master of Applied Mathematics from the University of Virginia (1987).

Dean Abbott is speaking in the following session:

Dean Abbott is instructor of the following workshop:

Javed Ahmed
Javed Ahmed

Senior Data Scientist

Javed Ahmed is a Senior Data Scientist with Metis, where he focuses on corporate training programs in Machine Learning and analytics. A financial economist by background, he has extensive experience developing analytic applications for large organizations including Amazon and the Federal Reserve Board of Governors. Javed holds a PhD in Finance and MA in Statistics from U.C. Berkeley, as well as undergraduate degrees in Finance and Systems Engineering from the University of Pennsylvania.

Muneeb Alam
Muneeb Alam

Specialist, Data Science

Muneeb Alam is a data science specialist at QuantumBlack, a McKinsey Company. He has experience in the public and social sector, healthcare, energy and basic materials. He holds a B.A. in astrophysics from Columbia University and an MSc. in business analytics from Imperial College Business School.

Meghan Anzelc
Meghan Anzelc

Head of Data & Analytics

Meghan joined Spencer Stuart in July 2018 leading data and analytics for the firm. She is responsible for creating and implementing a strategy and roadmap to advance the data and analytics capabilities across Spencer Stuart, focusing on delivering greater impact to our clients and for the firm. Her background is in physics and data science and she has extensive experience helping organizations leverage data and analytics to improve their businesses. Meghan likes to share her passion for data, science, diversity and analytics including by regularly speak at industry and scholastic events catered to attracting and retaining the next generation of the workforce. She has also been involved in a range of diversity and inclusion initiatives; among these, as the Co-founder and Co-Chair of the Women in Actuarial & Analytics group at Travelers, the first Diversity Business Network at Travelers, a group dedicated to the recruitment, retention, and advancement of women in analytical roles and winner of the 2011 NALC Above-and-Beyond Award. 

Meghan Anzelc is speaking in the following session:

Ashish Bansal
Ashish Bansal

Director Recommendations Systems

Ashish manages Events recommendations and trends at Twitch. He uses AI/ML to generate insights from vast amounts of data and build interesting B2C, B2B and enterprise products. He has over 20 years of experience in technology ranging from founding startups to large companies. He has an MBA in marketing from Kellogg School of Management and a B.Tech from IIT BHU, India.

Ashish Bansal is speaking in the following session:

Vladimir Barash
Vladimir Barash

Director

Vladimir Barash is Director Graphika Labs. He has received his Ph.D. from Cornell University, where he studied Information Science and wrote his thesis on the flow of rumors and virally marketed products through social networks. At Graphika, Vladimir's research focuses on deep learning applications of network analysis, detection and deterrence of disinformation operations on networks, and causal mechanisms of large-scale social behavior.

In addition to his research duties, Vladimir has a decade's experience working with big data, from scientific computing (Matlab, scipy) to parallel processing technologies (Hadoop / Hive) to data storage and pipelining (Redis, mongodb, MYSQL) at the terabyte scale. At Graphika, Vladimir has co-designed and implemented systems that process tens of millions every six hours to deliver timely information on influencers and conversation leaders in online communities tailored to client interests. Vladimir is proficient in over a dozen programming languages and frameworks and has designed production-ready systems for every stage of big data analysis, from collection to client-facing presentation via web, spreadsheet or graphic visualization.

Vladimir has been active in the Social Media Research Foundation (SMRF) and the NodeXL project, helping build a network analysis package that brings relational data analysis at scale to the fingertips of any interested user, without requiring specialized knowledge or technical training beyond familiarity with Microsoft Excel. NodeXL has enabled users in academia, industry and the general public to analyze tens of thousands of social networks, from networks of politicians voting on bills to networks of motorcycle enthusiasts working together. As part of his work with SMRF and the NodeXL team, Vladimir has contributed a chapter on Twitter analysis to Analyzing Social Media Networks with NodeXL: Insights from a Connected World.

Vladimir's work has received awards at the International Conference for Weblogs in Social Media and Bits on Our Minds. He has presented his research at academic and industrial campuses all over North America and Europe, including: Xerox/PARC, Microsoft, Colgate University, Northeastern University, UMCP and Oxford University (Oxford Internet Institute). He currently resides in Somerville, MA.


Vladimir Barash is instructor of the following workshop:

    Steve Bishop
    Steve Bishop

    Data Scientist

    Steve Bishop is a Data Scientist for Dow Jones & Company, Inc. in Princeton, NJ. Steve has developed a variety of analytical tools for internal stakeholders, and has promoted the value of data-driven insights across the company’s B2B Sales and Product teams through customer risk and user segmentation models. He has a BSBA from the University of Miami with a concentration in Management Science.

    Steve Bishop is speaking in the following session:

    Robert Blanchard
    Robert Blanchard

    SAS Senior Data Scientist.

    Robert is a Senior Data Scientist at SAS where he builds end-to-end artificial intelligence applications.  He also researches, consults, and teaches machine learning with an emphasis on deep learning and computer vision for SAS. Robert has authored a book on computer vision and has developed several professional courses on topics including neural networks, deep learning, and optimization modeling. Before joining SAS, Robert worked under the Senior Vice Provost at North Carolina State University, where he built models pertaining to student success, faculty development, and resource management. Robert also started a private analytics company while working at North Carolina State University that focused on predicting future home sales. Prior to working in academia, Robert was a member of the research and development group on the Workforce Optimization team at Travelers Insurance. His models at Travelers focused on forecasting and optimizing resources. Robert graduated with a master’s degree in Business Analytics and Project Management from the University of Connecticut and a master’s degree in Applied and Resource Economics from East Carolina University.

    Robert Blanchard is speaking in the following session:

    Clinton Brownley
    Clinton Brownley

    Data Scientist

    Clinton Brownley, Ph.D., is a data scientist at WhatsApp, where he’s responsible for a variety of analytics projects designed to improve messaging and VoIP calling performance and reliability.  Before WhatsApp, Clinton was a data scientist at Facebook, working on large-scale infrastructure analytics projects to inform hardware acquisition, maintenance, and data center operations decisions.  As an avid student and teacher of modern analytics techniques, Clinton is the author of two books, “Foundations for Analytics with Python” and “Multi-objective Decision Analysis,” and also teaches Python programming and data science courses at Facebook and in the Bay Area. Clinton is a past-president of the San Francisco Bay Area Chapter of the American Statistical Association and is a council member for the Section on Practice of the Institute for Operations Research and the Management Sciences. Clinton received degrees from Carnegie Mellon University and American University.

    Clinton Brownley is instructor of the following workshop:

    Val Carey
    Val Carey

    Data Scientist

    Valerie Carey joined Paychex in 2018, and focuses on exploratory analysis and client-facing analytics.  Prior to Paychex, Valerie was employed as a data scientist and a business analyst in healthcare related fields.  In addition, she has worked writing automated tests for a Unix operating system, and has a PhD in biophysics from Cornell University. 

    While enjoying the fun of data munging and the joy of discovery, Valerie’s deepest passion is building trust in data products and processes.  She prefers a comprehensive approach to data projects, emphasizing education and communication, automated testing, and iterative feedback.  Valerie believes that explainable AI is just one part of a journey to a comprehensible and useful model. 

    James Casaletto
    James Casaletto

    PhD Candidate

    UC Santa Cruz Genomics Institute and former Senior Solutions Architect, MapR

    James Casaletto is studying bioinformatics and biomedical engineering at UC Santa Cruz.  Previously, he worked at MapR Technologies where he designed, implemented, and deployed complete solution frameworks for big data. He has written and delivered courses on MapReduce programming, data engineering, and data science on Hadoop to thousands of students around the world.

    James Casaletto is instructor of the following workshop:

      Mark Do Couto
      Mark Do Couto

      Senior Vice President Data Analytics

      As SVP of Data Analytics for Altair, Mark is responsible for the global strategy for the Data Analytics business unit. This includes sales, pre-sales, support, consulting/services and product guidance. Altair's Data Analytics suite is focused on helping organization leverage AI and machine learning to make better business decisions.Mark possesses over 15 years of sales experience with a distinct focus on business intelligence, data mining and analytics. His deep understanding of Predictive Analytics and Machine Learning coincide with his need to nurture and maintain strong business relationships. He is passionate about collaborating with different organizations to discover the best solution to their specific challenges across multiple channels.

      Mark Do Couto is speaking in the following session:

      Matt Eckert
      Matt Eckert

      Sr. Data Scientist

      Matt Eckert is a Sr. Data Scientist at Marriott International applying Machine Learning to the digital domain. He has also help build out the Advanced Data Science platform for development and activation of models. He holds a B.S. in Computer Science from University of Maryland- College Park and M.S. in Computer Science from University of Maryland- Baltimore County

      Matt Eckert is speaking in the following session:

      John Elder Ph.D.
      John Elder Ph.D.

      Founder & Chair

      John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, Washington DC, and London. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia.

      Bill Franks
      Bill Franks

      Chief Analytics Officer

      Bill Franks is the Director of the Center for Statistics and Analytical Research at Kennesaw State University. He is also Chief Analytics Officer for The International Institute For Analytics (IIA) and serves on several advisory boards. Franks is the author of the books Taming The Big Data Tidal WaveThe Analytics Revolution, and 97 Things About Ethics Everyone In Data Science Should Know. He is a sought after speaker and frequent blogger who has been ranked a top global big data influencer, a top global artificial intelligence and big data influencer, a top AI influencer, and was an inaugural inductee into the Analytics Hall of Fame. His work, including several years as Chief Analytics Officer for Teradata (NYSE: TDC), has spanned clients in a variety of industries for companies ranging in size from Fortune 100 companies to small non-profit organizations.  You can learn more at http://www.bill-franks.com.

      Bill Franks is speaking in the following session:

      Mikhail Golovnya
      Mikhail Golovnya

      Senior Advisory Data Scientist

      Mikhail Golovnya has been prototyping new machine learning algorithms and modeling automation for the past 20 years. He has been a major contributor to Salford Systems / Minitab’s on-going search for technological improvements to among the most important algorithms in Machine Learning: CART® Decision Trees, MARS® Non-linear Regression, TreeNet® gradient boosting, and Random Forests®. Mikhail has presented at multiple conferences and seminars. He has also been teaching the mathematical foundations and applications of major predictive learning algorithms, both classical and modern. Having two master’s degrees, one in rocket science from Kharkov State Polytechnic University (Ukraine) and another in statistical computing from the University of Central Florida (Orlando), he currently serves in the role of Senior Advisory Data Scientist and is leading the next generation of Minitab machine learning product development. 

      Mikhail Golovnya is speaking in the following session:

      Peter Grabowski
      Peter Grabowski

      Software Engineering Manager

      Peter Grabowski is a longtime Googler and former Nest employee. He's currently the manager of the Enterprise Machine Learning team in Austin. Previously, he managed a data engineering team at Nest and helped build the Assistant for Kids team at Google. Outside of Google, he teaches machine learning as part of UC Berkeley's Master's in Data Science, and is a managing partner of PXN Residential, LLC.

      Peter Grabowski is speaking in the following session:

      Eui-Hong (Sam) Han Ph.D.
      Eui-Hong (Sam) Han Ph.D.

      Vice President, Advanced Data Science

      Eui-Hong (Sam) Han is Vice President, Advanced Data Science at Marriott International. Previously he was Director, Data Science & AI at The Washington Post where his team built tools and services to provide personalized customer experience, to empower newsroom with data-driven decisions and to provide targeted advertising capability. His expertise includes AI, machine learning, data mining, information retrieval and high-performance computing. He holds PhD in Computer Science from the University of Minnesota.

      Eui-Hong (Sam) Han Ph.D. is speaking in the following session:

      Matt Klubeck
      Matt Klubeck

      Data Scientist

      Matt Klubeck is a Data Scientist for Dow Jones & Company, Inc. in Princeton, NJ. He leverages data modeling to surface actionable insights for strategic B2B initiatives, including optimizing resource allocations in the business and reducing customer churn. Matt has also led Dow Jones’ Data Academy courses in data visualization and Python. He received his Bachelor’s degree in Mathematics from The College of New Jersey and a Master’s in BI & Analytics from Saint Joseph’s University.

      Matt Klubeck is speaking in the following session:

      Anastasiia Kornilova
      Anastasiia Kornilova

      Machine Learning Scientist

      Anastasiia Kornilova is a Machine Learning Scientist at Booking.com. In the last two years at Booking.com, she worked on the personalization of the website to the user needs (vacation rentals segment ) with a focus on a machine learning based quality rating system for alternative accommodations. Prior to Booking.com, Anastasiia has five years of experience in applying ML in various domains: healthcare, e-commerce, hospitality. Her main research interest is ML explainability in production.

      Aric LaBarr
      Aric LaBarr

      Associate Professor of Analytics

      A Teaching Associate Professor in the Institute for Advanced Analytics, Dr. Aric LaBarr is passionate about helping people solve challenges using their data. There he helps design the innovative program to prepare a modern workforce to wisely communicate and handle a data-driven future at the nation's first master of science in analytics degree program. He teaches courses in predictive modeling, forecasting, simulation, financial analytics, and risk management.

      Previously, he was Director and Senior Scientist at Elder Research, where he mentored and lead a team of data scientists and software engineers. As director of the Raleigh, NC office he worked closely with clients and partners to solve problems in the fields of banking, consumer product goods, healthcare, and government.

      Dr. LaBarr holds a B.S. in economics, as well as a B.S., M.S., and Ph.D. in statistics — all from NC State University.

      Richard Lee
      Richard Lee

      Director of Advanced Analytics

      Richard Lee is Director of Data Science for John Hancock, the U.S. division of Toronto-based Manulife.

      Richard leads the Advanced Analytics & AI group, which supports operations decision analytics across all U.S. businesses.

      In his current role, Richard finds opportunities for efficiencies in Life Insurance as well as Long Term Care Insurance operations. Much of his focus is on innovation to enhance the relevance and understanding of analytics and its impact on operations decision-making.

      Prior to his current role, Richard has spent 15 years at John Hancock in various analytics roles

      Richard Lee is speaking in the following session:

      Andrey Malevich
      Andrey Malevich

      Technical Lead Manager

      Andrey is a Technical Lead Manager at Facebook.

      During his career he had a chance to be participate in building multiple generations of ranking and recommendation models as well as Facebook AI Personalization Platform.

      His interests include Artificial Intelligence, High Performance Computing, Graph Learning and Personalization.

      Andrey Malevich is speaking in the following session:

      Jaya Mathew
      Jaya Mathew

      Senior Data Scientist

      Jaya Mathew is a Senior data scientist at Microsoft where she is part of the Artificial Intelligence and Research team. Her work focuses on the deployment of AI and ML solutions to solve real business problems for customers across multiple domains. Prior to joining Microsoft, she has worked with Nokia and Hewlett-Packard on various analytics and machine learning use cases. She holds an undergraduate as well as a graduate degree from the University of Texas at Austin in Mathematics and Statistics respectively.

      Jaya Mathew is speaking in the following session:

      Keith McCormick
      Keith McCormick

      Data Science Consultant, Trainer, Author, and Speaker

      Keith McCormick is an independent data miner, trainer, speaker, and author. For the last several years, his  emphasis has been working with analytics management to more efficiently run their teams and to nurture new hires as they expand their teams. Keith is skilled at explaining complex methods to new users or decision-makers and can do so at any level of technical detail. He specializes in predictive models and segmentation analysis including classification trees, neural nets, general linear model, cluster analysis, and association rules.

      Natalia Modjeska
      Natalia Modjeska

      Research Director

      Natalia Modjeska is a Research Director at Omdia (part of Informa Tech) where she leads the team of analysts covering Artificial Intelligence and Intelligent Automation from processors and software to enterprise deployments.

      Natalia’s journey into AI started in the late 1990’s with a PhD in NLP from the University of Edinburgh in Scotland. Since then she has worked in range of roles developing, deploying and evangelizing analytics and AI. Her diverse career includes R&D, product and program management, sales, consulting, and client advisory. She has worked with organizations of all sizes and levels of maturity across many industries and geographies helping clients to harness the power of data, advanced analytics and AI for transformative change. In the past four years she has advised 200+ organizations around the globe on topics ranging from strategy and use cases, to execution, best practices, governance, ethics, emerging trends, and vendor due diligence.

      Natalia is passionate about helping clients to demystify AI/ML, deploy these technologies responsibly and achieve sustainable business benefits. As part of this effort, she also serves as an AI expert on the ISO/IEC JTC 1/SC 42 - AI Standards working group and volunteers with several non-profits to develop responsible AI certification; and to increase AI literacy and improve government through innovative technologies.

      Robert Muenchen
      Robert Muenchen

      Manager of Research Computing Support

      Robert A. Muenchen () is the author of R for SAS and SPSS Users, and co-author of R for Stata Users and An Introduction to Biomedical Data Science. He is also the creator ofr4stats.com, a popular web site devoted to analyzing trends in data science software, reviewing such software, and helping people learn the R language.

      Bob is an ASA Accredited Professional Statistician™ who focuses on helping organizations migrate from SAS, SPSS, and Stata to the R Language. He has taught workshops on data science topics for more than 500 organizations and has presented workshops in partnership with the American Statistical Association, RStudio, DataCamp.com, and Revolution Analytics. Bob has written or co-authored over 70 articles published in scientific journals and conference proceedings and has provided guidance on more than 1,000 graduate theses and dissertations at the University of Tennessee.

      Bob has served on the advisory boards of SAS Institute, SPSS Inc., BlueSky Statistics, and the Statistical Graphics Corporation. His contributions have been incorporated into SAS, SPSS, JMP, jamovi, BlueSky Statistics, STATGRAPHICS, and numerous R packages. His research interests include data science software, graphics and visualization, machine learning, and text analytics.

      Robert Muenchen is instructor of the following workshop:

      Haig Nalbantian
      Haig Nalbantian

      Senior Partner, Co-leader Mercer Workforce Sciences Institute

      Haig R. Nalbantian is a Senior Partner at Mercer and a founder/leader of Mercer's Workforce Sciences Institute. A labor /organizational economist, he has been instrumental in developing Mercer's unique capability to measure the economic impact of human capital practices. Those capabilities have been applied in numerous projects he has directed for leading companies in the U.S. and abroad across a broad range of industries, including energy, high technology, manufacturing, consumer products, financial services, media and information services, telecommunications, and professional services. He has also consulted to organizations in the public and not-for-profit sectors. In recent years, Haig has worked extensively with high-profile organizations in the Middle East, with particular focus on strategic workforce planning, workforce strategies and metrics.

      Haig came to Mercer from National Economic Research Associates which he joined in 1989. Earlier, he was on the faculty of economics at New York University and was a research scientist at its C.V. Starr Center for Applied Economics. He is an internationally recognized expert in incentives, human capital measurement and management and their links to organizational performance. He has published widely on these topics in books and articles in leading academic and professional journals, such as the American Economic Review, The Journal of Labor Economics, The Harvard Business Review, Compensation and Benefits Review, WorldatWork, among many others. His HBR article, "Making Mobility Matter," received the Academy of Management's 2010 award for "Outstanding Practitioner-oriented Publication" in 2009.

      Nalbantian co-authored the prize-winning book on human capital measurement and management, Play to Your Strengths (McGraw Hill, 2004). He is also editor of and chief contributor to the book, Incentives, Cooperation and Risk Sharing and is a frequent speaker before industry groups, professional associations and academic audiences across the globe. He led the research team and co-authored the 2012 World Economic Forum/Mercer study of global talent mobility, "Talent Mobility Good Practices: Collaboration at the Core of Driving Economic Growth."

      Haig earned his BA in English and Economics at New York University and his graduate degrees in economics from Columbia University. He is a member of the American Economic Association.

      Kumaran Ponnambalam
      Kumaran Ponnambalam

      Director, AI

      Kumaran Ponnambalam has been working with data for more than 20 years. Data has always intrigued Kumaran and he has always searched for ways to mine, manage, and master it. Using analytics to solve business problems is his key interest domain.  He has successfully built and deployed data pipelines and machine learning models in the Customer Experience domain. He is also actively teaches courses on LinkedIn Learning (https://www.linkedin.com/learn... ) in the Big Data / Predictive Analytics domain.

      Kumaran Ponnambalam is speaking in the following session:

      Nicholas Pylypiw
      Nicholas Pylypiw

      Director of Data Science

      Nick is the Director of Data Science at Cape Fear Collective, a non-profit which supports Southeastern North Carolina’s front line organizations in combating poverty, racism, poor health and education outcomes, and socio-economic disparities. Prior to CFC, he honed his data science and consulting skills in the marketing analytics space, transforming the way Fortune 500+ companies (Lowe's Southwest Airlines, P&G, and many others) think about their customer strategy and value proposition. He lives in Raleigh, North Carolina.

      Nicholas Pylypiw is speaking in the following session:

      Thomas Schleicher
      Thomas Schleicher

      Sr. Director, Measurement Science

      Thomas Schleicher is a results-focused executive with nearly 20 years of experience in delivering actionable, data-based insights and profit-optimizing results for various high-profile clients across multifaceted, competitive industries. He is currently Senior Director of Measurement Science at National Consumer Panel, a joint venture of Nielsen and IRI. NCP is the largest longitudinal consumer panel in the world, and it provides the quality data its parent companies leverage to share consumer insights with their respective clients.

      Prior to his current role, Tom has had stints at Ipsos-ASI, Bayer HealthCare (Pharmaceuticals), and smaller analytic shops including Symphony Marketing Solutions and Spire, a Loyalty Marketing Analytics firm. Trained as an Experimental Social Psychologist (Ph.D. earned at the University of Wisconsin - Milwaukee), he is currently augmenting his statistical and social research methods expertise as he nears completion of his online Certificate in Predictive Analytics at UC-Irvine.

      Sarah Schmoller
      Sarah Schmoller

      Software Engineer - ML Automation

      Marc Smith
      Marc Smith

      Chief Social Scientist

      Dr. Marc A. Smith is a sociologist specializing in the social organization of online communities and computer mediated interaction. Smith leads the Connected Action consulting group. Smith co-founded the Social Media Research Foundation (http://www.smrfoundation.org/), a non-profit devoted to open tools, data, and scholarship related to social media research. He contributes to the open and free NodeXL project (http://nodexl.codeplex.com) that adds social network analysis features to the familiar Excel spreadsheet. NodeXL enables social network analysis of email, Twitter, Flickr, WWW, Facebook and other network data sets. Along with Derek Hansen and Ben Shneiderman, he is the co-author and editor of Analyzing Social Media Networks with NodeXL: Insights from a connected world, from Morgan-Kaufmann which is a guide to mapping connections created through computer-mediated interactions. Smith has published research on social media extensively, providing a map to the landscape of connected communities on the Internet.

      Marc Smith is instructor of the following workshop:

        David Stephenson Ph.D.
        David Stephenson Ph.D.

        Author and Founder

        David Stephenson is a data strategy consultant, corporate trainer and part-time faculty at the University of Amsterdam Business School.  He works alongside both regional and global companies to help them establish and develop their internal data science projects and programs. 

        David is also the author of Business Skills for Data Scientists: Practical Guidance in Six Key Topics.

        Nathan Susanj
        Nathan Susanj

        Applied Science Manager

        Previously Nathan was a data scientist on the Wells Fargo Enterprise Analytics and Data Science team where he led a small team as head of Natural Language Processing (NLP) and Speech Capabilities Development, and was focused on building out Wells Fargo's capabilities in areas related to NLP, deep learning and data science product design. Nathan holds a Masters in Predictive Analytics from Northwestern University and is working on his second Masters in Computer Science from Georgia Tech. He has been with Wells Fargo for the past five years and worked in marketing analytics prior to his current role.

        Nathan Susanj is speaking in the following session:

        Martin Szugat
        Martin Szugat

        Founder & Managing Director

        Martin Szugat is founder and managing director of Datentreiber, a data strategy consultancy supporting companies to digitally transform to a data-driven business. He invented the Data Strategy Design method and provides a free Data Strategy Designkit. Prior to Datentreiber, Martin Szugat was managing director of SnipClip, an agency for social media marketing & analytics. With a degree in bioinformatics, he has conducted research in machine learning and worked as a freelance software developer, consultant & author. Since 2014, he is responsible for the Predictive Analytics World & Deep Learning World conferences in Europe as program director.

        James Taylor
        James Taylor

        CEO

        James Taylor is the CEO of Decision Management Solutions and is a leading expert in how to use business rules and analytic technology to build decision management systems. He is passionate about using decision management systems to help companies improve decision-making and develop an agile, analytic and adaptive business. He provides strategic consulting to companies of all sizes, working with clients in all sectors to adopt decision-making technology. James is an expert member of the International Institute for Analytics and is the author of multiple books and articles on decision management, decision modeling, predictive analytics and business rules, and writes a regular blog at JT on EDM. James also delivers webinars, workshops and training. He is a regular keynote speaker at conferences around the world.

        James Taylor is speaking in the following session:

        James Taylor is instructor of the following workshop:

        James Taylor is moderator of the following session:

        PAW Financial

        Javed Ahmed
        Javed Ahmed

        Senior Data Scientist

        Javed Ahmed is a Senior Data Scientist with Metis, where he focuses on corporate training programs in Machine Learning and analytics. A financial economist by background, he has extensive experience developing analytic applications for large organizations including Amazon and the Federal Reserve Board of Governors. Javed holds a PhD in Finance and MA in Statistics from U.C. Berkeley, as well as undergraduate degrees in Finance and Systems Engineering from the University of Pennsylvania.

        Javed Ahmed is speaking in the following session:

        Muneeb Alam
        Muneeb Alam

        Specialist, Data Science

        Muneeb Alam is a data science specialist at QuantumBlack, a McKinsey Company. He has experience in the public and social sector, healthcare, energy and basic materials. He holds a B.A. in astrophysics from Columbia University and an MSc. in business analytics from Imperial College Business School.

        Tom Alby
        Tom Alby

        Chief Digital Transformation Officer

        Bala Venkatram Balantrapu
        Bala Venkatram Balantrapu

        Data Scientist

        Experienced Data Scientist with a demonstrated history of working in the insurance industry. Skilled in Machine Learning, Databases, Big Data Analytics, Big Data, Python, R, PySpark and Tableau. Strong engineering professional with a Master's degree focused in Computer Science from University of North Carolina at Charlotte. 

        Bala Venkatram Balantrapu is speaking in the following session:

        Robert Blanchard
        Robert Blanchard

        SAS Senior Data Scientist.

        Robert is a Senior Data Scientist at SAS where he builds end-to-end artificial intelligence applications.  He also researches, consults, and teaches machine learning with an emphasis on deep learning and computer vision for SAS. Robert has authored a book on computer vision and has developed several professional courses on topics including neural networks, deep learning, and optimization modeling. Before joining SAS, Robert worked under the Senior Vice Provost at North Carolina State University, where he built models pertaining to student success, faculty development, and resource management. Robert also started a private analytics company while working at North Carolina State University that focused on predicting future home sales. Prior to working in academia, Robert was a member of the research and development group on the Workforce Optimization team at Travelers Insurance. His models at Travelers focused on forecasting and optimizing resources. Robert graduated with a master’s degree in Business Analytics and Project Management from the University of Connecticut and a master’s degree in Applied and Resource Economics from East Carolina University.

        Robert Blanchard is speaking in the following session:

        Val Carey
        Val Carey

        Data Scientist

        Valerie Carey joined Paychex in 2018, and focuses on exploratory analysis and client-facing analytics.  Prior to Paychex, Valerie was employed as a data scientist and a business analyst in healthcare related fields.  In addition, she has worked writing automated tests for a Unix operating system, and has a PhD in biophysics from Cornell University. 

        While enjoying the fun of data munging and the joy of discovery, Valerie’s deepest passion is building trust in data products and processes.  She prefers a comprehensive approach to data projects, emphasizing education and communication, automated testing, and iterative feedback.  Valerie believes that explainable AI is just one part of a journey to a comprehensible and useful model. 

        John Elder Ph.D.
        John Elder Ph.D.

        Founder & Chair

        John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, Washington DC, and London. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia.

        John Elder Ph.D. is speaking in the following session:

        Mikhail Golovnya
        Mikhail Golovnya

        Senior Advisory Data Scientist

        Mikhail Golovnya has been prototyping new machine learning algorithms and modeling automation for the past 20 years. He has been a major contributor to Salford Systems / Minitab’s on-going search for technological improvements to among the most important algorithms in Machine Learning: CART® Decision Trees, MARS® Non-linear Regression, TreeNet® gradient boosting, and Random Forests®. Mikhail has presented at multiple conferences and seminars. He has also been teaching the mathematical foundations and applications of major predictive learning algorithms, both classical and modern. Having two master’s degrees, one in rocket science from Kharkov State Polytechnic University (Ukraine) and another in statistical computing from the University of Central Florida (Orlando), he currently serves in the role of Senior Advisory Data Scientist and is leading the next generation of Minitab machine learning product development. 

        Mikhail Golovnya is speaking in the following session:

        Abhishek Joshi ‘AJ’
        Abhishek Joshi ‘AJ’

        Senior Director

        Abhishek Joshi ‘AJ’ is a Sr. Director in Visa’s consulting & analytics group. He is responsible for helping financial institutions with improving growth and profitability through advanced analytics techniques. AJ has diverse experience in employing analytics to solve business problems across multiple industries – Manufacturing & Engineering, Financial Services and Telecom. 

        Abhishek Joshi ‘AJ’ is speaking in the following session:

        Ian Knopke
        Ian Knopke

        Senior Data Scientist

        Ian Knopke recieved his Ph.D. in Computer Science from McGill University, specializing in music search systems. He also worked as a researcher at academic institutions in the US and the UK before joining the BBC as their first data scientist, to work on applied R&D projects for TV, Radio, Sport, News, and the World Service Group. He later worked on data science problems for the Financial Times, Springer Nature, and Elsevier, as well as a couple of AI startups specializing in NLP. Ian joined Thomson Reuters as a Senior Data Scientist in the Reuters Applied Innovation group in 2020 and has also taken on an additional role as a new father in March.

        Aric LaBarr
        Aric LaBarr

        Associate Professor of Analytics

        A Teaching Associate Professor in the Institute for Advanced Analytics, Dr. Aric LaBarr is passionate about helping people solve challenges using their data. There he helps design the innovative program to prepare a modern workforce to wisely communicate and handle a data-driven future at the nation's first master of science in analytics degree program. He teaches courses in predictive modeling, forecasting, simulation, financial analytics, and risk management.

        Previously, he was Director and Senior Scientist at Elder Research, where he mentored and lead a team of data scientists and software engineers. As director of the Raleigh, NC office he worked closely with clients and partners to solve problems in the fields of banking, consumer product goods, healthcare, and government.

        Dr. LaBarr holds a B.S. in economics, as well as a B.S., M.S., and Ph.D. in statistics — all from NC State University.

        Carrie Lu Ph.D.
        Carrie Lu Ph.D.

        Senior Data Scientist

        Carrie (Caimei) Lu is a Senior Data Scientist at Safety National. She has over eight years of experience in using machine learning to generate insights from huge amounts of data, and using data science technologies to solve challenging business problems where data holds the key. At Safety National, Carrie Lu works with insurance business stakeholders on developing predictive models that can flag potential high risk and help the company reduce cost on long-term developmental claims. Carrie Lu holds Ph.D. in Information Science from Drexel University. She has over 15 published papers in the fields of Data Mining and Machine Learning.

        Carrie Lu Ph.D. is speaking in the following session:

        Michael Lyons
        Michael Lyons

        Manager, Data Science

        Michael Lyons manages a Data Science team at Paychex.  The team produces predictive models used throughout the company and is responsible for the Paychex | IHS Markit Small Business Employment Watch which gauges small business wage and employment trends on a national, regional, state, metro, and industry basis.  He had a long career in information systems at Xerox Corporation prior to joining the Buffalo Bills as their first Director of Analytics, building the department and capabilities over the course of five seasons which culminated with the team making their first playoff appearance in 18 years.

        Michael Lyons is speaking in the following session:

        Keith McCormick
        Keith McCormick

        Data Science Consultant, Trainer, Author, and Speaker

        Keith McCormick is an independent data miner, trainer, speaker, and author. For the last several years, his  emphasis has been working with analytics management to more efficiently run their teams and to nurture new hires as they expand their teams. Keith is skilled at explaining complex methods to new users or decision-makers and can do so at any level of technical detail. He specializes in predictive models and segmentation analysis including classification trees, neural nets, general linear model, cluster analysis, and association rules.

        Syed Mehmud
        Syed Mehmud

        Principal & Senior Consulting Actuary, ASA

        Syed Mehmud, ASA, MAAA, FCA, is a Principal and Senior Consulting Actuary in the Denver office of Wakely. Syed is a recognized expert on risk adjustment and actuarial applications of predictive modeling. Through the combination of large scale actuarial projects and developing popular product offerings, Syed has served most health plans in the United States in some capacity. He has worked on a variety of healthcare related projects, particularly involving the application of risk adjustment tools and implementation of risk adjustment methodologies.

        Syed has worked on risk adjustment with clients in Medicare, Medicaid, and Commercial settings. His recent work includes a large-scale actuarial consulting engagement where the Wakely team simulated the HHS risk adjustment methodology in over 30 individual and small group markets across the United States. His other works include the conception and development of the Wakely Risk Assessment (WRA) model, advanced Risk Score Optimization (RSO) analytics, the Wakely RAPID program, and the Wakely Risk Insight (WRI) program.

        Most recently, Syed and his team have executed an on-going national-scale project aimed at understanding the drivers of success and challenges in the Affordable Care Act (ACA) program. The Wakely Risk Insight – National Reporting (WRINR) project is a unique lens on the ACA program in that it uses detailed data on millions of ACA lives in order to uncover insights related to succeeding in this program.

        Syed co-authored (with Ross Winkelman) the 2007 Society of Actuaries' study on the comparative assessment of risk assessment models. Syed led a 2012 Society of Actuaries’ study on Uncertainty in Risk Adjustment. His other major published works include Society of Actuaries research project titled 'Non-Traditional Predictors in Risk Assessment' (SOA, 2013), and Risk Scoring in Health Insurance – A Primer (SOA, 2016). He is also in the process of writing a book on predictive modeling.

        Syed Mehmud is speaking in the following session:

        Natalia Modjeska
        Natalia Modjeska

        Research Director

        Natalia Modjeska is a Research Director at Omdia (part of Informa Tech) where she leads the team of analysts covering Artificial Intelligence and Intelligent Automation from processors and software to enterprise deployments.

        Natalia’s journey into AI started in the late 1990’s with a PhD in NLP from the University of Edinburgh in Scotland. Since then she has worked in range of roles developing, deploying and evangelizing analytics and AI. Her diverse career includes R&D, product and program management, sales, consulting, and client advisory. She has worked with organizations of all sizes and levels of maturity across many industries and geographies helping clients to harness the power of data, advanced analytics and AI for transformative change. In the past four years she has advised 200+ organizations around the globe on topics ranging from strategy and use cases, to execution, best practices, governance, ethics, emerging trends, and vendor due diligence.

        Natalia is passionate about helping clients to demystify AI/ML, deploy these technologies responsibly and achieve sustainable business benefits. As part of this effort, she also serves as an AI expert on the ISO/IEC JTC 1/SC 42 - AI Standards working group and volunteers with several non-profits to develop responsible AI certification; and to increase AI literacy and improve government through innovative technologies.

        Mei Najim
        Mei Najim

        CSPA, Founder and Lead Data Scientist

        Advanced Analytics Consulting Services, LLC

        Mrs. Mei Najim, CSPA, Founder and Lead Data Scientist is the Co-Chair of PAW for Financial.  

        She provides advanced analytics consulting services including developing full life cycle predictive modeling processes from raw data exploration to model implementation into IT data systems, thorough documentation, and related training.  Mei has over 14 years hands-on advanced analytics and machine learning experience dealing with large and complex data sets in various types of predictive analytics settings (claims, underwriting, pricing).  She also has extensive traditional actuarial analysis experience including pricing, reserving, and research & development in the insurance industry. She has presented at many conferences to share and discuss her papers and expertise in predictive analytics with industry analytics experts. 

        Mei holds a Bachelor of Science in Actuarial Science from Hunan University and two Master of Science degrees, in Applied Mathematics and in Statistics, from Washington State University.  Mei is a member of the American Statistical Association and a Certified Specialist in Predictive Analytics (CSPA) of the Casualty Actuarial Society.

        George Papaioannou
        George Papaioannou

        Director, Senior Trading Strategist

        George Papaioannou, is a Senior Trading Strategist within the Scientific Implementation Group of Bank of America Merrill Lynch. A Global quantitative team employing systematic, quantitative and scientifically informed methodologies around execution, portfolio management, and risk management, with emphasis on development of client solutions. George joined BAML in May 2018, following 12 years in energy major Shell, where he worked on a variety of functions. His latest role was in a team of computational science specialists, advising on machine learning, data, cloud, and high performance computing projects. He has previously worked in production operations, oil and gas forecasting, production optimization, reservoir management, development and project execution, for offshore fields in Brunei. The first 5 years of his industry career he worked in R&D as a scientific software developer focusing on scalable solvers and high performance computing.  George holds a PhD in Computational Fluid Mechanics from the Massachusetts Institute of Technology, where he also completed two MSc degrees and worked as a post-doctoral associate for a year. He has authored academic articles and acted as referee for several scientific journals.

        George Papaioannou is speaking in the following session:

        Andreas Petrides PhD
        Andreas Petrides PhD

        Executive Director, Quantitative Execution Services

        Andreas is an Executive Director at Goldman Sachs Quantitative Execution Services, focusing on signal research for execution algorithms. Andreas has received a PhD in Information Engineering at the University of Cambridge, working on the interface of stochastic control theory and Bayesian machine learning. Andreas also holds a BA and an MEng degree in Electrical and Information Sciences from Trinity College, University of Cambridge, during which he has received the G-Research and TTP awards.

        Andreas Petrides PhD is speaking in the following session:

        Viktoriia Samatova
        Viktoriia Samatova

        Head of Technology Innovation

        Viktoriia Samatova is a Director of Applied Innovation team of Data Scientists within Reuters Technology division focused on discovering and applying new technologies to enhance Reuters products and improving efficiency of news content production and discoverability. Prior to joining Reuters, Viktoriia spent over 5 years at State Street Bank’s Global Exchange division where she was managing product development of academic and financial industry content ingestion platform, which was the first company-wide product application utilizing emerging technologies of AI and machine learning.

        Harphajan Singh
        Harphajan Singh

        Head Of Analytics

        With over 20 years of professional expertise, Harphajan has led global business transformations across Wealth Management, Insurance, Retail and Institution Asset Management as well as Corporate Business Strategy in a diverse set of markets 

        Harphajan Singh is speaking in the following session:

        Tarun Sood
        Tarun Sood

        Head of Data and Analytics

        Tarun Sood is head of data and analytics in Vanguard Institutional Investor Group. He leads four different teams; Data Management and Governance: Business Intelligence and Reporting; Data Science and AI; Data and ML Engineering. The main goal of his group is to deliver actionable insights to the business in a timely manner. Prior to Joining Vanguard, Tarun worked as a strategy and analytics leader in a consulting capacity for over 15 years. He has implemented various solutions: Big Data & predictive Analytics, Advanced visualizations & Business Intelligence, Data Lakes both on premise and on cloud, Internet of Things (IoT), Enterprise Data Warehousing, Enterprise Data Governance, and multi domain Master Data Management. He has a track record of establishing and maintaining successful partnerships with Business and IT executives. He has successfully led large global teams with multi-million dollar portfolios across the Americas and Asia with a proven record of accomplishments.

        Tarun Sood is speaking in the following session:

        Michael Steliaros
        Michael Steliaros

        Managing Director

        Michael Steliaros is the global head of Quantitative Execution Services at Goldman Sachs. He is responsible for the research, development and implementation of quantitative processes for portfolio and electronic trading as well as managing the bank's relations with the quantitative client base. Previously, Michael held a variety of senior roles at BofAML in London and New York, most recently running the global agency portfolio trading and quantitative equity businesses. Earlier in his career, he spent a decade on the buy-side (most notably BGI and Winton) building quant stock-selection models and managing global market neutral equity portfolios. Michael received a bachelor's degree in Economics & Econometrics from the University of Nottingham, and an MSc and PhD in Finance from City University (CASS) Business School in London

        Michael Steliaros is speaking in the following session:

        David Stephenson Ph.D.
        David Stephenson Ph.D.

        Author and Founder

        David Stephenson is a data strategy consultant, corporate trainer and part-time faculty at the University of Amsterdam Business School.  He works alongside both regional and global companies to help them establish and develop their internal data science projects and programs. 

        David is also the author of Business Skills for Data Scientists: Practical Guidance in Six Key Topics.

        David Stephenson Ph.D. is speaking in the following session:

        Nathan Susanj
        Nathan Susanj

        Applied Science Manager

        Previously Nathan was a data scientist on the Wells Fargo Enterprise Analytics and Data Science team where he led a small team as head of Natural Language Processing (NLP) and Speech Capabilities Development, and was focused on building out Wells Fargo's capabilities in areas related to NLP, deep learning and data science product design. Nathan holds a Masters in Predictive Analytics from Northwestern University and is working on his second Masters in Computer Science from Georgia Tech. He has been with Wells Fargo for the past five years and worked in marketing analytics prior to his current role.

        Nathan Susanj is speaking in the following session:

        Edo van Uitert
        Edo van Uitert

        Senior Data Scientist/Team Lead

        Edo van Uitert started working for ABN AMRO in 2018 as data scientist for the Non-Financial Risk grid, where he worked on a variety of topics, including a text mining analysis of customer complaints and a predictive model for credit fraud. In August 2019 he moved to the Detecting Financial Crime Data Science Innovation team, where he develops novel advanced analytics methods to improve transaction monitoring. In 2012 Edo obtained his PhD in astronomy from Leiden University on the topic of weak gravitational lensing. After six years of research at the University of Bonn and University College London, he decided to change careers and transitioned into data science.

        Edo van Uitert is speaking in the following session:

        Min Yu
        Min Yu

        Lead Data Scientist

        Axis Capital

        Min Yu is a Lead Data Scientist at Axis Capital. She specializes in AI transformation of the insurance business including personal, commercial, and specialty lines by developing and deploying machine learning models within the business process. Min holds a Ph.D. in Physics from the University of Illinois at Urbana-Champaign.

        Min Yu is speaking in the following session:

        Jing Zhu
        Jing Zhu

        Risk Modeling Analyst

        Paychex Inc.

        Jing Zhu is a Risk Modeling Analyst at Paychex Inc., a leading provider of payroll, human resource, insurance, and benefits outsourcing solutions for small- to medium-sized businesses. Jing's main responsibility is developing models to help with strategic decisions across all aspects of the business, including effectively targeting retention strategies, assisting in dynamic cross-sell initiatives, and improving collection targets. Jing holds a PhD in Biology from the University of Rochester, where she applied statistics in biological research.

        Jing Zhu is speaking in the following session:

        PAW Healthcare

        Dean Abbott
        Dean Abbott

        President

        Dean Abbott is Co-Founder and Chief Data Scientist of Smarter Remarketer, Inc., and President of Abbott Analytics, Inc. in San Diego, California. Mr. Abbott is an internationally recognized data mining and predictive analytics expert with over two decades experience applying advanced data mining algorithms, data preparation techniques, and data visualization methods to real-world problems, including fraud detection, risk modeling, text mining, personality assessment, response modeling, survey analysis, planned giving, and predictive toxicology.

        Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and co-author of IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a highly-regarded and popular speaker at Predictive Analytics and Data Mining conferences and meetups, and is on the Advisory Boards for the UC/Irvine Predictive Analytics Certificate as well as the UCSD Data Mining Certificate programs.

        He has a B.S. in Mathematics of Computation from Rensselaer (1985) and a Master of Applied Mathematics from the University of Virginia (1987).

        Dean Abbott is speaking in the following session:

        Javed Ahmed
        Javed Ahmed

        Senior Data Scientist

        Javed Ahmed is a Senior Data Scientist with Metis, where he focuses on corporate training programs in Machine Learning and analytics. A financial economist by background, he has extensive experience developing analytic applications for large organizations including Amazon and the Federal Reserve Board of Governors. Javed holds a PhD in Finance and MA in Statistics from U.C. Berkeley, as well as undergraduate degrees in Finance and Systems Engineering from the University of Pennsylvania.

        Javed Ahmed is speaking in the following session:

        Benjamin Arias-Gálvez
        Benjamin Arias-Gálvez

        General Manager

        Benjamin Arias is Co-Founder and Head of Consultancy at Foresta.IO. He combines operational and information technology experience since he has led operational improvement teams for Nestle in the US, Europe, Asia and Latin America during seven years. Mr. Arias has also been the CIO for the biggest fresh fruit broker in the America’s Pacific Coast for ten years and also been the Corporate Head of Industrial Engineering for Unilever at its Heardquarters in Schaffhausen, Switzerland for three years, before returning back home to Chile.

        Mr. Arias is an Industrial Engineer (1997) with a Master Degree in Information Technology and Artificial Intelligence (2012) and also a lecturer at his alma mater for last year undergraduate students and a presenter for the topic of operational efficiency with algorithms and AI at Berlin, Germany (2019) and Santiago de Chile (2020).

        Benjamin Arias-Gálvez is speaking in the following session:

        Robert Blanchard
        Robert Blanchard

        SAS Senior Data Scientist.

        Robert is a Senior Data Scientist at SAS where he builds end-to-end artificial intelligence applications.  He also researches, consults, and teaches machine learning with an emphasis on deep learning and computer vision for SAS. Robert has authored a book on computer vision and has developed several professional courses on topics including neural networks, deep learning, and optimization modeling. Before joining SAS, Robert worked under the Senior Vice Provost at North Carolina State University, where he built models pertaining to student success, faculty development, and resource management. Robert also started a private analytics company while working at North Carolina State University that focused on predicting future home sales. Prior to working in academia, Robert was a member of the research and development group on the Workforce Optimization team at Travelers Insurance. His models at Travelers focused on forecasting and optimizing resources. Robert graduated with a master’s degree in Business Analytics and Project Management from the University of Connecticut and a master’s degree in Applied and Resource Economics from East Carolina University.

        Robert Blanchard is speaking in the following session:

        Jeff Deal
        Jeff Deal

        Chief Operating Officer

        Jeff Deal is the Chief Operating Officer for Elder Research, the nation's leading data science, machine learning, and artificial intelligence consultancy. He has also been the Chair of the Predictive Analytics World for Healthcare conference since its inception in 2014.  In his role at Elder Research, Jeff oversees the operations of the business including contracting, finances, regulatory/legal issues and human resources. Jeff has worked with dozens of clients to understand their business needs and organizational goals and, in the process, has gained insight into organizational obstacles to successful data analytics engagements. His talk on the Top 10 Data Mining Business Mistakes has been well received at prior Predictive Analytics World conferences. In 2016, Jeff and the Elder Research President & CEO, Gerhard Pilcher, published, Mining Your Own Business: A Primer for Executives on Understanding and Employing Data Mining and Predictive Analytics.

        Jeff has more than 30 years of experience in business operations, planning, and government relations, primarily in the health care industry. Prior to ERI, he was the president of a health planning consulting business that assisted hospitals and physicians with operational analysis, forecasting, and navigating through complex regulatory processes. Before that, Jeff spent 16 years in hospital administration with responsibility for clinical, support, and planning functions. Jeff has a Master of Health Administration degree from Virginia Commonwealth University and an undergraduate degree from the College of William and Mary.

        John Elder Ph.D.
        John Elder Ph.D.

        Founder & Chair

        John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, Washington DC, and London. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia.

        John Elder Ph.D. is speaking in the following session:

        Chris Franciskovich
        Chris Franciskovich

        Director, Advanced Analytics

        Chris is currently the Direct of Advanced Analytics at OSF Healthcare where he leads a team of data scientists and statisticians who create and deploy industry leading advanced analytics solutions.  He has more than 12 years of experience working in healthcare and holds a MS in Predictive Analytics from Northwestern University, where he focused on advanced modeling techniques and predictive text mining.

        Chris Franciskovich is speaking in the following session:

        Mark Gudesblatt
        Mark Gudesblatt

        Chief Medical Officer

        Dr. Gudesblatt, the medical director of the Comprehensive MS Care Center at South Shore Neurologic Associates, P.C., graduated from Johns Hopkins University in 1976 and from Cornell University Medical College in 1980. His postgraduate training included a medical internship and neurologic residency at Mount Sinai Hospital, where he was the Chief Resident, as well as a Clinical Research Fellow in Neuromuscular Disease through the National Institute of Health. Dr. Gudesblatt is certified by the American Board of Psychiatry and Neurology in the specialty of Neurology, is a diplomate in the American Academy of Pain Management, and has had additional training in Neuro-Rehabilitation. Dr. Gudesblatt has authored articles appearing in professional literature on numerous topics, including movement disorders, tumors of the brain and spinal cord, neurologic complications of pregnancy, stroke, familial inheritance of neurologic illness and multiple sclerosis. He also participates in clinical research at South Shore Neurologic, involving MS and other neurologic diseases.

        Tanvir Khan
        Tanvir Khan

        Senior VP & Chief Analytics Officer

        Capital District Physicians’ Health Plan (CDPHP)

        Veysel Kocaman
        Veysel Kocaman

        Lead Data Scientist

        Veysel is a Lead Data Scientist at John Snow Labs, improving the Spark NLP for Healthcare library and delivering hands-on projects in Healthcare and Life Science. He is a seasoned data scientist with a strong background in every aspect of data science including machine learning, artificial intelligence and big data with over ten years of experience. He’s also pursuing his PhD in ML at Leiden University, Netherlands and delivering graduate level lectures in ML and Distributed Data Processing. Veysel has broad consulting experience on Statistics, Data Science, Software Architecture, DevOps, Machine Learning and AI to several start-ups, bootcamps and companies around the globe. He also speaks at Data Science & AI events, conferences and workshops, and has delivered more than 30 talks at International as well as national conferences and meet-ups.

        Zhipeng Liu
        Zhipeng Liu

        Principal Data Scientist

        Zhipeng is a principal data scientist at Geneia. His focus is creating AI models that identify people at high risk for developing chronic conditions, while also helping care managers provide personalized management for high-risk patients. 

        Zhipeng is a researcher experienced in computational genomics, pharmacogenomics and causal inference. Before Geneia, he was an Insight Health Data Science-program Fellow, where he created a predictive model that uses EHR data to identify people at high risk for developing fatty liver diseases. At Purdue University, he studied how genetic factors contribute to the development of metabolic diseases and published six peer-reviewed papers in high-impact journals. Additionally, the highly-ranked Journal of Hepatology published part of his Ph.D. work. 

        Zhipeng holds a Master of Science in statistics and a Ph.D. in pharmacology from Purdue University. He also earned a master’s degree in biochemistry and bachelor’s degree in bioengineering. 

        Jorn op den Buijs PhD
        Jorn op den Buijs PhD

        Senior Scientist

        Jorn op den Buijs, PhD is a senior scientist at Philips Research, carrying out research on predictive analytics to predict and prevent emergency hospitalizations in the frail and elderly. Jorn op den Buijs has a Master’s in Biomedical Engineering from the Eindhoven University of Technology and a PhD degree in Biomedical Engineering from the Mayo Clinic Graduate School, Rochester Minnesota.

        Jorn op den Buijs PhD is speaking in the following session:

        Arjun Panesar
        Arjun Panesar

        Founder and CEO

        Arjun is the founder and CEO of Diabetes Digital Media. Arjun launched DDM's first service, Diabetes.co.uk (the world’s largest diabetes community) whilst in his first year of university in 2003 as a result of his grandfather’s quadruple heart bypass and diagnosis of type 2 diabetes. Benefiting from a decade of experience in big data and affecting user outcomes, Arjun leads the organisation's development of intelligent, evidence-based digital health interventions that harness the power of big data and machine learning to provide precise and personalized care to patients, health agencies and governments worldwide.

        DDM's Low Carb Program and Gro Health digital health interventions are regulated as Software as a Medical Device and redefining chronic disease and wellness.  Over 1.8 million members use a DDM service.

        Joe Perez Dr.
        Joe Perez Dr.

        Senior Systems Analyst / Team Lead

        With advanced degrees in computers and secondary education, along with several IT certifications, Dr. Perez brings more than 35 years of experience to the stage as an IT/higher ed professional. Having served as Business Intelligence Specialist at NC State University and currently serving as Senior Systems Analyst/Team Lead at the NC Department of Health & Human Services (DHHS), Perez stays active in the IT community with more than 11,000 LinkedIn followers. In addition to his full-time leadership role at DHHS, Perez has been named Chief Technology Officer at SolonTek Corporation.  A highly-recommended & experienced international keynote speaker, data analytics/visualization expert, and specialist in efficiency/process improvement, he is indeed a much sought-after resource. When taking a break from work, Joe sings, plays the piano, composes songs, & has performed PSA's and voice-overs for schools & other organizations. "I’m a firm believer that if I’m not innovating, I’m stagnating," says Joe.

        Joe Perez Dr. is speaking in the following session:

        Matthew Pietrzykowski
        Matthew Pietrzykowski

        Director, Data Science & Transformational Analytics

        Matt earned a MS in Physical Chemistry from the University of Rochester and a PGDip with distinction from DeMontfort University in Industrial Data Modeling. He began his career interfacing and automating instrumentation and sensors. When he joined General Electric 2004, he focused his career on applying the scientific method to analytics problems. Matt has applied data science to a varied array of fields including chemometrics, sustainability, industrial internet, and compliance.

        Matthew Pietrzykowski is speaking in the following session:

        Maneesh Shrivastav Ph.D.
        Maneesh Shrivastav Ph.D.

        Director of Market Development

        Maneesh Shrivastav is an accomplished, well rounded professional with exceptional academic credentials, deep clinical and technical knowledge and experience in Medical Devices spanning business development, market development, strategy, predictive analytics, and engineering across several therapeutic areas. Maneesh has a proven track record of successful international product launches, strategic partnerships deals, and commercialization schemes with start-ups and well established organizations. He is currently engaged in the intersection of market development and predictive analytics at Medtronic.

        Maneesh Shrivastav Ph.D. is speaking in the following session:

        Sara Stevens
        Sara Stevens

        Vice President of Analytics Operations

        Sara Stevens is Vice President of Analytics Operations at Capital District Physicians’ Health Plan (CDPHP), a non-profit, physician-governed insurer in upstate New York.  In this role, Sara leads a team of data scientists, informatics analysts, and statisticians to provide analytical insights to internal and external constituents.  Her specialty is in the conception, implementation, and evaluation of value-based provider payment programs designed in pursuit of the quadruple aim.

        Sara’s background in healthcare finance, along with her education in math and business, give her a unique and valuable perspective on alternate payment methods in healthcare.  Her ability to distil complex data sets down to consumable, actionable insights, coupled with her passion for impacting meaningful change in the healthcare landscape, give her a distinctive voice in the discussion around the use and adoption of analytics in this industry.

        Nathan Susanj
        Nathan Susanj

        Applied Science Manager

        Previously Nathan was a data scientist on the Wells Fargo Enterprise Analytics and Data Science team where he led a small team as head of Natural Language Processing (NLP) and Speech Capabilities Development, and was focused on building out Wells Fargo's capabilities in areas related to NLP, deep learning and data science product design. Nathan holds a Masters in Predictive Analytics from Northwestern University and is working on his second Masters in Computer Science from Georgia Tech. He has been with Wells Fargo for the past five years and worked in marketing analytics prior to his current role.

        Nathan Susanj is speaking in the following session:

        Mike Thurber
        Mike Thurber

        Principal Scientist

        Mike Thurber is the Lead Data Scientist in Elder Research's Commercial Analytics Group working across multiple teams and industries – including finance, retail, energy, and telecom – to deliver information products that drive business value.  Mike’s primary focus is healthcare and insurance, where his projects range from predicting extreme payouts on long-term care claims, and identifying healthcare provider fraud, to measuring the effect of Cesarean delivery on infant health. His expertise in collaboration, data exploration, predictive modeling and rigorous testing, and in remediating the selection bias common to analytic algorithms, creates confidence in the actions recommended by the analytic products of his team.

        Mike earned a BS degree in Chemical Engineering from Brigham Young University and a Master's degree in Statistics from Virginia Commonwealth University. For the last four years, Mike has been teaching principles and best practices of predictive modeling to a broad audience of emerging data scientists.

        Jaya Tripathi
        Jaya Tripathi

        Principal, Data Analytics

        Jaya Tripathi is a Principal Scientist and an advanced analytics expert in The MITRE Corporation’s Information Technology Technical Center. 

        She is the principal investigator in MITRE's effort to apply health IT concepts to address prescription drug misuse and abuse. She has been working in this domain for many years and has collaborated with law enforcement officials, physicians, policy makers, Board of Pharmacy, academicians and state and Federal partners.

        She has been at MITRE for 14 years. Before joining MITRE, Ms. Tripathi worked at several multinational corporations, applying big data analytics on projects such as a customer retention forecasting pilot for a major telecommunications company, and the origin-and-destination revenue management, one of the most significant innovations in the airline industry. She holds master’s degrees in physics and computer science from the University of Texas.

        Jaya Tripathi is speaking in the following session:

        PAW Industry 4.0

        Javed Ahmed
        Javed Ahmed

        Senior Data Scientist

        Javed Ahmed is a Senior Data Scientist with Metis, where he focuses on corporate training programs in Machine Learning and analytics. A financial economist by background, he has extensive experience developing analytic applications for large organizations including Amazon and the Federal Reserve Board of Governors. Javed holds a PhD in Finance and MA in Statistics from U.C. Berkeley, as well as undergraduate degrees in Finance and Systems Engineering from the University of Pennsylvania.

        Javed Ahmed is speaking in the following session:

        Robert Blanchard
        Robert Blanchard

        SAS Senior Data Scientist.

        Robert is a Senior Data Scientist at SAS where he builds end-to-end artificial intelligence applications.  He also researches, consults, and teaches machine learning with an emphasis on deep learning and computer vision for SAS. Robert has authored a book on computer vision and has developed several professional courses on topics including neural networks, deep learning, and optimization modeling. Before joining SAS, Robert worked under the Senior Vice Provost at North Carolina State University, where he built models pertaining to student success, faculty development, and resource management. Robert also started a private analytics company while working at North Carolina State University that focused on predicting future home sales. Prior to working in academia, Robert was a member of the research and development group on the Workforce Optimization team at Travelers Insurance. His models at Travelers focused on forecasting and optimizing resources. Robert graduated with a master’s degree in Business Analytics and Project Management from the University of Connecticut and a master’s degree in Applied and Resource Economics from East Carolina University.

        Robert Blanchard is speaking in the following session:

        Richard Boire
        Richard Boire

        President

        Richard Boire's experience in predictive analytics and data science dates back to 1983, when he received an MBA from Concordia University in Finance and Statistics. 

        His initial experience at organizations such as Reader’s Digest and American Express allowed  him to become a pioneer in the application of predictive modelling technology for all database and CRM type marketing programs. This extended to the introduction of models which targeted the acquisition of new customers based on return on investment.

        With this experience, Richard formed his own consulting company back in 1994 which is now called the Boire Filler Group, a Canadian leader in offering  analytical and database services to companies seeking solutions to their existing predictive analytics or database marketing challenges.

        Richard is a recognized authority on predictive analytics and is among a very few, select top five experts in this field in Canada, with expertise and knowledge that is difficult, if not impossible to replicate in Canada. This expertise has evolved into international speaking assignments and workshop seminars in the U.S., England, Eastern Europe, and Southeast Asia. 

        Within Canada, he gives seminars on segmentation and predictive analytics for such organizations as Canadian Marketing Association (CMA), Direct Marketing News, Direct Marketing Association Toronto, Association for Advanced Relationship Marketing (AARM) and Predictive Analytics World (PAW).  His written articles have appeared in numerous Canadian  publications such as  Direct Marketing News, Strategy Magazine, and Marketing Magazine. He has taught applied statistics, data mining and database marketing at a variety of institutions across Canada which include University of Toronto, George Brown College, Seneca College, and currently Centennial College. Richard was  Chair at the CMA's Customer Insight and Analytics Committee and  sat on the CMA's Board of Directors from 2009-2012. He has chaired numerous full day conferences on behalf of the CMA (the 2000 Database and Technology Seminar as well as the  2002 Database and Technology Seminar and the first-ever Customer Profitability Conference  in 2005. He has most recently chaired the Predictive Analytics World conferences in both 2013 and 2014 which were held in Toronto.

        He has co-authored white papers on the following topics: "Best Practices in Data Mining" as well as "Customer Profitability:  The State of Evolution among Canadian Companies."  In Oct. of 2014, his new book on "Data Mining for Managers-How to use Data (Big and Small) to Solve Business Problems" was published by Palgrave Macmillian.  In March of 2016, Boire Filler Group was acquired by Environics Analytics where his current role is senior vice-president of innovation.

        John Elder Ph.D.
        John Elder Ph.D.

        Founder & Chair

        John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, Washington DC, and London. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia.

        John Elder Ph.D. is speaking in the following session:

        Rishabh Gaur
        Rishabh Gaur

        Technical Architect

        A Software and AI enthusiast, Rishabh Gaur works as a Technical Architect at Microsoft Technology Center, where he works on advancing Microsoft's world view of Intelligent cloud and Intelligent Edge to our customers and partners. While working as a cross-domain architect, Rishabh specializes in Microsoft Power Platform, Azure IoT and Azure App Dev related service offerings. Albeit quite young, he carries significant expertise in setting up and working with global teams to deliver value for business by providing robust solutions and right technology choices. So much was his impact in a short span that at the completion of year 1 in industry, he was awarded with the prestigious Techie Award for Data & AI from Microsoft. In his day to day role, he acts as a strategy leader and a digital advisor for many global and regional customers for Microsoft.

        Sarah Kalicin
        Sarah Kalicin

        Data Scientist

        Intel

        Sarah Kalicin is a Data Scientist & Industrial Statistician with Intel Corporation, who is passionate about how business organizations gain more business value through Data Analytics. In her extensive data career at Intel, she develops strategic plans for analytic adoption to increase business impact. Working in various industry and government positions, such as Becton Dickinson (BD), Kraft Foods, Nabisco, Ford Motor Company, and USDA/National Agriculture Statistics Service, she has gain insight and experience on how successful organizations function that allow them to succeed in their analytic initiatives.  She holds a Master’s degree in Applied Statistics from the University of Michigan and Bachelors’ degrees in Mathematics and Psychology from the SUNY at Oswego.

        Sharan Kalwani
        Sharan Kalwani

        HPC practioner/Training Specialist

        Sharan Kalwani has been working in the manufacturing world in using HPC for accelerating simulation designs of engineering processes.. He was also the Subject Matter Expert and Project lead at hpcexperiment.com (now UberCloud), working on helping to realize HPC in the cloud, several years before it finally took hold.With 30 years of experience in Scientific and Technical computing, Sharan has worked at numerous HPC industry leaders that include Cray Research, Silicon Graphics, Intel, etc. He has also spent several years in the industry at General Motors managing their global engineering HPC centers, as well as in the academic domain, helping to fulfill their research computing missions.Sharan is a member of the ACM, Senior member of IEEE, Computer Society, Society of Automotive Engineers. He also runs the popular discussion group ’Innovative Uses of HPC’ on Linked In. He has given numerous tutorials and talks at Supercomputing, European PRACE Consortium, IB Trade Association, IDC HPC user Forum and several other

        Sharan Kalwani is speaking in the following session:

        Markus Larsson
        Markus Larsson

        Head of Predictive Maintenance

        Markus is a member of PARC’s Sr. leadership team. He brings 10+ years’ experience in corporate and startup innovation, and innovation partnership in the industrial and consumer sector. He is also an early stage tech enthusiast. Markus holds a M.Sc. in Industrial Engineering from Chalmers University of Tech.

        Markus Larsson is speaking in the following session:

        Allan Luk
        Allan Luk

        Director of Data Science and Analytics Business Solutions

        Allan has been a data storage solutions industry professional for 21 years. He held technical positions in different disciplines at Seagate from research, engineering, product development, operations, quality, customer experience engineering to analytics. He currently leads and manages global analytics teams in the US, Singapore, Thailand, and China for the operations and technology advanced analytics group (OTAAG) at Seagate. His teams support different business units in the area of analytics solutions research, development, deployment, and analytics upskilling functions.

        Andrey Malevich
        Andrey Malevich

        Technical Lead Manager

        Andrey is a Technical Lead Manager at Facebook.

        During his career he had a chance to be participate in building multiple generations of ranking and recommendation models as well as Facebook AI Personalization Platform.

        His interests include Artificial Intelligence, High Performance Computing, Graph Learning and Personalization.

        Andrey Malevich is speaking in the following session:

        Jaya Mathew
        Jaya Mathew

        Senior Data Scientist

        Jaya Mathew is a Senior data scientist at Microsoft where she is part of the Artificial Intelligence and Research team. Her work focuses on the deployment of AI and ML solutions to solve real business problems for customers across multiple domains. Prior to joining Microsoft, she has worked with Nokia and Hewlett-Packard on various analytics and machine learning use cases. She holds an undergraduate as well as a graduate degree from the University of Texas at Austin in Mathematics and Statistics respectively.

        Rob Montalvo
        Rob Montalvo

        President

        One of the founders of DataCrunch Lab, Mr. Montalvo has a bachelor's degree in Computer Engineering from the University of Puerto Rico. He has more than 20 years of experience developing enterprise software technology for companies including IBM, Ericsson, Alcatel Microelectronics, VMware, BlackBerry, Qualcomm, and Cisco.

        Rob Montalvo is speaking in the following session:

        Zeydy Ortiz
        Zeydy Ortiz

        CEO

        Dr. Zeydy Ortiz is the co-founder & CEO of DataCrunch Lab, LLC.  She has been helping teams and organizations transform data into value across many industries including IT,  financial, retail, and the manufacturing sectors.  Her team built an innovative, award-winning digital assistant that was recognized as 'Highest Potential Value to Manufacturers' for increasing visibility of real-time production and plant operations. 

        She started her career as a Performance Engineer at IBM building predictive models to inform business strategy.  She worked on multiple projects focused on improving performance & efficiency.  She earned recognition for innovation on Smarter Planet/IoT solutions and for her industry contributions defining resource efficiency metrics. Dr. Ortiz obtained her bachelor's degree from the University of Puerto Rico, master's from Texas A&M University, and Ph. D. in Computer Science from North Carolina State University.

        Zeydy Ortiz is speaking in the following session:

        Ramon Perez
        Ramon Perez

        Director of UK Operations

        Ramon Perez leads the Elder Research London office. A decorated war veteran, Major Perez served as an Air Force Intelligence Officer specializing in Signals Intelligence. As a mission director at the National Security Agency, Ramon led teams analyzing enormous data sets to produce actionable information in support of worldwide contingency operations–including deployments to Iraq, Afghanistan, and South America in support of Special Operations. Upon leaving the military, Ramon returned to graduate school with an interest in understanding economic models and became an Elder Research data scientist focused on building machine learning models to detect financial crime. He has since taken a leadership role and his team has been modeling risk within power production systems. Ramon holds a Bachelors degree in Systems Engineering from Georgia Tech as well as Masters degrees from Harvard and Georgetown in Finance and Economics, respectively.

        Ramon Perez is speaking in the following session:

        Suhas Pillai
        Suhas Pillai

        Deep Learning Engineer

        Suhas Pillai is a Deep Learning Engineer at Center for Deep Learning in Electronics Manufacturing (CDLe). At CDLe, his work focuses primarily on applying deep learning in semi conductor manufacturing, where there is data scarcity. His work at the Center has demonstrated that using synthetic data can leverage the potential of applying deep learning in areas where there is a dearth of data. In the past, he has worked in applying deep learning in Speech recognition, NLP and Computer Vision domains. He was associated with couple of startups, where he was responsible for developing Deep learning algorithms for detecting objects in satellite imagery and creating cognitive search engines. He holds a Masters in Computer Science from Rochester Institute of Technology.

        Kumaran Ponnambalam
        Kumaran Ponnambalam

        Director, AI

        Kumaran Ponnambalam has been working with data for more than 20 years. Data has always intrigued Kumaran and he has always searched for ways to mine, manage, and master it. Using analytics to solve business problems is his key interest domain.  He has successfully built and deployed data pipelines and machine learning models in the Customer Experience domain. He is also actively teaches courses on LinkedIn Learning (https://www.linkedin.com/learn... ) in the Big Data / Predictive Analytics domain.

        Kumaran Ponnambalam is speaking in the following session:

        Steven Ramirez
        Steven Ramirez

        CEO

        Steven J. Ramirez is the chief executive officer of Berkeley, Calif.-based Beyond the Arc, Inc., a firm recognized as a leader in helping companies transform their customer experiences by leveraging advanced analytics.

        In addition to developing and executing the vision for Beyond the Arc, Ramirez leads teams of data and strategy consultants committed to client success. They analyze customer and social media data, combined with text analysis, to drive customer growth, improve customer retention, understand service breaks and build stronger customer loyalty.

        Prior to leading Beyond the Arc, Ramirez served as an executive with Time Warner, where he was responsible for creating and successfully implementing marketing and corporate development strategies.

        Ramirez earned a bachelor's degree and master's in Business Administration from the University of California at Berkeley. He as also created and taught courses in business management for UC Berkeley and been a guest speaker at the university's Haas School of Business.

        Lauren Stern
        Lauren Stern

        Data Science Community Lead

        Lauren Stern is a dedicated tech professional, community leader, and overall advocate for data. She currently serves as the Data Science Community Lead at Audi of America, where she is responsible for building, supporting, and representing the Data Science Community (DSC), which comprises more than 70 individuals across every department within the organization. Her mission is to encourage digital collaboration across the departments and empower the business to work directly and effectively with their data.

        Lauren Stern is speaking in the following session:

        Nathan Susanj
        Nathan Susanj

        Applied Science Manager

        Previously Nathan was a data scientist on the Wells Fargo Enterprise Analytics and Data Science team where he led a small team as head of Natural Language Processing (NLP) and Speech Capabilities Development, and was focused on building out Wells Fargo's capabilities in areas related to NLP, deep learning and data science product design. Nathan holds a Masters in Predictive Analytics from Northwestern University and is working on his second Masters in Computer Science from Georgia Tech. He has been with Wells Fargo for the past five years and worked in marketing analytics prior to his current role.

        Nathan Susanj is speaking in the following session:

        Paul Turner
        Paul Turner

        Vice President I4.0 Applications & Analytics

        Paul leads Stanley Black & Decker's global strategy and efforts in leveraging Industry 4.0 Applications & Advanced Analytics to drive operational performance improvements as part of Industry 4.0 and the digital transformation of manufacturing. Touching over 40,000 employees and over 120 factories worldwide he is responsible for driving millions of dollars in value by leveraging the transformative capabilities of artificial intelligence, machine learning and advanced analytics in manufacturing.

        Deep Learning World

        Dean Abbott
        Dean Abbott

        Co-Founder and Chief Data Scientist

        Dean Abbott is Co-Founder and Chief Data Scientist of SmarterHQ, and President of Abbott Analytics, in San Diego, California. Mr. Abbott is an internationally recognized data science and predictive analytics expert with over three decades of experience. Abbott is the author of Applied Predictive Analytics (Wiley, 2014, 2nd edition forthcoming in 2020. He has a B.S. in Mathematics of Computation from Rensselaer (1985) and a Master of Applied Mathematics from the University of Virginia (1987).

        Dean Abbott is instructor of the following workshop:

        Javed Ahmed
        Javed Ahmed

        Senior Data Scientist

        Javed Ahmed is a Senior Data Scientist with Metis, where he focuses on corporate training programs in Machine Learning and analytics. A financial economist by background, he has extensive experience developing analytic applications for large organizations including Amazon and the Federal Reserve Board of Governors. Javed holds a PhD in Finance and MA in Statistics from U.C. Berkeley, as well as undergraduate degrees in Finance and Systems Engineering from the University of Pennsylvania.

        Javed Ahmed is speaking in the following session:

        Vladimir Barash
        Vladimir Barash

        Director

        Vladimir Barash is Director Graphika Labs. He has received his Ph.D. from Cornell University, where he studied Information Science and wrote his thesis on the flow of rumors and virally marketed products through social networks. At Graphika, Vladimir's research focuses on deep learning applications of network analysis, detection and deterrence of disinformation operations on networks, and causal mechanisms of large-scale social behavior.

        In addition to his research duties, Vladimir has a decade's experience working with big data, from scientific computing (Matlab, scipy) to parallel processing technologies (Hadoop / Hive) to data storage and pipelining (Redis, mongodb, MYSQL) at the terabyte scale. At Graphika, Vladimir has co-designed and implemented systems that process tens of millions every six hours to deliver timely information on influencers and conversation leaders in online communities tailored to client interests. Vladimir is proficient in over a dozen programming languages and frameworks and has designed production-ready systems for every stage of big data analysis, from collection to client-facing presentation via web, spreadsheet or graphic visualization.

        Vladimir has been active in the Social Media Research Foundation (SMRF) and the NodeXL project, helping build a network analysis package that brings relational data analysis at scale to the fingertips of any interested user, without requiring specialized knowledge or technical training beyond familiarity with Microsoft Excel. NodeXL has enabled users in academia, industry and the general public to analyze tens of thousands of social networks, from networks of politicians voting on bills to networks of motorcycle enthusiasts working together. As part of his work with SMRF and the NodeXL team, Vladimir has contributed a chapter on Twitter analysis to Analyzing Social Media Networks with NodeXL: Insights from a Connected World.

        Vladimir's work has received awards at the International Conference for Weblogs in Social Media and Bits on Our Minds. He has presented his research at academic and industrial campuses all over North America and Europe, including: Xerox/PARC, Microsoft, Colgate University, Northeastern University, UMCP and Oxford University (Oxford Internet Institute). He currently resides in Somerville, MA.


        Robert Blanchard
        Robert Blanchard

        SAS Senior Data Scientist.

        Robert is a Senior Data Scientist at SAS where he builds end-to-end artificial intelligence applications.  He also researches, consults, and teaches machine learning with an emphasis on deep learning and computer vision for SAS. Robert has authored a book on computer vision and has developed several professional courses on topics including neural networks, deep learning, and optimization modeling. Before joining SAS, Robert worked under the Senior Vice Provost at North Carolina State University, where he built models pertaining to student success, faculty development, and resource management. Robert also started a private analytics company while working at North Carolina State University that focused on predicting future home sales. Prior to working in academia, Robert was a member of the research and development group on the Workforce Optimization team at Travelers Insurance. His models at Travelers focused on forecasting and optimizing resources. Robert graduated with a master’s degree in Business Analytics and Project Management from the University of Connecticut and a master’s degree in Applied and Resource Economics from East Carolina University.

        Robert Blanchard is speaking in the following session:

        Clinton Brownley
        Clinton Brownley

        Data Scientist

        Clinton Brownley, Ph.D., is a data scientist at WhatsApp, where he’s responsible for a variety of analytics projects designed to improve messaging and VoIP calling performance and reliability.  Before WhatsApp, Clinton was a data scientist at Facebook, working on large-scale infrastructure analytics projects to inform hardware acquisition, maintenance, and data center operations decisions.  As an avid student and teacher of modern analytics techniques, Clinton is the author of two books, “Foundations for Analytics with Python” and “Multi-objective Decision Analysis,” and also teaches Python programming and data science courses at Facebook and in the Bay Area. Clinton is a past-president of the San Francisco Bay Area Chapter of the American Statistical Association and is a council member for the Section on Practice of the Institute for Operations Research and the Management Sciences. Clinton received degrees from Carnegie Mellon University and American University.

        Clinton Brownley is instructor of the following workshop:

        Sergei Burkov
        Sergei Burkov

        CEO and Founder

        Sergei Burkov is the founder and CEO of Alterra.ai, a Deep Learning / NLP startup. He previously co-founded and led three Silicon Valley startups, of which one, Dulance, was acquired by Google back in 2006, where he became the first head of its Moscow R&D Center. He holds PhD in Theoretical Physics and worked at Cornell University.

        James Casaletto
        James Casaletto

        PhD Candidate

        UC Santa Cruz Genomics Institute and former Senior Solutions Architect, MapR

        James Casaletto is studying bioinformatics and biomedical engineering at UC Santa Cruz.  Previously, he worked at MapR Technologies where he designed, implemented, and deployed complete solution frameworks for big data. He has written and delivered courses on MapReduce programming, data engineering, and data science on Hadoop to thousands of students around the world.

        James Casaletto is instructor of the following workshop:

        Nicola Corradi
        Nicola Corradi

        Research Scientist

        Nicola is a Research Scientist at Datavisor, the world’s leading AI-powered Fraud and Risk Platform for enterprises, where he develops deep learning models to fight fraud and online abuse. He uses self-supervised learning, attention, and other state-of-art algorithms to detect content abuse and other malicious activities and protect the experience of other users on the platform.Nicola gained his Ph.D. at the University of Padova in Cognitive Science before moving to Cornell University for a postdoc, where he explored the integration of computational models of neurons within neural networks.

        Pranjal Daga
        Pranjal Daga

        Machine Learning Scientist

        Pranjal helped set up Cisco Innovation Labs after dropping out of his PhD and handles Machine Learning/Product there. He also serves as an Entrepreneur-in-Residence at Vonzos Partners. Previously he conducted ML research at Adobe Research, IBM Research, University of Alberta, Purdue University and Northwestern University. He attended Stanford GSB in the Ignite program and is an On Deck Fellow.

        Pranjal Daga is speaking in the following session:

        John Elder Ph.D.
        John Elder Ph.D.

        Founder & Chair

        John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, Washington DC, and London. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia.

        Alireza Fathi
        Alireza Fathi

        Senior Research Scientist

        Luba Gloukhova
        Luba Gloukhova

        Consultant & Speaker

        Luba Gloukhova leads and executes advanced machine learning projects for high tech firms and major research universities in Silicon Valley. She also preaches what she practices, serving as the founding chair of Deep Learning World – the premier conference covering the commercial deployment of deep learning – and delivering highly-rated talks at many other events as well. Luba previously supported Stanford faculty as an internal consultant at the university's Graduate School of Business, conceiving and generating innovative solutions to accelerate research.

        Before that, Luba gained industry experience in high frequency trading analysis, catastrophe risk modeling, and marketing analytics. She received her master’s in analytics from the University of San Francisco and two bachelors degrees from Berkeley: applied mathematics and economics. Luba also teaches yoga and enjoys an active lifestyle.

        Nicolas Hohn
        Nicolas Hohn

        Chief Data Scientist, Australia

        Nicolas is a Senior Analytics Expert at McKinsey & Company in Melbourne and the Chief Data Scientist for QuantumBlack Australia. He leads data science teams to extract actionable insights from data in a pragmatic and responsible way across a range of fields, including telecommunications, IoT and financial services. Having more than 15 years of post-PhD experience in research, development and commercialisation of product innovation in big data analytics and predictive modelling, his areas of expertise include: data science, machine learning, analytics transformation programs, DevOps for analytics and ethics in AI. Prior to joining McKinsey, Nicolas led data science at Dun & Bradstreet and analytics at a Big Data start-up in the US. 

        Nicolas Hohn is speaking in the following session:

        Nathan Kirchner
        Nathan Kirchner

        Founder, CTO

        Dr Nathan Kirchner's accomplishments resulted in him being named as one of Australia’s Most Innovative Engineers by Australia’s peak engineering body Engineers Australia & as one of Australia's and the US' Top Ten Young Scientists by Popular Science magazine, along with seeing him receive a number of other international awards and recognitions. He is the Founder | CTO at Presien - a cutting edge AI vision systems, a Special Advisor for Robotics | Ventures at one of the worlds largest private construction companies, a Director of the Robotics Australia Group peak body & sits on the Advisory Board of Queensland Robotics. He is an active academic researcher in robotics as an Honorary Professor at the Ohio State University. Previously to this he served multiple academic appointments at Stanford University and the University of Technology Sydney. 

        Dr Kirchner's speciality is uncovering and imagining opportunities for emergent robotics & future technologies in the real world and forging viable R&D to Deployment (R&D2D) pathways to their realisation. One of his multi-award winning portfolio projects - Blindsight by Presien (formerly Toolbox Spotter) AI computer vision for heavy industries - has recently evolved into a $7m VC funded spinoff at which he is the Founder | CTO. He has over 15+ years in industry, and 10+ years in academia, initiating, shaping, driving and leading cutting-edge, research driven disruptive innovation.

        Ian Knopke
        Ian Knopke

        Senior Data Scientist

        Ian Knopke recieved his Ph.D. in Computer Science from McGill University, specializing in music search systems. He also worked as a researcher at academic institutions in the US and the UK before joining the BBC as their first data scientist, to work on applied R&D projects for TV, Radio, Sport, News, and the World Service Group. He later worked on data science problems for the Financial Times, Springer Nature, and Elsevier, as well as a couple of AI startups specializing in NLP. Ian joined Thomson Reuters as a Senior Data Scientist in the Reuters Applied Innovation group in 2020 and has also taken on an additional role as a new father in March.

        Carter Lin
        Carter Lin

        Data Science Manager

        Carter Lin is a Data Science manager at Stripe with a Stanford Ph.D. degree. He manages a team of data scientists to minimize risk and abuse while preserving good user experience and optimizing operations. His team is solving challenging problems in the areas of fraud, credit risk, identity, compliance, account security, operation forecast and optimization with analytics and machine learning.

        Carter Lin is speaking in the following session:

        Patrick Miller
        Patrick Miller

        Lead of Enterprise AI

        Patrick Miller is the NYC lead of Google's Enterprise AI team. His team builds scalable, cutting-edge machine learning solutions to internal Google problems. Before Google, Patrick led machine learning at Macmillan, a major trade publisher. He's a core contributor to Cognoma, a cancer genomics ML research tool. Patrick has a Master's in Computer Science from the Georgia Institute of Technology.

        Patrick Miller is speaking in the following session:

        Robert Muenchen
        Robert Muenchen

        Manager of Research Computing Support

        Robert A. Muenchen () is the author of R for SAS and SPSS Users, and co-author of R for Stata Users and An Introduction to Biomedical Data Science. He is also the creator ofr4stats.com, a popular web site devoted to analyzing trends in data science software, reviewing such software, and helping people learn the R language.

        Bob is an ASA Accredited Professional Statistician™ who focuses on helping organizations migrate from SAS, SPSS, and Stata to the R Language. He has taught workshops on data science topics for more than 500 organizations and has presented workshops in partnership with the American Statistical Association, RStudio, DataCamp.com, and Revolution Analytics. Bob has written or co-authored over 70 articles published in scientific journals and conference proceedings and has provided guidance on more than 1,000 graduate theses and dissertations at the University of Tennessee.

        Bob has served on the advisory boards of SAS Institute, SPSS Inc., BlueSky Statistics, and the Statistical Graphics Corporation. His contributions have been incorporated into SAS, SPSS, JMP, jamovi, BlueSky Statistics, STATGRAPHICS, and numerous R packages. His research interests include data science software, graphics and visualization, machine learning, and text analytics.

        Robert Muenchen is instructor of the following workshop:

        Suhas Pillai
        Suhas Pillai

        Deep Learning Engineer

        Suhas Pillai is a Deep Learning Engineer at Center for Deep Learning in Electronics Manufacturing (CDLe). At CDLe, his work focuses primarily on applying deep learning in semi conductor manufacturing, where there is data scarcity. His work at the Center has demonstrated that using synthetic data can leverage the potential of applying deep learning in areas where there is a dearth of data. In the past, he has worked in applying deep learning in Speech recognition, NLP and Computer Vision domains. He was associated with couple of startups, where he was responsible for developing Deep learning algorithms for detecting objects in satellite imagery and creating cognitive search engines. He holds a Masters in Computer Science from Rochester Institute of Technology.

        Felix Reinhart
        Felix Reinhart

        Data Scientist

        Dr. Felix Reinhart studied computer science at Bielefeld University. In 2011, he received a Ph.D. at the Research Institute for Cognition and Robotics (CoR-Lab). Felix was visiting researcher at NASA JPL and Birmingham University. At the Fraunhofer Institute for Mechatronic Systems Design, Felix was Senior Expert for Industrial Data Science. Since 2018, Felix Reinhart is Data Scientist at Miele.

        Gowdhaman Sadhasivam
        Gowdhaman Sadhasivam

        Senior Computer Vision Scientist

        Gowdhaman Sadhasivam is a Senior Computer Vision Scientist at Orbital Insight, Inc. His current work is focused on designing and implementing highly scalable Computer Vision algorithms to understand satellite and aerial imagery. Prior to his current role, he worked as a Senior Data Scientist where he solved Computer Vision and Machine Learning problems and built enterprise products. He also worked as a Software Engineer where he developed and optimized computationally expensive applications. Gowdham received his Master of Science degree in Computer Science from University of Illinois at Chicago, and Bachelor of Engineering in Computer Science and Engineering from Anna University, India.

        Gowdhaman Sadhasivam is speaking in the following session:

        Aashish Sheshadri
        Aashish Sheshadri

        Staff Machine Learning Engineer

        Aashish Sheshadri has a master's degree in Computer Science from the University of Texas at Austin. He is currently part of strategic machine learning enablement at PayPal. His interests lie in machine learning enablement and research.

        Aashish Sheshadri is speaking in the following session:

        Marc Smith
        Marc Smith

        Chief Social Scientist

        Dr. Marc A. Smith is a sociologist specializing in the social organization of online communities and computer mediated interaction. Smith leads the Connected Action consulting group. Smith co-founded the Social Media Research Foundation (http://www.smrfoundation.org/), a non-profit devoted to open tools, data, and scholarship related to social media research. He contributes to the open and free NodeXL project (http://nodexl.codeplex.com) that adds social network analysis features to the familiar Excel spreadsheet. NodeXL enables social network analysis of email, Twitter, Flickr, WWW, Facebook and other network data sets. Along with Derek Hansen and Ben Shneiderman, he is the co-author and editor of Analyzing Social Media Networks with NodeXL: Insights from a connected world, from Morgan-Kaufmann which is a guide to mapping connections created through computer-mediated interactions. Smith has published research on social media extensively, providing a map to the landscape of connected communities on the Internet.

        Nathan Susanj
        Nathan Susanj

        Applied Science Manager

        Previously Nathan was a data scientist on the Wells Fargo Enterprise Analytics and Data Science team where he led a small team as head of Natural Language Processing (NLP) and Speech Capabilities Development, and was focused on building out Wells Fargo's capabilities in areas related to NLP, deep learning and data science product design. Nathan holds a Masters in Predictive Analytics from Northwestern University and is working on his second Masters in Computer Science from Georgia Tech. He has been with Wells Fargo for the past five years and worked in marketing analytics prior to his current role.

        Nathan Susanj is speaking in the following session:

        James Taylor
        James Taylor

        CEO

        James Taylor is the CEO of Decision Management Solutions and is a leading expert in how to use business rules and analytic technology to build decision management systems. He is passionate about using decision management systems to help companies improve decision-making and develop an agile, analytic and adaptive business. He provides strategic consulting to companies of all sizes, working with clients in all sectors to adopt decision-making technology. James is an expert member of the International Institute for Analytics and is the author of multiple books and articles on decision management, decision modeling, predictive analytics and business rules, and writes a regular blog at JT on EDM. James also delivers webinars, workshops and training. He is a regular keynote speaker at conferences around the world.

        Yizhar Toren
        Yizhar Toren

        Senior Data Scientist

        Yizhar has more than 15 years of experience working as a data scientist (from the time it was still called "statistics"). He worked in many industries and across disciplines: from clinical trials for biotech, behavioural analysis for gaming, fintech consultancy to large scale NLP/image based recommendation systems. Yizhar worked with big data, small data and everything in between. Bayesian by belief, but a big believer in GSD.

        Giovanni Turra
        Giovanni Turra

        Computer Vision, Machine Learning and Deep Learning Engineer

        Giovanni Turra has been working since 2013 developing Computer Vision, Machine Learning and Deep Learning software solutions in the emerging field of Digital Microbiology Imaging and Data Analysis.

        He is part of the imaging team in Copan working both on dozens of already installed automations and on new R&D tools and solutions.

        He has a PhD in Technology for Health (from University of Brescia) focusing its research on the application of machine learning and deep learning solutions for analysis of Chromogenic and nonselective media.

        Giovanni Turra is speaking in the following session:

        Hadrien Van Lierde
        Hadrien Van Lierde

        Machine Learning Engineer

        Hadrien Van Lierde is a Machine Learning Engineer with WeBank, China’s leading digital bank backed by Tencent. He received his B.Sc. and M.Sc. in Mathematical Engineering from UCLouvain (Belgium), and Ph.D. from the City University of Hong Kong (Hong Kong, China) with research topics ranging from Complex Networks to Social Media Analysis and Natural Language Processing. Now based in Shenzhen, he joined WeBank to contribute to the company’s core mission of providing underbanked individuals and SMEs with high-quality banking services. WeBank’s AI lab is dedicated to the automation of the banking services delivered to its fast-growing base of 200 million customers. In that context, Hadrien’s current work focuses primarily on the development of a multilingual AI-empowered Customer Service System, thereby contributing to the design of cutting-edge Deep Learning models for various NLP tasks. Hadrien’s core areas of interest also include literature, learning foreign languages and traveling the world.

        Vaibhav Verdhan
        Vaibhav Verdhan

        Principal Data Scientist

        Vaibhav Verdhan is a seasoned data science professional with rich experience spanning across geographies and domains. He is a published author with books on machine learning and deep learning. He is a hands-on technical expert and has led multiple engagements in Machine Learning and Artificial Intelligence. He is a leading industry expert, is a regular speaker at conferences and meet-ups and mentors students and professionals. Currently he resides in Ireland and is working as a Principal Data Scientist at Johnson and Johnson.

        Vaibhav Verdhan is speaking in the following session:

        Han Wang
        Han Wang

        Staff Engineer

        Han Wang is the tech lead of Lyft Machine Learning Platform, focusing on distributed computing and training. Before joining Lyft, he worked at Microsoft, Hudson River Trading, Amazon and Quantlab. Han is the creator of the Fugue project, aiming at democratizing distributed computing and machine learning.

        Alexander Wu
        Alexander Wu

        Senior Deep Learning Engineer

        Alex Wu is a senior engineer at Nauto where he works on optimizing the vision models that power core safety features like Forward Collision Warning. Before that, he worked on object depth estimation at Deepscale, a self-driving startup that was later acquired by Tesla. Alex completed his computer science degree at UCLA, where he spent a lot of his time at the Ahmanson-Lovelace Brain Mapping Center applying deep learning to 2D and 3D brain segmentation. He is passionate about technologies that improve people's lives, and spends his free time camping and listening to podcasts.

        Alexander Wu is speaking in the following session:

        Jintao Zhang
        Jintao Zhang

        Software Engineer, Machine Learning

        Dr. Jintao Zhang achieved his PhD. in machine learning in 2012. Since then he has been working in various companies as data science, machine learning, and engineering roles, with extensive experience on developing distributed machine learning platforms and providing end-to-end machine learning solutions.