Machine Learning Week Speakers

June 19-24, 2022 l Caesars Palace, Las Vegas

PAW Business

Dean Abbott
Dean Abbott

Co-Founder and Chief Data Scientist

Dean Abbott is cofounder and chief data scientist at SmarterHQ, a Wunderkind Company. Mr. Abbott is an internationally recognized expert and innovator in data science and predictive analytics, with more than three decades of experience solving problems in customer analytics, fraud detection, risk modeling, text mining, survey analysis, and many more. He is frequently included in lists of top pioneering and influential data scientists.

Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014, 2nd edition forthcoming) and coauthor of The IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a popular keynote speaker and workshop instructor at conferences worldwide and serves on advisory boards for the UC/Irvine Predictive Analytics and UCSD Data Science Certificate programs.

He holds a Bachelor's Degree in Computational Mathematics from Rensselaer Polytechnic Institute and a Master of Applied Mathematics from the University of Virginia.


Rohit Agarwal
Rohit Agarwal

Chief Data Officer

Rohit works as Senior Data Scientist in Mobisy Technologies Pvt Ltd, Bangalore, India where he leads a team of Data Scientists & Software Engineers, focusing on salesforce automation by applying state of the art ML & Deep Learning techniques. He has 12 years of industry experience with 11 years in GE where he worked on conceptualising, designing, prototyping a number of software & data solutions using cutting edge technologies for solving large industrial problems. As a hobby project, Rohit launched a website which aims at finding bus routes in Bangalore and is currently in top google search results. He has a Master's degree in IT from IIIT, Bangalore and a Bachelor’s degree in Computer Science from IET, Lucknow, India.

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.


Jodi Blomberg
Jodi Blomberg

Senior Director, Data Science and Machine Learning

Jodi Blomberg leads the enterprise data science and machine learning teams that integrate models into applications across Waste Management. Former head of data science at Charles Schwab.  Experienced data science executive with wide track record in creating products that embed NLP, computer vision, machine learning, statistical modeling, and optimization to create demonstrable value.

Jodi Blomberg is speaking in the following session:

Larry Braman
Larry Braman

Director of Career Services, Master of Science in Business Analytics

Larry Braman built and currently leads Career Services for UCLA Anderson's Master of Science in Business Analytics program, ranked #2 in the world by QS for the past three years.  With the support of the hundreds of corporate relationships he has developed as well as the Career Curriculum and individual coaching he delivers, his students consistently achieve 100% internship and full-time placement rates in data science and analytics roles across multiple industries and environments, from start-up to Fortune 100.  He welcomes your outreach at .

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.

Peter Bruce
Peter Bruce

Chief Learning Officer

Peter Bruce founded the Institute for Statistics Education at Statistics.com, now part of Elder Research, in 2002. The Institute specializes in introductory and graduate level online education in statistics, optimization, risk modeling, and predictive modeling.

Peter is a leading author in the field of data science.  He co-authored of Responsible Data Science (Wiley, 2021), cited by Bookauthority.com as one of the best new data science books of 2021.  He is also a co-author of the Wiley best-selling Machine Learning for Business Analytics, (Wiley, 2006 & 2021), used in over 600 universities around the world. Peter co-authored Practical Statistics for Data Scientists (Reilly, 2nd ed. 2020), which ranks #3 in Amazons list of best-selling books in Mathematical Analysis. He is also the author of Introductory Statistics and Analytics, a Resampling Perspective (Wiley 2015). In addition to English, Peters books have appeared in German, Chinese, Japanese, Korean and Polish. Peter has degrees from Princeton, Harvard and the University of Maryland. Prior to his work in statistics, Peter worked in the US Diplomatic Corps as a Foreign Service Officer.

Peter Bruce is speaking in the following session:

Valerie Carey
Valerie 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.

Anna Casey
Anna Casey

Data Scientist

Anna Casey is a Data Scientist with Cape Fear Collective, a non-profit organization based out of Wilmington, North Carolina working toward systemic change by leveraging local assets, illuminating actionable insights, and catalyzing innovative programming. Before joining CFC, Dr. Casey received her Ph.D. in Behavior, Cognition & Neuroscience from American University and completed a post-doctoral fellowship at Duke University. She is a published academic and researcher, a passionate advocate for evidence-based policy and programming, and a wood elf Artificer in her monthly DnD game.

Chanchal Chatterjee
Chanchal Chatterjee

AI Leader

Chanchal Chatterjee, Ph.D, held leadership roles in machine learning. He is currently leading Machine Learning and Artificial Intelligence at Google Cloud Platform. Chanchal received several awards including Outstanding paper award from IEEE Neural Network Council for adaptive learning algorithms recommended by MIT professor Marvin Minsky. Chanchal founded two tech startups between 2008-2013. Chanchal has 29 granted or pending patents, and over 30 publications. Chanchal received M.S. and Ph.D. degrees in Electrical and Computer Engineering from Purdue University.

Chanchal Chatterjee is speaking in the following session:

Tom Chi
Tom Chi

Former cofounder of Google X & Founder

Tom Chi has worked in roles ranging from astrophysical researcher to Fortune 500 consultant to corporate executive leading hardware/software team to develop innovative products & services. He pioneered and practices a unique approach to rapid prototyping and leadership that can jumpstart innovative new ideas and move large organizations at unprecedented speeds. He was head of Product Experience and a founding member of Google X, and currently works to accelerate a future where humanity becomes a net positive to nature as Managing Partner of At One Ventures.

Vidhi Chugh
Vidhi Chugh

Staff Data Scientist

She works as a Staff Data Scientist with Walmart and was previously at Blue Yonder. She designs AI/ML powered solutions which help the organizations make efficient and smarter business decisions.

She is an active contributor of AI/ML articles on key platforms and aims to break down the complex Data Science jargons into an easy to understand language.

Vidhi Chugh is speaking in the following session:

Matt Denesuk
Matt Denesuk

SVP, Data Analytics & Artificial Intelligence

Tulsee Dolshi
Tulsee Dolshi

Head of Product, Responsible AI & ML Fairness (and Forbes’ 30 under 30)

Tulsee Doshi is the Head of Product for Google’s Responsible AI & Human Centered Technology organization. In this role, she leads the development of Google-wide improvements, resources, and best practices for developing more inclusive & ethical products. Tulsee has been recognized as one of Forbes’ 30 under 30 leaders and one of the top women in AI Ethics. She also serves as an AI Ethics advisor to growing Insurtech, Lemonade. She holds a BS in Symbolic Systems and an MS in Computer Science from Stanford University.

Tulsee Dolshi is speaking in the following session:

Jim Duarte
Jim Duarte

Principle, IMAGILYTICS and Academician

Jim is co-author on 9 domestic and international patents for advanced analytics in Oil & Gas, and Utilities.  He is honored as an Academician of the International Academy for Quality, a Fellow of the American Society for Quality with recognition for his work in big data, advanced analytics and data science.  He Jim has been invited as a keynote speaker for the China International Industries Fair in Shanghai for the past 5 years. Jim shared keynotes with the China Ministry of Economics and CEO's of major corporations in China.  He is sought out by both domestic and international societies as a speaker by the Shanghai Academy for Total Quality, China Quality Society, American Quality Institute, and American Society for Quality. Universities in Taiwan, Portugal and Qatar hosted Jim as a management and engineering lecturer as well as performing independent training in China.  Jim worked as a corporate director for two Fortune 100 companies. His past positions include Director, Strategic Business Analytics for Anheuser-Busch, Senior Data Scientist for SAS Institute, and Technology Director, Corporate Quality Assurance for Reynolds Metals. During his tenure as Technology Director in Quality at Reynolds Metals he developed the non-destructive statistical testing methodology for the Space Shuttle's heat treated aluminum plate in conjunction with NASA. He is published internationally. His most recent publications are on Disruptive Analytics and Data Science. He chaired the committee on statistical procedures for the Aluminum Association and served on the GMP SPC Committee for the Pharmaceutical Manufacturers Association.

Jim Duarte 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.

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

Usama Fayyad Ph.D.
Usama Fayyad Ph.D.

Executive Director, Chairman

Usama Fayyad is the Executive Director of the Institute for Experiential AI and Chairman of Open Insights, a technology and consulting firm he founded in 2008. His previous roles include co-Founder & CTO at OODA Health, Inc., Global Chief Data Officer at Barclays Bank. Fayyad was also the first person to hold the Chief Data Officer title when Yahoo acquired his second startup in 2004. There, he built the Strategic Data Solutions group and founded Yahoo Research Labs. He held leadership roles at Microsoft and founded the Machine Learning Systems group at NASA's Jet Propulsion Laboratory. He has published over 100 technical articles, edited two books, holds over 20 patents, and is an ACM and AAAI Fellow. Usama has served on the boards/advisory boards of private and public companies.


Fabio Ferraretto
Fabio Ferraretto

Kay Firth-Butterfield
Kay Firth-Butterfield

Head of AI and Machine Learning

Kay Firth-Butterfield is Head of Artificial Intelligence and a member of the Executive Committee at the World Economic Forum and is one of the foremost experts in the world on the governance of AI. She is a Barrister, former Judge and Professor, technologist and entrepreneur who has an abiding interest in how humanity can equitably benefit from new technologies, especially AI.  Kay is an Associate Barrister (Doughty Street Chambers), Master of the Inner Temple, London and serves on the Lord Chief Justice’s Advisory Panel on AI and Law. She co-founded AI Global and was the world’s first Chief AI Ethics officer in 2014 and created the AIEthics twitter hashtag.  Kay is Vice-Chair of The IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems and was part of the group which met at Asilomar to create the Asilomar AI Ethical Principles. She is on the Polaris Council for the Government Accountability Office (USA), the Advisory Board for UNESCO International Research Centre on AI and AI4All. Kay has advanced degrees in Law and International Relations and regularly speaks to international audiences addressing many aspects of the beneficial and challenging technical, economic and social changes arising from the use of AI. She has been consistently recognized as a leading woman in AI since 2018 and was featured in the New York Times as one of 10 Women Changing the Landscape of Leadership.

Kay Firth-Butterfield is speaking in the following session:

Grant Fleming
Grant Fleming

Data Scientist

Grant Fleming is a Data Scientist at Elder Research. At Elder Research, Grant works on developing, designing, and implementing analytic solutions and educational materials for private and public sector clients. His professional focus is on machine learning for social science applications, model interpretability, civic technology, and building software tools to improve reproducibility in data science.

Bala Ganesh
Bala Ganesh

Vice President, Engineering

Bala Ganesh leads the Operation Technology, Advanced Technology & Technology Support Groups at UPS. He joined UPS in 2012 as a Program Manager for UPS’s customer technology group. Thereafter he had stints in Global Retail Strategy and the Advanced Analytics & Revenue Management groups.

Prior to joining UPS, Bala was a consultant with McKinsey & Co.  He has also worked as an Aerospace Engineering researcher at the Georgia Institute of Technology.  Early in his career, Ganesh served as a pilot in the Indian Air Force. 

Bala earned a PhD in Aerospace Engineering with a minor in Math along with an MBA from the Georgia Institute of Technology. He graduated from the Indian National Defense Academy and Air Force Academy with his undergraduate degree.

Siddha Ganju
Siddha Ganju

Senior Data Scientist, Self-Driving Vehicles, Medical Instruments and Deep Learn

Siddha Ganju, who Forbes featured in their 30 under 30 list, is a Self-Driving Architect at Nvidia. Previously at Deep Vision, she developed deep learning models for resource constraint edge devices.

A graduate from Carnegie Mellon University, her prior work ranges from Visual Question Answering to Generative Adversarial Networks to gathering insights from CERN's petabyte-scale data and has been published at top-tier conferences including CVPR and NeurIPS.

Siddha authored O'Reilly's 600-page book on Practical Deep Learning for Cloud, Mobile, and Edge. With its strong reception, the book is being translated into five languages all in less than a year of publication.

Serving as an AI domain expert, she has also been guiding teams at NASA as well as featured as a jury member in several international tech competitions. She has been an invited speaker and keynote speaker at multiple conferences and was the Youth Women's Representative for India, 2013 at IET. Siddha is also a member of the Open Leadership Cohort, Mozilla Science Lab.

Bas Geerdink
Bas Geerdink

CTO

Bas is a technology leader in the AI and big data domain. His academic background is in Artificial Intelligence and Informatics. Trained as a software engineer and architect, he has 15 years experience in delivering successful data-driven projects with a wide range of companies and technologies. He occasionally teaches programming courses and is a regular speaker on conferences and informal meetings, where he brings a mixture of market context, his own vision, business cases, architecture and source code in an enthusiastic way towards his audience.


Dante Haywood
Dante Haywood

Data Scientist

Dante is a data scientist 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. In his current role, he builds a Community Data Platform and builds relationships with non-profits, unlocking new potential with data. Prior to his current role at CFC, Dante built data solutions to tackle some of the toughest problems faced by the federal government doing consulting work with Deloitte and Accenture. He lives in Wilmington, North Carolina.

Weiwei Hu
Weiwei Hu

Director, Marketing Insights and Data

Weiwei is a data science and analytics leader with extensive experience delivering actionable insights and innovative solutions that drive business and system changes through analytics and market research. Currently leading the Research Center of Excellence (COE) team at Zendesk to drive cross-functional collaboration with executives, business, technical teams to achieve effective outcomes at the speed of business. Winner of the Citrix Marketing ACE award and the Analytic 50 award for the innovative use of data and analytics to create and deliver business values.

Weiwei Hu is speaking in the following session:

Piyanka Jain
Piyanka Jain

CEO

In more than 15 years as an analytics leader, Aryng Founder Piyanka Jain is a leading expert in Data Literacy, building Data Culture, Machine Learning, Data Science and Analytics. She is an Amazon #1 bestselling author in Data Mining, paid keynoter in conferences as well as contributes to Forbes, HBR, InsideHR, TDWI, Experian, Modern Workplace, Predictive Analytics World, etc. She has developed the BADIR framework which enables 10X+ faster insights, 20X+ impact and driven $1b+ in business impact for her clients. She has two Masters degrees, with her thesis involving applied mathematics and statistics. Before founding Aryng, she was the Head of Business Analytics at PayPal-North America.


Piyanka Jain is speaking in the following session:

Adita Karkera
Adita Karkera

Data & AI Architect

Adita Karkera is a distinguished data & AI architect in Deloitte's Government & Public Services (GPS) Analytics & Cognitive practice. In her role, Adita is a senior data advisor to Chief Data Officers (CDO), providing guidance to federal and state CDOs on their data and AI strategies. She also serves as a fellow in Deloitte’s AI Institute for Government. Prior to joining Deloitte, Adita spent nearly 20 years with the Arkansas Division of Information Services (DIS) in Little Rock, Arkansas. She began her career as a database administrator and was appointed the Deputy State Chief Data Officer (CDO) in 2017.

Aric LaBarr
Aric LaBarr

Associate Professor of Analytics

An Associate Professor of Analytics 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 work force 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.


Aric LaBarr is speaking in the following session:

Jared Lander
Jared Lander

Chief Data Scientist

Jared P. Lander is Chief Data Scientist of Lander Analytics, the Organizer of the New York Open Statistical Programming Meetup and the New York and Government R Conferences, an Adjunct Professor at Columbia Business School, and a Visiting Lecturer at Princeton University. With a masters from Columbia University in statistics and a bachelors from Muhlenberg College in mathematics, he has experience in both academic research and industry. Jared oversees the long-term direction of the company and acts as Lead Data Scientist, researching the best strategy, models and algorithms for modern data needs. This is in addition to his client-facing consulting and training. He specializes in data management, multilevel models, machine learning, generalized linear models, data management, visualization and statistical computing. He is the author of R for Everyone (now in its second edition), a book about R Programming geared toward Data Scientists and Non-Statisticians alike. The book is available from Amazon, Barnes & Noble and InformIT. The material is drawn from the classes he teaches at Columbia and is incorporated into his corporate training. Very active in the data community, Jared is a frequent speaker at conferences, universities and meetups around the world.

James McCaffrey
James McCaffrey

Senior Scientist Engineer

James McCaffrey works for Microsoft Research in Redmond, Wash. James explores applied deep machine learning and artificial intelligence. He has worked on several Microsoft products including Internet Explorer and Bing. James has a PhD in cognitive psychology and computational statistics from the University of Southern California, a BA in psychology, a BA in applied mathematics, and an MS in computer science. 

James learned to speak to the public while working at Disneyland as a college student, and he can still recite the entire Jungle Cruise ride narration from memory.

Terry Miller
Terry Miller

Executive Director-Predictive Analytics (Global Services)

Terry Miller has spent nearly 10 years working with OEMs to evaluate and optimize industrial processes through increased performance of their machines. After finishing a Master’s Degree in Predictive Analytics, Terry began formally training and deploying traditional statistical models, as well as Machine Learning algorithms for asset-predictive (explanatory) maintenance and process optimization, specifically on industrial robots.

Terry Miller is speaking in the following session:

Ehsan Mousavi
Ehsan Mousavi

Machine Learning/AI

Ehsan Mousavi is speaking in the following session:

Sage Murakishi
Sage Murakishi

Senior Data Scientist

Sage Murakishi is the Senior Data Scientist at Little Caesars Enterprises where he leads and optimizes reporting, analytics, and data science projects. As a data storyteller, Sage utilizes everything from basic statistics to automated machine learning to explain what happened to what will happen. He has experience using analytics in QSR, insurance, finance, healthcare, and retail.

Sage holds a Bachelor of Arts in Political Science from Michigan State University and a Master of Science Predictive Analytics from Northwestern University.

Ali Narimany
Ali Narimany

Ali Narimany is speaking in the following session:

Brian O’Neill
Brian O’Neill

Founder

Brian T. O'Neill is a designer, advisor, and the founder of Designing for Analytics, an independent consultancy that helps software leaders turn ML and analytics into indispensable data products. For over 20 years, he has worked with companies including DellEMC, Tripadvisor, Fidelity, JP Morgan Chase, ETrade and multiple startups. Brian is also an international speaker, having given talks at premier technology conferences including Strata, the International Institute for Analytics Symposium, and Predictive Analytics World. Brian also hosts the podcast, Experiencing Data, where he reveals the strategies that product, data science and analytics leaders are using to deliver human-centered data products. Brian also authored the DFA Self-Assessment Guide, teaches a seminar called Designing Human-Centered Data Science Solutions, and publishes a weekly Insights mailing list. In 2020, Brian began advising students in MIT's Sandbox Innovation Fund and was published in O'Reilly Media's 97 Things About Ethics in Data Science Everyone Should Know.

Aleks Ontman
Aleks Ontman

Lead Data Scientist and Senior Manager

Aleks Ontman, PhD, is a Lead Data Scientist and Senior Manager at Deloitte, specializing in data science, algorithms, and advanced analytics with a focus on NLP and Graph Theory. He has over 15 years of experience in academia, industry, and government in the theory and application of most sophisticated and up-to-date machine learning and stochastic modeling to real-world problems building and leading teams ensuring rigor and adoption of best-in-class practices in data preparation, modeling, and performance measurement. Additionally, Aleks is actively engaged in firm and external activities which include algorithm development (in various programming environments, e.g., MATLAB, Java SE, C++), implementation, deployment, and optimization. Aleks has over seven years of consulting experience with strong communication and technical skills which are demonstrated by numerous client projects, firm contributions, and publications.

Aleks Ontman is speaking in the following session:

Olivia Parr-Rud
Olivia Parr-Rud

Founder and CEO

Olivia is an expert data scientist, award-winning and best-selling author, and communication coach. Her passion for data science and emotional intelligence guides her quantitative and qualitative research that unveils the relationship between human-centered corporate culture and long-term corporate profits. Olivia's success in data science led to the writing of her international best-seller, Data Mining Cookbook (Wiley 2001). Her research into the need for higher emotional intelligence to thrive in our increasingly complex economy led to her second book, Business Intelligence Success Factors, Aligning for Success in a Global Economy (Wiley/SAS, 2009). Her third book, "Business Analysis Using SAS Enterprise Miner and SAS Enterprise Guide, A Beginner's Guide," highlighted communication and won Best of Show at the Carolina Technical Book competition.

Olivia holds a BA in Mathematics, an MS in Statistics. Clients include Cisco, Clorox, Walmart, Wells Fargo, Genentech, State Farm, Nationwide, Liberty Mutual, Citizen's Bank, HP, IBM, SAS, and Xerox.

George Paslaski
George Paslaski

Director of Data Science

George Paslaski has a PhD in Mathematics from LSU and an MBA from University of Richmond. He started his career in statistics, in 1999 at Capital One where he led the Analytic Testing Lab and was instrumental in getting Capital One statisticians to be early adopters of Stochastic Gradient Boosting. He moved to Farmers Insurance in 2007 where he served as the Director of R&D and later as the Director of Growth Analytics. He became the Director of Data Science at DriveTime in January of 2021.

George Paslaski is speaking in the following session:

Rushabh Patel
Rushabh Patel

Machine Learning Engineer II

Rushabh Patel is speaking in the following session:

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.

Satish Prabhu
Satish Prabhu

Data Scientist

Satish Prabhu has been part of the Paychex family since 2018. He graduated from Clemson University with a Masters in Electrical Engineering, specializing in ML algorithms and their underlying math. Prior to Paychex, he worked as a data scientist for a start-up that developed wearable technology. He is at the core of problem-solving; someone who understands business and is very passionate about data. He has the knack to uncover insights from data and translate that into actions and business outcomes. He is a big advocate for explainable AI, so as to build trust in black box models across all the Paychex teams.


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.

Steven Ramirez is speaking in the following session:

Jennifer Redmon
Jennifer Redmon

Chief Data Evangelist

Jennifer Redmon joined Cisco in 2009 and serves as its Chief Data Evangelist. Her charter is to enable an increasingly data-driven culture through globally-scaled data platforms, services, and community enablement. Her team has trained over 6,000 employees in the areas of data science, artificial intelligence, data storytelling, data engineering, and lean six sigma. Her Data Evangelism group also hosts Data Symposiums serving Cisco's data science and AI communities of practice around the world, bi-annual Kaggle-style data science competitions, internal data science collaboration platforms, and Cisco's Data Science for Good program.

Jennifer holds an international MBA from Duke University with a concentration in Strategy and Bachelor's in Economics and Art History from UC Davis.

Jennifer Redmon is speaking in the following session:

Karl Rexer
Karl Rexer

President

Karl Rexer founded Rexer Analytics in 2002.  He and his teams provide predictive modeling and analytic consulting to clients across many industries.  Recent clients include PwC, Boston Scientific, Redbox, ADT
Security, Interamericana University, MIT, A.S.Watson, and many smaller companies.  In addition to leading client engagements and hands-on data work, Karl is a predictive analytics evangelist, frequently speaking at conferences, colleges, and other events.  He also serves on Advisory Boards for the Business Analytics programs at both Babson College and Bentley University.  Several software companies have sought Karl's input, and in 2008 and 2010 he served on SPSS's (IBM) Customer Advisory Board.  He also served 11 years on the Board of Directors of the Oracle Business Intelligence, Warehousing, & Analytics (BIWA) Special Interest Group.  Since 2007 Rexer Analytics has conducted surveys of analytic professionals,  asking them about their algorithms, tools, behaviors and views.  Summary reports from these surveys are available as a free download from the Rexer Analytics website.

Prior to founding Rexer Analytics, Karl held leadership positions at several consulting firms and two multi-national banks.  Karl holds a PhD from the University of Connecticut.

Karl Rexer is speaking in the following session:

Jennifer Schaff
Jennifer Schaff

Managing Director

Dr. Jennifer Schaff leads Elder Research's Commercial business unit where she advises organizational decision makers to help them realize maximum value from their analytics investments. In her 20 years of management, data analysis, and business experience, Dr. Schaff has built her reputation as a "Barricade Buster" in the data analytics industry. Her experience has uncovered that business barriers -- defining the right opportunity and consumer, delivering the pertinent results to guide data driven decisions, and implementing the change processes -- rather than model building, is where analytics initiatives often fail. Dr. Schaff channels this approach into a passion for guiding organizations through these business challenges to maximize their analytics ROI.

Hassan Sherwani
Hassan Sherwani

Data Scientist Architect

As a Data Scientist expert, Hassan has worked with the IT industry, startups & Academia for more than 10 years, ultimately gaining hands-on experience in machine (deep) learning for Energy, Retail, Banking, Law, Telecom, and Automotive sectors.

Hassan Sherwani is speaking in the following session:

Drew Smith
Drew Smith

Vice President of Global Data and Analytics

Drew Smith is the Vice President of Global Data and Analytics for Little Caesar Enterprises and Ilitch Holdings where he leads the vision, strategy, and execution of enterprise data and analytics across a diverse array of leading brands in QSR, transport and logistics, food processing, property development, as well as sports and entertainment, with the aim enabling data-driven decisioning.  In his most recent role prior Drew worked for the International Institute for Analytics (IIA) where he led the Analytics Leadership Consortium, working with CDOs, VPs and Directors from Fortune 500 companies across several sectors.  Before the IIA Drew held several positions at IKEA leading: the national commercial analytics functions based in the US HQ, a global divisional analytics function based in the Global Product Development HQ in Sweden, as well as the first global enterprise analytics function based at the Global Retail HQ in the Netherlands.

Drew has a Bachelor’s in History and Political Science from Boston University and an MBA from The Smeal College of Business at Penn State.

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.

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 moderator of the following session:

Tejaswi Tenneti
Tejaswi Tenneti

Senior Manager, Algorithms and Machine Learning

Tejaswi Tenneti is a Senior Manager and Tech Lead at Instacart. His team is responsible for building ML models for user intent understanding, neural text modeling and multi-objective ranking for search and recommendation use cases across multiple content types like products and recipes. He graduated with a master's degree in CS from Stanford University with a specialization in Artificial Intelligence. He has over a decade of experience in leading search and discovery efforts across multiple domains like e-commerce, points of interest in maps, job search and enterprise.

Tejaswi Tenneti is speaking in the following session:

Yentai (Vincent) Wan
Yentai (Vincent) Wan

Director, Network Planning & Optimization

Yentai Wan is the Director of Network Planning & Optimization in UPS Corporate Industrial Engineering group. His primary responsibilities are to (a) improve network planning processes, (b) generate network efficiencies and (c) support strategic initiatives across the enterprise. He joined UPS in 2007 as an Enterprise Network Planning Manager in Corporate Transportation.

Yentai was born and raised in Taipei City, Taiwan. He came to US in 2000 for advanced education and received his PhD of Industrial Engineering and Operations Research from Georgia Institute of Technology. Prior to joining UPS, Yentai served as investigator of research projects sponsored by National Science Foundation, and R&D Scientist in an industry-leading Supply Chain Software company since 2004.

Yentai (Vincent) Wan is speaking in the following session:

Ryan Withop
Ryan Withop

Director of Analytics

Director of Analytics & Data Sciences at WeVideo, the most popular online video editing tool. Former Sr. Mgr. Electronic Arts, YouSendIt and FAA Predictive Analyst. Ryan Withop is a three time top conference speaker, specializing in Purchasing Behavior Product-led/growth for subscription services.

Ryan Withop is speaking in the following session:


PAW Financial

Dean Abbott
Dean Abbott

Co-Founder and Chief Data Scientist

Dean Abbott is cofounder and chief data scientist at SmarterHQ, a Wunderkind Company. Mr. Abbott is an internationally recognized expert and innovator in data science and predictive analytics, with more than three decades of experience solving problems in customer analytics, fraud detection, risk modeling, text mining, survey analysis, and many more. He is frequently included in lists of top pioneering and influential data scientists.

Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014, 2nd edition forthcoming) and coauthor of The IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a popular keynote speaker and workshop instructor at conferences worldwide and serves on advisory boards for the UC/Irvine Predictive Analytics and UCSD Data Science Certificate programs.

He holds a Bachelor's Degree in Computational Mathematics from Rensselaer Polytechnic Institute and a Master of Applied Mathematics from the University of Virginia.


Tucker Balch
Tucker Balch

Managing Director

Tucker Balch 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.


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.

Tom Chi
Tom Chi

Former cofounder of Google X & Founder

Tom Chi has worked in roles ranging from astrophysical researcher to Fortune 500 consultant to corporate executive leading hardware/software team to develop innovative products & services. He pioneered and practices a unique approach to rapid prototyping and leadership that can jumpstart innovative new ideas and move large organizations at unprecedented speeds. He was head of Product Experience and a founding member of Google X, and currently works to accelerate a future where humanity becomes a net positive to nature as Managing Partner of At One Ventures.

Brandon Cosley
Brandon Cosley

Director of Data Science & AI

Brandon Cosley 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.

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

Siddha Ganju
Siddha Ganju

Senior Data Scientist, Self-Driving Vehicles, Medical Instruments and Deep Learn

Siddha Ganju, who Forbes featured in their 30 under 30 list, is a Self-Driving Architect at Nvidia. Previously at Deep Vision, she developed deep learning models for resource constraint edge devices.

A graduate from Carnegie Mellon University, her prior work ranges from Visual Question Answering to Generative Adversarial Networks to gathering insights from CERN's petabyte-scale data and has been published at top-tier conferences including CVPR and NeurIPS.

Siddha authored O'Reilly's 600-page book on Practical Deep Learning for Cloud, Mobile, and Edge. With its strong reception, the book is being translated into five languages all in less than a year of publication.

Serving as an AI domain expert, she has also been guiding teams at NASA as well as featured as a jury member in several international tech competitions. She has been an invited speaker and keynote speaker at multiple conferences and was the Youth Women's Representative for India, 2013 at IET. Siddha is also a member of the Open Leadership Cohort, Mozilla Science Lab.

Hussain Jiwani
Hussain Jiwani

Quantitative Analyst

Hussain Jiwani is quantitative analyst at CHS Inc. He has been with CHS since 2014. He is responsible for developing analytics and forecasting models to improve profitability and manage risk across several fronts. Hussain's demonstrated ability to extrapolate and interpret vast amounts of data adds tremendous value to CHS, its owners and customers.

His work experience is broad and deep, from fixed income and equity derivatives to futures and options. Prior to joining CHS, he spent 11 years as a senior quantitative research analyst with Waterstone Capital Management, Plymouth, Minn., where his research and risk management analysis on convertible and distressed bonds helped fuel the startup hedge funds growth from under $100 million to $1.5 billion. He also held quantitative research analyst positions with DRW Trading Group and JPMorgan Chase.

Hussain Jiwani is speaking in the following session:

Jared Lander
Jared Lander

Chief Data Scientist

Jared P. Lander is Chief Data Scientist of Lander Analytics, the Organizer of the New York Open Statistical Programming Meetup and the New York and Government R Conferences, an Adjunct Professor at Columbia Business School, and a Visiting Lecturer at Princeton University. With a masters from Columbia University in statistics and a bachelors from Muhlenberg College in mathematics, he has experience in both academic research and industry. Jared oversees the long-term direction of the company and acts as Lead Data Scientist, researching the best strategy, models and algorithms for modern data needs. This is in addition to his client-facing consulting and training. He specializes in data management, multilevel models, machine learning, generalized linear models, data management, visualization and statistical computing. He is the author of R for Everyone (now in its second edition), a book about R Programming geared toward Data Scientists and Non-Statisticians alike. The book is available from Amazon, Barnes & Noble and InformIT. The material is drawn from the classes he teaches at Columbia and is incorporated into his corporate training. Very active in the data community, Jared is a frequent speaker at conferences, universities and meetups around the world.

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

Senior Data Scientist

Carrie (Caimei) Lu is a Senior Data Scientist at Safety National Safety National Casualty Corporation. She has worked in data science domain for over 10 years. She is an expert of using data analytics and machine learning technologies to generate business insights from large amounts of industry data, and solve challenging business problems where data holds the key. At Safety National, Carrie Lu works with insurance business stakeholders to improve and optimize claim and underwriting operations by applying predictive models developed on internal and external insurance data. 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:

James McCaffrey
James McCaffrey

Senior Scientist Engineer

James McCaffrey works for Microsoft Research in Redmond, Wash. James explores applied deep machine learning and artificial intelligence. He has worked on several Microsoft products including Internet Explorer and Bing. James has a PhD in cognitive psychology and computational statistics from the University of Southern California, a BA in psychology, a BA in applied mathematics, and an MS in computer science. 

James learned to speak to the public while working at Disneyland as a college student, and he can still recite the entire Jungle Cruise ride narration from memory.

Julia Minkowski
Julia Minkowski

Product Lead

Julia is a Fraud Detection and Risk Management expert, innovator, startup advisor, mentor and a speaker. Currently she is a Product lead at Walmart Global tech focusing on mitigating fraud for Mobile payments and Marketplace. Prior to this, Julia worked with Fiserv, Signifyd, ThreatMetrix, LexisNexis Risk Solutions and helped Fortune 50 Tech and E-Commerce companies such as Microsoft, Intuit, Ebay, Chegg and others to save millions of dollars in fraud losses.

Julia holds a Bachelor’s Degree in Sociology and Geography from the Hebrew University of Jerusalem, Software Programming Certificate from John Bryce Institute, MBA from HaUniversita Ha-Ptuha of Israel, and Strategic Decision and Risk Management Diploma from Stanford University.

Julia Minkowski is speaking in the following session:

Tope Ogunmola
Tope Ogunmola

Tope is an Actuary at Safety National Casualty Corporation, where he works in Enterprise Risk Management (ERM). In addition to his ERM work, Tope has also worked on Safety Nationals IFRS Implementation team, providing actuarial support, developing illustrative models for internal documentation and reference purposes, and contributing to the teams data quality effort. In prior roles at MetLife and Assurant Employee Benefits, Tope worked in Asset-Liability Management (ALM), Deferred Acquisition Costs (DAC), and Financial Reporting. Tope is an Associate of the Society of Actuaries (ASA) and holds a M.S. degree in Applied Mathematics from the University of Missouri Columbia.

Venkat Subramanian Selvaraj
Venkat Subramanian Selvaraj

Sr. Manager, Global Data Science

Venkat heads the International Consumer Credit Data Science team for PayPal, supporting PayPal's fast-expanding credit offerings across markets in Europe and APAC through state-of-the-art machine learning models. With ~15 years of industry experience predominantly working in Financial Technology firms (viz. PayPal, D E Shaw & Altisource), Venkat comes with rich knowledge and practical experience in dealing with vast quantities of Financial data and enabling business decisions.

Apart from his full-time role at PayPal, he also serves as a Visiting Professor for Financial Data Science at XLRI (Xavier School of Management), one of India's leading business schools.

https://www.linkedin.com/in/ve...

Venkat Subramanian Selvaraj is speaking in the following session:

    Pramod Singh
    Pramod Singh

    Chief Analytics Officer, Vice-President Data Sciences and Analytics

    Pramod Singh is the chief analytics officer and vice president of data sciences and analytics at Envestnet Yodlee since May 2015. In his role, he is responsible for delivering analytics solutions for the organization and leads an 160-member team that comprises data scientists, analytics engineers and business analysts. Pramod has over 24 years of experience in leading analytics teams spanning design and implementation of analytics solutions, and creating strategies that impact the bottom line. His core competency lies in implementing decision science technologies like structured and unstructured data, machine learning and artificial intelligence. In his past role, he was the director of digital and big data analytics in HP where he joined as a data miner and progressively elevated to being part of the leadership. Pramod has a PhD and masters in mathematics from University of Arkansas and an MBA in marketing and is author of several published papers and patents and is a regular speaker at international conferences.

    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.

    Corwin Smith
    Corwin Smith

    Data Science Manager, Finance & Administration Strategic Analytics

    Corwin Smith 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:

    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.

    Priya Venkat
    Priya Venkat

    Lead Data Scientist

    Priya Venkat is speaking in the following session:

    Evan Wimpey
    Evan Wimpey

    Director of Strategic Analytics

    Evan Wimpey was a Financial Management Officer in the Marine Corps and an Operations Associate at Goldman Sachs prior to joining Elder Research as a Data Scientist. He holds master's degrees in Economics from East Carolina University and in Analytics from North Carolina State University. He is currently the Director of Strategic Analytics at Elder Research. Evan has a passion for cryptocurrency and exploring more equitable access to credit markets. Evan lives in Cary, NC with his wife and two sons.

    Evan Wimpey is speaking in the following session:


    PAW Healthcare

    Peter Bak
    Peter Bak

    CIO

    Anasse Bari Ph.D.
    Anasse Bari Ph.D.

    Clinical Assistant Professor of Computer Science

    Prof Anasse Bari holds a Ph.D. in Computer Science with a focus on Data Mining and is currently a clinical assistant professor of computer science at New York University. He was previously professor of computer science at George Washington University where he was awarded with the Computer Science Professor of the Year award in 2014 and was recognized by the Carnegie Foundation for his nomination for the United States Professor of the Year Award. He is the co-author of Predictive Analytics for Dummies.

    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.

    Kelley Counts
    Kelley Counts

    Data Scientist

    Kelley Counts is a Data Scientist at OneBlood. He leads teams that develop and deploy innovative machine learning applications to increase blood donations, anticipate hospital demand for blood products, and optimize the supply chain.  Kelley also has expertise in marketing analytics, data visualization, and the development of statistical business solutions. In addition to his work at OneBlood, Kelley supervises teams of students in Data Science graduate programs. He has also worked on committees to design Python-based Machine Learning graduate courses. Kelley is a frequent speaker on practical applications of machine learning and has published articles on analytics-driven organizational change and workforce adoption. He has served on international professional boards as an advisor on analytics, digital technology, and information systems. Kelley has a Bachelors in Biochemistry, and a MS and MBA in Business Analytics.

    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.

    Robert Grossman
    Robert Grossman

    Managing Partner

    Analytic Strategy Partners LLC

    Robert L. Grossman is the Managing Partner of Analytic Strategy Partners LLC, which he founded in 2016. From 2002-2015, he was the Founder and Managing Partner at Open Data Group, which built and deployed predictive models over big data for Fortune 500 companies.  He is also the Frederick H. Rawson Professor of Medicine, a Professor of Computer Science, and the Jim and Karen Frank Director of the Center for Translational Data Science (CTDS) at the University of Chicago.

    Danita Kiser
    Danita Kiser

    Director of Applied Research and AI/ML

    Karl Rexer
    Karl Rexer

    President

    Karl Rexer founded Rexer Analytics in 2002.  He and his teams provide predictive modeling and analytic consulting to clients across many industries.  Recent clients include PwC, Boston Scientific, Redbox, ADT
    Security, Interamericana University, MIT, A.S.Watson, and many smaller companies.  In addition to leading client engagements and hands-on data work, Karl is a predictive analytics evangelist, frequently speaking at conferences, colleges, and other events.  He also serves on Advisory Boards for the Business Analytics programs at both Babson College and Bentley University.  Several software companies have sought Karl's input, and in 2008 and 2010 he served on SPSS's (IBM) Customer Advisory Board.  He also served 11 years on the Board of Directors of the Oracle Business Intelligence, Warehousing, & Analytics (BIWA) Special Interest Group.  Since 2007 Rexer Analytics has conducted surveys of analytic professionals,  asking them about their algorithms, tools, behaviors and views.  Summary reports from these surveys are available as a free download from the Rexer Analytics website.

    Prior to founding Rexer Analytics, Karl held leadership positions at several consulting firms and two multi-national banks.  Karl holds a PhD from the University of Connecticut.

    Tom Shafer PhD
    Tom Shafer PhD

    Lead Data Scientist

    David Talby Ph.D
    David Talby Ph.D

    Chief Technology Officer

    David Talby is a chief technology officer at John Snow Labs, helping fast-growing companies apply big data and data science techniques to solve real-world problems in healthcare, life science, and related fields. David has extensive experience in building and operating web-scale data science and business platforms, as well as building world-class, Agile, distributed teams. Previously, he was with Microsoft's Bing Group, where he led business operations for Bing Shopping in the US and Europe, and worked at Amazon both in Seattle and the UK, where he built and ran distributed teams that helped scale Amazon’s financial systems. David holds a PhD in computer science and master’s degrees in both computer science and business administration.

    Zahava Uddin
    Zahava Uddin

    Managing Director

    Piotr Wygocki Ph.D.
    Piotr Wygocki Ph.D.

    CEO & Co-Founder

    Co-founder of MIM Solutions. A graduate from the University of Warsaw with a  Ph.D. in Informatics and double master's degree in Informatics and Mathematics. Research assistant at the University of Warsaw (the faculty of Computer Science and Mathematics). Experienced both in the theoretical and commercial aspects of machine learning. Founder of Warsaw C++ Users Group, active member of open source community, contributor to boost open-source library.

    Tirzah Zielinski
    Tirzah Zielinski

    VP of Marketing


    PAW Industry 4.0

    Daniel Brannock
    Daniel Brannock

    Data Scientist

    Daniel Brannock is a Senior Data Scientist at Elder Research, a boutique analytics consultancy. He has spent the last five years working for corporate and government clients, applying practical data science in every project. Much of his experience is in retail where he has built solutions for nearly every business unit—marketing, supply chain, pricing and promotions, and more. His focus is on solving client problems using the best available tool, whether it requires a deep neural network or a set of simple heuristics.

    Daniel is an experienced instructor, having provided dozens of lectures for corporate clients and presented seminars at multiple conferences.


    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.

    Arnab Chakrabarti
    Arnab Chakrabarti

    Senior Research Scientist

    Dr. Chakrabarti is a Senior Research Scientist in Hitachi's Financial Innovation Lab. in Santa Clara. He works at the intersection of data science and finance, and has been doing industrial research for over ten years . He did his MS-PhD in Electrical and Computer Engineering at Rice University, and afterwards did his Master of Financial Engineering at U C Berkeley. Dr. Chakrabarti's research publications and patents have collectively been cited over one thousand times.

    Vidhi Chugh
    Vidhi Chugh

    Staff Data Scientist

    She works as a Staff Data Scientist with Walmart and was previously at Blue Yonder. She designs AI/ML powered solutions which help the organizations make efficient and smarter business decisions.

    She is an active contributor of AI/ML articles on key platforms and aims to break down the complex Data Science jargons into an easy to understand language.

    Jim Duarte
    Jim Duarte

    Principle, IMAGILYTICS and Academician

    Jim is co-author on 9 domestic and international patents for advanced analytics in Oil & Gas, and Utilities.  He is honored as an Academician of the International Academy for Quality, a Fellow of the American Society for Quality with recognition for his work in big data, advanced analytics and data science.  He Jim has been invited as a keynote speaker for the China International Industries Fair in Shanghai for the past 5 years. Jim shared keynotes with the China Ministry of Economics and CEO's of major corporations in China.  He is sought out by both domestic and international societies as a speaker by the Shanghai Academy for Total Quality, China Quality Society, American Quality Institute, and American Society for Quality. Universities in Taiwan, Portugal and Qatar hosted Jim as a management and engineering lecturer as well as performing independent training in China.  Jim worked as a corporate director for two Fortune 100 companies. His past positions include Director, Strategic Business Analytics for Anheuser-Busch, Senior Data Scientist for SAS Institute, and Technology Director, Corporate Quality Assurance for Reynolds Metals. During his tenure as Technology Director in Quality at Reynolds Metals he developed the non-destructive statistical testing methodology for the Space Shuttle's heat treated aluminum plate in conjunction with NASA. He is published internationally. His most recent publications are on Disruptive Analytics and Data Science. He chaired the committee on statistical procedures for the Aluminum Association and served on the GMP SPC Committee for the Pharmaceutical Manufacturers Association.

    Fabio Ferraretto
    Fabio Ferraretto

    Matthew Klein
    Matthew Klein

    CEO

    Aqualaurus Group

    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.

    Wes Madrigal
    Wes Madrigal

    Machine Learning Engineer

    Wes is a data science innovator, with a career of experience working on projects that elevate data science solutions to business problems.  With a strong background in software engineering, analytics, and machine learning Wes is able to bridge the gap between computer science and data science.  Wes has built software to streamline machine learning at scale, built product integrated machine learning models that drive revenue by increasing product ROI, and answered countless questions with deep dive analysis projects.

    Terry Miller
    Terry Miller

    Executive Director-Predictive Analytics (Global Services)

    Terry Miller has spent nearly 10 years working with OEMs to evaluate and optimize industrial processes through increased performance of their machines. After finishing a Master’s Degree in Predictive Analytics, Terry began formally training and deploying traditional statistical models, as well as Machine Learning algorithms for asset-predictive (explanatory) maintenance and process optimization, specifically on industrial robots.

    Santosh Padmagirison
    Santosh Padmagirison

    Sr. Director, Commercial Finance, Forecasting and Advanced Analytics

    Oscar Porto
    Oscar Porto

    Guillermo Jenaro Rabadan
    Guillermo Jenaro Rabadan

    Project Executive

    Acubed (Airbus’ Innovation Center) - Project ADAM

    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.

    Prakash Reddy
    Prakash Reddy

    Distinguished Technologist

    Karl Rexer
    Karl Rexer

    President

    Karl Rexer founded Rexer Analytics in 2002.  He and his teams provide predictive modeling and analytic consulting to clients across many industries.  Recent clients include PwC, Boston Scientific, Redbox, ADT
    Security, Interamericana University, MIT, A.S.Watson, and many smaller companies.  In addition to leading client engagements and hands-on data work, Karl is a predictive analytics evangelist, frequently speaking at conferences, colleges, and other events.  He also serves on Advisory Boards for the Business Analytics programs at both Babson College and Bentley University.  Several software companies have sought Karl's input, and in 2008 and 2010 he served on SPSS's (IBM) Customer Advisory Board.  He also served 11 years on the Board of Directors of the Oracle Business Intelligence, Warehousing, & Analytics (BIWA) Special Interest Group.  Since 2007 Rexer Analytics has conducted surveys of analytic professionals,  asking them about their algorithms, tools, behaviors and views.  Summary reports from these surveys are available as a free download from the Rexer Analytics website.

    Prior to founding Rexer Analytics, Karl held leadership positions at several consulting firms and two multi-national banks.  Karl holds a PhD from the University of Connecticut.

    Hassan Sherwani
    Hassan Sherwani

    Data Scientist Architect

    As a Data Scientist expert, Hassan has worked with the IT industry, startups & Academia for more than 10 years, ultimately gaining hands-on experience in machine (deep) learning for Energy, Retail, Banking, Law, Telecom, and Automotive sectors.


    Deep Learning World

    Dean Abbott
    Dean Abbott

    Co-Founder and Chief Data Scientist

    Dean Abbott is cofounder and chief data scientist at SmarterHQ, a Wunderkind Company. Mr. Abbott is an internationally recognized expert and innovator in data science and predictive analytics, with more than three decades of experience solving problems in customer analytics, fraud detection, risk modeling, text mining, survey analysis, and many more. He is frequently included in lists of top pioneering and influential data scientists.

    Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014, 2nd edition forthcoming) and coauthor of The IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a popular keynote speaker and workshop instructor at conferences worldwide and serves on advisory boards for the UC/Irvine Predictive Analytics and UCSD Data Science Certificate programs.

    He holds a Bachelor's Degree in Computational Mathematics from Rensselaer Polytechnic Institute and a Master of Applied Mathematics from the University of Virginia.


    Rohit Agarwal
    Rohit Agarwal

    Chief Data Officer

    Rohit works as Senior Data Scientist in Mobisy Technologies Pvt Ltd, Bangalore, India where he leads a team of Data Scientists & Software Engineers, focusing on salesforce automation by applying state of the art ML & Deep Learning techniques. He has 12 years of industry experience with 11 years in GE where he worked on conceptualising, designing, prototyping a number of software & data solutions using cutting edge technologies for solving large industrial problems. As a hobby project, Rohit launched a website which aims at finding bus routes in Bangalore and is currently in top google search results. He has a Master's degree in IT from IIIT, Bangalore and a Bachelor’s degree in Computer Science from IET, Lucknow, India.

    Eitan Anzenberg
    Eitan Anzenberg

    Chief Data Scientist

    Eitan is the Chief Data Scientist at Bill.com and has many years of experience as a researcher. His recent focus is in machine learning, deep learning, applied statistics and software engineering. Before, he was a Postdoctoral Scholar at Lawrence Berkeley National Lab, received his PhD in Physics from Boston University and his B.S. in Astrophysics from University of California Santa Cruz. He holds 4 patents and 11 publications to date and has spoken about data at various conferences around the world.

    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.


    Daniel Brannock
    Daniel Brannock

    Data Scientist

    Daniel Brannock is a Senior Data Scientist at Elder Research, a boutique analytics consultancy. He has spent the last five years working for corporate and government clients, applying practical data science in every project. Much of his experience is in retail where he has built solutions for nearly every business unit—marketing, supply chain, pricing and promotions, and more. His focus is on solving client problems using the best available tool, whether it requires a deep neural network or a set of simple heuristics.

    Daniel is an experienced instructor, having provided dozens of lectures for corporate clients and presented seminars at multiple conferences.


    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.

    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.

    Jared Lander
    Jared Lander

    Chief Data Scientist

    Jared P. Lander is Chief Data Scientist of Lander Analytics, the Organizer of the New York Open Statistical Programming Meetup and the New York and Government R Conferences, an Adjunct Professor at Columbia Business School, and a Visiting Lecturer at Princeton University. With a masters from Columbia University in statistics and a bachelors from Muhlenberg College in mathematics, he has experience in both academic research and industry. Jared oversees the long-term direction of the company and acts as Lead Data Scientist, researching the best strategy, models and algorithms for modern data needs. This is in addition to his client-facing consulting and training. He specializes in data management, multilevel models, machine learning, generalized linear models, data management, visualization and statistical computing. He is the author of R for Everyone (now in its second edition), a book about R Programming geared toward Data Scientists and Non-Statisticians alike. The book is available from Amazon, Barnes & Noble and InformIT. The material is drawn from the classes he teaches at Columbia and is incorporated into his corporate training. Very active in the data community, Jared is a frequent speaker at conferences, universities and meetups around the world.

    James McCaffrey
    James McCaffrey

    Senior Scientist Engineer

    James McCaffrey works for Microsoft Research in Redmond, Wash. James explores applied deep machine learning and artificial intelligence. He has worked on several Microsoft products including Internet Explorer and Bing. James has a PhD in cognitive psychology and computational statistics from the University of Southern California, a BA in psychology, a BA in applied mathematics, and an MS in computer science. 

    James learned to speak to the public while working at Disneyland as a college student, and he can still recite the entire Jungle Cruise ride narration from memory.

    Taesik Na
    Taesik Na

    Senior Machine Learning Engineer

    Taesik Na is a senior machine learning engineer at Instacart where he focuses on search relevance and ranking models. Prior to Instacart, he worked on efficient ML training algorithms and optimization techniques at Microsoft. He also worked on computer aided design at Samsung. Taesik received his Ph.D. in Electrical and Computer Engineering from Georgia Tech, where his research focused on energy efficient, noise robust and secure deep learning system design.

    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.

    Kim Youngsuk
    Kim Youngsuk

    Head of Resilience Modeling and Sr. Data Science Manager

    Dr. Youngsuk Kim has been designing and developing complex predictive risk models for over 15 years. Currently, he serves as Senior Data Science Manager at One Concern, a Menlo Park-based Resilience as a Service solution provider that brings disaster science together with machine learning, for better decision-making. In his role, he leads resilience model development, data analytics, verification, and validation of the company’s models. Prior to One Concern, Dr. Kim was a Senior Principle Modeler at catastrophe modeler, RMS, and before that a Senior Research Scientist at EQECAT, now a CoreLogic company.

    Youngsuk obtained his Ph.D in Civil Engineering from the University of Illinois Urbana-Champaign, where he focused on modeling risk for complex urban infrastructure, meta-heuristic methods for non-traditional optimization problems, reliability analysis for networks, and dynamic analysis for structures.