Machine Learning Week Las Vegas Speakers

May 31-June 4, 2020 – Caesars Palace

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, Inc. in San Diego, California. Mr. Abbott is an internationally recognized data mining and predictive analytics expert with over two decades of 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 speaker of the following session:

Dean Abbott is instructor of the following workshop:

Haya Ajjan
Haya Ajjan

Associate Professor of MIS, Director of the Center for Organizational Analytics,

Haya Ajjan, associate professor of management information systems, faculty administrative fellow for Innovation and assistant to Elon University president, director of the Center for Organizational Analytics, joined Elon University in 2010.  She teaches data analytics and information systems courses in the Love School of Business’ undergraduate business, MBA and M.S. in Management programs. 

Her research focuses on better understanding the impact of technology use on individuals, groups, and organizations, and has been published in journals such as the Journal of Business Research, European Journal of Operations Research, and Journal of Marketing Theory and Practice. She also serves as project lead for Elon’s participation in Apple’s Everyone Can Code initiative. 

During her tenure at Elon, Ajjan received the Love School of Business Dean’s Awards for Service and Scholarship, founded the Center for Organizational Analytics, and served as the faculty advisor of Elon’s Sigma Iota Epsilon chapter.

Gil Arditi
Gil Arditi

Former Product Lead, Machine Learning, Lyft

Gil serves as the head of Lyft's Machine Learning Platform. Previously he was co-founder of Octarine, a security startup, and VP Product of Reflektion, an e-commerce personalization company, and AppDirect, the largest B2B app marketplace. Gil also spent a few years in product positions at Google in the Ads group, where he helped integrate YouTube and DoubleClick after their acquisition.

Gilad Barash
Gilad Barash

VP of Analytics

Gilad Barash, VP Of Analytics, has been driving innovative work on the Data Science and analytics team at Dstillery for over six years. He previously worked at a Fashion-Tech startup and held various roles at HP, including Research and Engineering at HP Labs Israel.  As a research assistant at Tufts, he worked to improve personalized healthcare. He holds a B.S. and and M.S. in Computer Science from San Diego State University.

Gilad Barash is speaker of the following session:

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.

Anasse Bari Ph.D. is speaker of the following session:

Bob Bress
Bob Bress

Vice President of Analytics & Business Intelligence

Bob Bress is Vice President of Analytics & Business Intelligence at Freewheel, a Comcast Company focused on advanced advertising technologies. In that role he leads teams of data science and analytical staff using their expertise to lead the development of the next generation of advanced targeted advertising products for television and premium video. Bob has over 15 years of analytics experience across industries including work in hospitality, energy, and at GE's Global Research Center in the Applied Statistics Lab.

Bob holds undergraduate and graduate degrees in Industrial Engineering and Operations Research & Statistics from Rensselaer Polytechnic Institute.

Bob Bress is speaker of 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 speaker of the following session:

Clinton Brownley is instructor of the following workshop:

Clayton Clouse
Clayton Clouse

Senior Data Scientist

Clayton Clouse is a Data Science Manager at FedEx where his team explores and implements artificial intelligence solutions to solve business challenges.  In his six years at FedEx Clayton has developed and implemented many advanced analytical structures, organized cross-operating company research and science collaboration groups, and spearheaded the use and expansion of artificial intelligence.

Mark Cramer
Mark Cramer

Applied AI Product Management

Mark runs Applied AI Product Management for Xerox at PARC where he works with developers and research scientists to bring Artificial Intelligence from the lab into the marketplace. He previously founded Rank Dynamics which developed AI to enhance the relevance of search results. He has an EE degree from MIT and an MBA from Harvard.

Mark Cramer is speaker of the following session:

Antonia de Medinaceli
Antonia de Medinaceli

CEO

At the forefront of AI and machine learning since the late 1990's, Antonia de Medinaceli has created and deployed predictive models for fraud detection, credit scoring, natural language processing, computer vision, and crime prediction problems, among many other applications. She has worked with both commercial and government clients to ensure that their analytics efforts are impactful to the goals of the organization. Antonia also spent time in advertising technology, heading up an R&D team of data scientists and mathematicians. She is a frequent speaker on analytics at conferences and seminars. Antonia holds degrees in Computer Science and Systems Engineering. Her woman-owned small business, Augmented, specializes in AI applications for both the public and private sectors.

Antonia de Medinaceli is speaker of the following session:

Kunal Desai
Kunal Desai

Director of Product Management

Kunal is a Product leader with more than 15 years of experience building successful, innovative and customer­-focused products.  During his career, he has delivered products that drive user and business growth. As the Director of Product Management at Walmart eCommerce, he continuously looks at analytical data to identify ways to improve user experience and engagement. He has a track record of managing high traffic consumer web sites with millions of users. Previously he has held positions at Snapfish and Oracle and is well versed in both the B2C and B2B space.

Kunal Desai is speaker of the following session:

Markus Dmytrzak
Markus Dmytrzak

Director, Advanced Analytics and Decision Sciences

As Director of Advanced Analytics and Decision Sciences at Sam's Club, Markus Dmytrzak and his team are responsible for delivering marketing measurement, targeting design, model development, automation, visualization and building simulation tools. Markus started his career at PepsiCo Germany in brand management and worked as an Analytics consultant for retailers in the United States (Costco, Meijer, Giant Eagle) and in Japan (Aeon). He got his MBA from the University Bremen in Germany and completed a Data Mining Certificate program at the University of California San Diego focusing on Predictive Analytics.

Markus Dmytrzak is speaker of the following session:

Richard Dutton
Richard Dutton

Head of Machine Learning for Corporate Engineering at Google

Rich Dutton is the Head of Machine Learning for Corporate Engineering at Google, where he leads a team of 15 engineers and data scientists across NYC and Austin. Prior to this role, Rich was a tech lead in Bigtable at Google following a 15 year career working in data and analytics across both tech and finance in the US (New York and Seattle), Europe and Asia. When not working, Rich practices Muay Thai and spends time with his family, in Williamsburg, Brooklyn, including his Mini Australian Shepherd, Radia, and his self-driving car, Trinity.

Richard Dutton is speaker of 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.

Hamza Farooq
Hamza Farooq

Principal Data Scientist

As part of the first Merchant technology data science team at Walmart Labs, Hamza has worked to help create a data-informed culture at the company. During his tenure, he led the first ever data science to make assortment, pricing and replenishment recommendation in stores, eventually owning the PnL for them. Currently, he leads multiple data science team, responsible for building machine learning & optimization algorithms to help merchants make better decision.

Hamza Farooq is speaker of the following session:

Mohamed Fawzy
Mohamed Fawzy

Senior Software Engineering Lead - AI Infra

Mohamed Fawzy is senior manager and tech lead at Facebook. In his six years at the company, he's worked on its distributed storage system and was part of the team that developed cold storage, Facebook's exabyte archiver storage system that keeps your memories safe. More recently, he started the Distributed Training Group to build large-scale distributed training infrastructure for deep learning at Facebook.

Mohamed Fawzy is speaker of the following session:

Kevin Feasel
Kevin Feasel

Engineering Manager, Predictive Analytics

Kevin Feasel is a Microsoft Data Platform MVP and Engineering Manager of the Predictive Analytics team at ChannelAdvisor, where he specializes in T-SQL and R development, fighting with Kafka, and pulling rabbits out of hats on demand. He is the lead contributor to Curated SQL (https://curatedsql.com) and author of PolyBase Revealed (forthcoming). A resident of Durham, North Carolina, he can be found cycling the trails along the triangle whenever the weather's nice enough.

Kevin Feasel is speaker of the following session:

Jason Feliciano
Jason Feliciano

Associate Director of HR Analytics

Jason is Associate Director of HR Analytics at Bristol Myers-Squibb, where he partners with HR leaders to address strategic business concerns using data and analytics, as well as designs data infrastructure in the cloud to enable firm wide HR reporting and analytics.

Jason has held similar roles in S&P Global, Tata Consultancy Services and JetBlue Airways, where he created and oversaw analytical models and business intelligence applications that helped leaders identify and monitor trends, as well as understand the importance of their people on the quality of their products and satisfaction of their customers.

Jason holds a BBA in I/O Psychology from Baruch College, an MA in Psychology from New York University, and an MS in Analytics from North Carolina State University.

Jason Feliciano is speaker of the following session:

Celeste Fralick
Celeste Fralick

Chief Data Scientist, Senior Principal Engineer

Celeste Fralick, Senior Principal Engineer and Chief Data Scientist for McAfee in the Office of the CTO, is responsible for innovating advanced analytics at McAfee.  She was recently named by Forbes on their inaugural list of "Top 50 Technical Women in America", SC Media's "Women in IT Security", and Industry Leaders  "Influential Leaders in Cybersecurity". She has applied ML, DL, and AI to 10 different markets, spanning a nearly 40-year career.  Celeste holds a Ph.D. in Biomedical Engineering from Arizona State University, concentrating in Deep Learning, Design of Experiments, and neuroscience.

Celeste Fralick is speaker of the following session:

Josh Frank
Josh Frank

Former Vice President-Gaming Data Science & Fraud Analytics

Josh Frank works at Caesars as Vice President of Gaming, Data Science, and Fraud Analytics having previously worked in the role of Director of Advanced Analytics.  Prior to Caesars he worked at Intuit as Manager of Risk Modeling and Data Sciences.  Prior to that Josh worked as a Senior Researcher for the Center for Responsible Lending (a think tank/advocacy organization), as a professor of economics, an economic forecaster for state government, co-founded a non-profit organization, and managed various functions at a top ten credit card issuer.  Josh has his Ph.D. in Economics as well as an MBA.  Josh has had numerous newspaper/television interviews from major media outlets as well as academic publications.

Josh Frank is speaker of the following session:

Michael Galtress
Michael Galtress

Director, Business Analytics & Insights

Michael is the Director of Business Analytics & Insights at AppFolio, Inc., a leading SaaS provider for vertical markets based out of Santa Barbara, CA.  At AppFolio, Michael manages the company's Analytics Data Platform and is responsible for creating Analytics culture, implementing best practices, and leading Analytics initiatives to drive business growth and improve customer experience.

Michael Galtress is speaker of the following session:

John Gao
John Gao

Senior Manager

John Gao is a leader of data science team of Work Human Research institute at Work Human. In addition, he has worked at marketing companies, such as ConstantContact, as a director of predictive modeling team, CVS, Staples, etc., and at financial companies, suych as FleetBoston, and First Marble Head as senior statistician. He has published his research in academic conferences and journals, including, "An Asymmetric Theory of Nonlocal Elasticity Part 1 & 2" (1999) IJSS,  "A New Spline Regression Method" (2002) JSM,  "A New Method of Using Polytomous independent variables with many levels for binary outcome of Big Data analysis" (2015), SAS Global Forum, and "Financial impact analysis of New RUG-IV on Post-Acute Medicare Providers Using Monte-Carlo Simulation" (2012) NESUG.

Priyanka Gariba
Priyanka Gariba

Head of Artificial Intelligence Technical Program Management

Priyanka Gariba heads Technical Program Management for the Artificial Intelligence organization at LinkedIn. Her team's mission is to lead cross-functional technical programs focused at building products powered by AI. She is an experienced professional who has worked in both enterprise and consumer space. At LinkedIn, she has led several company-wide data science and artificial intelligence initiatives, most recently playing a dual role in leading a team of stellar TPMs and leading one of the top 5 initiatives for LinkedIn Engineering organization (Productive Machine Learning Program). She is actively involved with Women in Tech community to advance women’s career in tech, particularly focused in Technical Program and Product Management discipline. She is passionate about sharing her knowledge on Technical Program Management and mentoring through external tech talks, panel and other mentoring circles.

Priyanka Gariba is speaker of the following session:

Jen Gennai
Jen Gennai

Head of Responsible Innovation, Global Affairs

Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.

Enrique Gil Ph.D.
Enrique Gil Ph.D.

Scientist

Enrique Gil, PhD is a scientist at Philips Research in the Netherlands responsible for data science activities in fields ranging from health and well-being applications to business analytics and marketing. In addition to data science, he is active in business development and value proposition creation for new Philips innovations. With 10 years of data science and analytics experience in academia and industry, his focus lies on the translation and leveraging of data science methods and technologies into real-world business value.

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.

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.

Cetin Karakus
Cetin Karakus

Global Head of Quant Technology and Analytics Core Strategies

Cetin is the Global Head of Quant Technology and Analytics Core Strategies at BP.  

Cetin Karakus is speaker of the following session:

Kristen Kehrer
Kristen Kehrer

Founder

2018 LinkedIn Top Voice - Data Science & Analytics.  Data Science instructor at UC Berkeley Ext.  Since 2010, Kristen has been delivering innovative and actionable machine learning solutions across multiple industries, including the utilities, healthcare, and eCommerce.  Currently Founder of Data Moves Me, LLC and data science consultant.  Kristen holds an MS in Applied Statistics from Worcester Polytechnic Institute and a BS in Mathematics.

Charlie Lewis
Charlie Lewis

Senior Manager, Business Intelligence

Charlie is Senior Manager, Business Intelligence at MINDBODY. He has 10 years experience in varying levels of analytics across several industries including SaaS, energy management, and climate change planning. Charlie has a BS in Earth and Planetary Sciences from the University of California and is an avid outdoorsman.

Charlie Lewis is speaker of the following session:

Shingai Manjengwa
Shingai Manjengwa

Chief Executive Officer

Shingai Manjengwa is the Chief Executive Officer of Fireside Analytics Inc., an ed-tech start-up that develops customized online and in-person professional development programs that teach digital and AI literacy, data science, data visualization and computer programming. Clients include corporates, governments, higher education institutions and high schools. Data Science courses by Fireside Analytics have over 400,000 registered learners on platforms like IBMs CognitiveClass.ai and Coursera. 

A data scientist by profession, Shingai is the Technical Education Specialist at the Vector Institute for AI in Toronto, Canada and she is also the founder of Fireside Analytics Academy, a registered private high school (BSID: 886528) that teaches high school students data science and offers the data science course curriculum to other high schools. Shingai’s children’s book, ‘The Computer and the Cancelled Music Lessons’ teaches data science to kids ages 5 to 12.

Shingai Manjengwa is speaker of the following session:

Ben Martin Ph.D.
Ben Martin Ph.D.

Chief Data Analytics Officer

Ben Martin is the Chief Data Analytics Officer at Hanesbrands Inc.  He has responsibility for advanced analytic functions globally and has spent the last decade establishing analytics as a core competency at Hanes.  He also leads the Global Planning function with global responsibility for demand planning, capacity planning, inventory planning, production planning, and material planning.

Ben received his Ph.D. from North Carolina State University and his expertise involves simulation-based optimization, process simulation, organization design & development, and critical process improvement.

Prior to joining Hanes, Ben consulted in a variety of business functions in the textile, apparel, automotive, medical device, cosmetic, semiconductor, and healthcare industries.

Ben Martin Ph.D. is speaker of the following session:

Natalia Modjeska
Natalia Modjeska

Director, Research, DnA (Data & Analytics)

Natalia Modjeska is Director, Research & Advisory, at Info-Tech Research Group. She writes, speaks and advises IT organizations around the world on topics related to AI, Machine Learning, analytics, and governance. She is currently developing an AI governance framework for Info-Tech members to ensure they build ethical, responsible and trustworthy AI. 

Reeto Mookherjee
Reeto Mookherjee

Vice President, Data, Analytics and Business Intelligence

Reeto Mookherjee serves as vice president of data science, advanced analytics and business intelligence at Fandango, a Comcast/NBCUniversal portfolio company. He has over 13 years of experience in the design, development, implementation and use of analytic decision support tools, primarily in pricing, revenue management, and predictive sales and marketing disciplines in sectors such as retail, media & entertainment, e-commerce, online travel and hospitality, wholesale trade, industrial and high tech manufacturing. He has over 8 years of experience in recruiting, developing, managing and leading distributed teams of professionals across the globe for two Fortune 100 companies and has built their award-winning data science/machine learning/pricing and analytics practices from the ground up. Reeto holds a Ph.D. in operations research from Penn State and a M.S. in systems engineering from Boston University and an INFORMS Edelman laureate (2015).

Reeto Mookherjee is speaker of 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:

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.

Venkata Pakkala
Venkata Pakkala

Staff Data Scientist

Venkata Pakkala is a Staff Data Scientist at Samsung Electronics America. In his current role, Venkata leads a team of data scientists developing cutting edge data products that primarily focuses on optimizing marketing initiatives and enhancing customer experience. Before joining Samsung, Venkata held top data analytics positions at Fortune 500 companies. Venkata holds a Ph.D. in Theoretical Chemistry from Duquesne University.

Venkata Pakkala is speaker of the following session:

Kumaran Ponnambalam
Kumaran Ponnambalam

Analytics Architect

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 speaker of the following session:

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.

Satish Prabhu is speaker of the following session:

Jennifer Lewis Priestley
Jennifer Lewis Priestley

Professor of Applied Statistics and Data Science

Dr. Jennifer Lewis Priestley, Ph.D., is a Professor of Applied Statistics and Data Science at Kennesaw State University, where she is the Director of the Center for Statistics and Analytical Services. She oversees the Ph.D. Program in Advanced Analytics and Data Science, and teaches courses in Applied Statistics at the undergraduate, Masters and Ph.D. levels. In 2012, the SAS Institute recognized Dr. Priestley as the 2012 Distinguished Statistics Professor of the Year. She served as the 2012 and 2015 Co-Chair of the National Analytics Conference. Datanami recognized Dr. Priestley as one of the top 12 "Data Scientists to Watch in 2016."

She has authored dozens of articles on Binary Classification, Risk Modeling, Sampling, Applications of Statistical Methodologies for Problem Solving as well as several textbook manuals for Excel, SAS, JMP and Minitab. Prior to receiving a Ph.D. in Statistics, Dr. Priestley worked in the Financial Services industry for 11 years. Her positions included Vice President of Business Development for VISA EU in London, where she was responsible for developing the consumer credit markets for Irish and Scottish banks. She also worked for MasterCard International as a Vice President for Business Development, where she was responsible for banking relationships in the Southeastern US. She also held positions with AT&T Universal Card and with Andersen Consulting.

Dr. Priestley received an MBA from The Pennsylvania State University, where she was president of the graduate student body, and a BS from Georgia Tech. She also received a certification from the ABA Bankcard School in Norman, OK, and a Certification in Base SAS Programming, and a Business Analyst Certification from the SAS Institute.

Jennifer Lewis Priestley is speaker of 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 speaker of the following session:

Gil Reich
Gil Reich

Data Developer

Gil Reich is a Data Developer for the Wix Data Science team. He spends his days working with Data Scientists to get them the data they need. Gil was a founding member of Answers.com, where he led the Engineering and Product Management teams. He has a B.S. in Engineering from the Cooper Union (1990) and an M.S. in Management from Ben Gurion University (1991)

Gil Reich is speaker of 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 speaker of the following session:

Allan Sammy
Allan Sammy

Director, Data Science and Audit Analytics

Allan Sammy, M.Sc., CPA, CIA is the Director, Data Science and Audit Analytics at Canada Post . He works with Internal Audit clients across the corporation to provide assurance and advisory services relating to advanced analytics and data modeling and leads the development of big data capabilities and utilization as well as the coordination of IA department analytic initiatives. He has a Master's degree in Predictive Analytics from Northwestern and over 20 years of experience in Risk Management, Investigations and Internal Audit. Prior to joining Canada Post he was Director, Fraud Risk Management at the Ontario Lottery and Gaming Corporation and the Head of Internal Audit at the Canadian Air Transport Security Authority (CATSA). He has published articles on Auditing Analytic Models (IA Magazine) and using Artificial Intelligence and Neural Network Models for Fraud Ddetection (Certified Fraud Examiners (CFE) magazine online).

Allan Sammy is speaker of the following session:

Michael Simon
Michael Simon

Chief of Analytics

Dr. Simon is serving as the chief analytics officer (CAO) in the science and technology directorate.  He is responsible for implementing the Artificial Intelligence (AI) and Machine Learning (ML) strategy, having served as its lead technical author.  He is also the chief data & analytics officer (CDAO) for a large technology organization, building the data strategy and driving integration on cutting edge analytics in network and cyber security, biometrics, and behavioral modeling.  

He previously served as the Agency’s Technical Director for Data Science and Editor of the CIA’s in-house peer-reviewed methodology journal.  Dr. Simon is an award-winning bridge-builder between technical and non-technical teams, between social, natural, and computational science fields, and between research and development (R&D) and application.  He is an advisor to investors and researchers on cyber security, predictive modeling, and AI, with successful prior work experience in banking, education, financial services, and health.

Michael Simon is speaker of the following session:

Marc Smith
Marc Smith

Chief Social Scientist

Connected Action Consulting Group

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:

Paul Speaker
Paul Speaker

Senior Data Scientist

Paul Speaker is a Senior Data Scientist with The Dow Chemical Company. He has been with Dow for 9 years. His work covers a wide array of analytics modeling work, but primarily covers predictive analytics for the needs of short-term and long-term corporate strategy. He holds B.S. degrees in Physics and Mathematics from the University of Dallas, a Masters in Astrophysics from the California Institute of Technology, and a Ph.D in Applied Mathematics from Michigan State University.

Paul Speaker is speaker of the following session:

Dan Steinberg Ph.D.
Dan Steinberg Ph.D.

Dan Steinberg, Ph.D. Harvard University (Econometrics) was the founder of Salford Systems, one of the world’s first software companies in the field of machine learning.  Working closely with Leo Breiman and Jerome Friedman since 1990 Salford introduced commercial software based on Friedman’s proprietary code for the CART decision tree, MARS regression splines, and the first gradient boosting machine (TreeNet) and Breiman and Cutler’s Random Forests.  Dan led the teams that won the KDDCup 2000 predictive modeling competition and also the 2002 Teradata/Duke Churn modeling competition and was involved in a number of other subsequent competition winning efforts. Besides software development Dan has been involved in major consulting projects for some of the world’s largest banks and has published in economics, statistics, and computer science journals.

Salford Systems was acquired by Minitab in 2017 and as of March, 2020, Dan is an independent consultant.

Dan Steinberg Ph.D. is speaker of 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.

James Taylor is speaker of the following session:

James Taylor is instructor of the following workshop:

James Taylor is moderator of the following session:

A Charles Thomas
A Charles Thomas

Chief Data & Analytics Officer

Charles is an Enterprise Data and Analytics leader who maximizes the impact Data, Insights, and Artificial Intelligence have on business results, operational efficiency & effectiveness, and fact-based cultural change.  A rare three-time Chief in the data domain, he’s led large scale data and analytics efforts for brands such as HP, USAA (where he was its first Chief Data and Analytics Officer), and Wells Fargo (its first Chief Data Officer and Head, Enterprise Data & Analytics).

He has expertise leveraging data to drive strategy across B2B and B2C segments, digital and traditional routes to market, multiple regions, and industry verticals such as energy, high-tech, pharma, retail, financial services and automotive.

Charles is committed to increasing the role of "Activist Analysts" in organizations, and driving a diversity and inclusion agenda in technology, particularly in the Data Sciences.  He formerly sat on the University of California at Berkeley’s School of Information advisory panel and currently serves as a Director at the United Negro College Fund, Inc. in Washington, DC.

He holds a PhD in Sociology (with a concentration in Organizational Behavior & studies in Quantitative Methods) from Yale University, is headquartered in Detroit, and lives in Austin with his wife and two children.  Select external communications Charles is featured in are listed below. 

A Charles Thomas is speaker of the following session:

Emma Vazirabadi
Emma Vazirabadi

Associate Director of People Insights & HR Analytics

Dr. Vazirabadi (Vazeerabaadi), received her PhD in Psychological Measurement and Quantitative Research Methods from University of Denver, in Denver, CO in 2010. She has been contributing to the workforce analytics field since 2005 and was directly responsible for her team's achievement of their first industry award in 2008 from IQPC for Best HR Metrics and Analytics. Since then, she has been key in the analytics strategy, development, and execution of number of mid-size and large organization where through her work she was responsible for significant cost savings, business process improvement and HR effectiveness measures. She has received multiple other industry awards for her work, published in peer reviewed journals and taught at colleges and universities in her field of expertise. For the past two and half years she has been working for Bristol Myers Squibb as a subject matter expert in HR Analytics, where she designs measurement techniques, analyzes data, interpret results, and provides action plans and next steps for her HR colleagues.

Emma Vazirabadi is speaker of the following session:

Karl Weinmeister
Karl Weinmeister

Developer Advocacy Manager

Karl is a Developer Advocacy Manager from Google's Developer Relations Artificial Intelligence and Machine Learning team.  Karl has worked extensively in data science and cloud computing, and was a contributor to one of the first AI-based crossword puzzle solvers that is still referenced today. He holds a BS in Computer Science and Economics from Duke University, and an MBA from the University of Texas-Austin.

Karl Weinmeister is speaker of the following session:

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

​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.

Piotr Wygocki Ph.D. is speaker of the following session:

Allen Yu
Allen Yu

Director of AI

Allen Yu is Director of AI at Lineate Labs where he leads a team of AI engineers, solution architects, and data scientists to identify and tackle the business problems for clients in ad tech and marketing using machine learning techniques. His expertise in AI product solutions spans from product recommendations for retail customers to real-time ML predictions in advertising.

PAW Financial

Gil Arditi
Gil Arditi

Former Product Lead, Machine Learning, Lyft

Gil serves as the head of Lyft's Machine Learning Platform. Previously he was co-founder of Octarine, a security startup, and VP Product of Reflektion, an e-commerce personalization company, and AppDirect, the largest B2B app marketplace. Gil also spent a few years in product positions at Google in the Ads group, where he helped integrate YouTube and DoubleClick after their acquisition.

Naveed Asem
Naveed Asem

Chief Data and Analytics Officer

Naveed Asem is the Chief Data and Analytics Officer and Senior Vice President at Donnelley Financial Solutions (DFIN), a $1.2 billion company that provides software and services to support clients with regulatory reporting, filing, and compliance functions globally.

Naveed joined DFIN in 2016 as the head of data and analytics. He now leads a growing team of data architects, engineers, and data scientists who are focused on creating business value from data through the use of modern data management technologies, analytics and machine learning. The team is not only responsible for the implementation of DFIN’s enterprise data warehouse and data lakes, but they manage everything from data ingestion and curation, to the delivery of reporting, and filing of artifacts with regulatory bodies in the U.S. and EU.

Naveed Asem is speaker of the following session:

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.

Anasse Bari Ph.D. is speaker of the following session:

Leslie Barrett
Leslie Barrett

Senior Software Engineer

Leslie Barrett is a Senior Software Engineer at Bloomberg LP's Bloomberg Law division specializing in NLP and Machine Learning applied to legal and government text. Before Bloomberg she was Director of Search Technology at The Ladders Inc, an online resource for executive jobseekers and recruiters. Previously, she was Director of Language Technology at the Financial Times where she managed groups creating new online news search products and electronic news alerts. Leslie holds Ph.D. in Computational Linguistics from New York University. She has over 20 published papers in the fields of Natural Language Processing and Information Retrieval and holds 2 patents. She serves on the Program Committees for the International Conference on Computational Linguistics and Intelligent Text Processing and the International Workshop on Big Data for Financial News.


Leslie Barrett is speaker of the following session:

Jodi Blomberg
Jodi Blomberg

Managing Director, Enterprise Analytics

Jodi Blomberg leads the team that uses data, analytics and data science to understand and measure the events and interactions that make up a client journey as it crosses the enterprise. They connect big data across lots of silos and turn it into visualizations, insights, models and data products to understand and influence client experiences. 

She is also responsible for model governance and risk management of data science models across the centralized analytics organization.  She has over 15 years of experience in data science and predictive analytics in a variety of industries including software as service fraud solutions, text classification and financial services.

Jodi Blomberg is speaker of the following session:

Richard Boire
Richard Boire

President

Boire Analytics

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.

Richard Boire is speaker of the following session:

Chakri Cherukuri
Chakri Cherukuri

Senior Quantitative Researcher

Chakri Cherukuri is a senior researcher in the Quantitative Financial Research Group at Bloomberg LP in NYC. His research interests include quantitative portfolio management, algorithmic trading strategies, and applied machine learning. He has extensive experience in scientific computing and software development. Previously, he built analytical tools for the trading desks at Goldman Sachs and Lehman Brothers. He holds an undergraduate degree in mechanical engineering from the Indian Institute of Technology (IIT) Madras, India, and an MS in computational finance from Carnegie Mellon University.

Christian Elsasser
Christian Elsasser

Senior Risk Analytics Manager - P&C Analytics

Christian Elsasser is part of Swiss Re's P&C (Property & Casualty) Analytics unit that focusses on delivering data-analytics services and solutions to insurers. In his role he is managing projects that support Swiss Re's clients with data-driven insights – both for Personal Lines and Commercial Lines – based on external as well as internal data sets and analytics methods. In addition, he is responsible for the identification of new needs and opportunities of insurers in the area of data analytics and hence to define the strategy of the P&C Analytics unit.

Before joining Swiss Re he worked for five years at CERN as a physicist where he was responsible for the analysis and interpretation of data samples collected by the Large Hadron Collider (LHC).

Christian studied physics, economics, and computer science and holds an MSc degree from the University of Zurich. For his research at CERN he was awarded a PhD in natural science. He is currently also appointed as a lecturer in scientific computing and data analytics by the University of Zurich.

Christian Elsasser is speaker of the following session:

Bas Geerdink
Bas Geerdink

CTO

Bas is a programmer, scientist, and IT manager. He works as an independent technology lead in the AI domain. His academic background is in Artificial Intelligence and Informatics. Bas has a background in software development, design and architecture with a broad technical view from C++ to Prolog to Scala. 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.

Jen Gennai
Jen Gennai

Head of Responsible Innovation, Global Affairs

Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.

Keith Higdon
Keith Higdon

President

Keith Higdon serves as President of ESIS, Inc., with overall management responsibility for this business. He is based in Chicago.

ESIS is one of the industry’s oldest and largest risk management services companies, providing claim and risk management services to a wide variety of commercial clients in the U.S. and globally. ESIS maintains a sharp focus on helping its clients manage their total cost of loss, offering comprehensive and flexible programs and innovative approaches to claims administration. ESIS is committed to achieving measurable results through consistently superior execution, and employing data analytic and predictive modelling capabilities to track progress.

Previously, Mr. Higdon served as Senior Vice President of Partnership Services for ESIS where he oversaw the management and development of client partnerships across all ESIS lines of business. In addition, he has accountability for new client implementations, ESIS University, ESIS construction practice, and ESIS global initiatives. 

Mr. Higdon has 20 years of industry experience. He began his career in consulting conducting and managing auditing, program evaluation, and program design projects for workers compensation and integrated disability management programs to large employers and service providers. He left consulting for the third-party administrator (TPA) space where he held a variety of positions under information technology and client services developing and delivering differentiated products and services to clients. With a strong focus on information delivery, his previous TPA experience culminated in the management of four departments focusing on client reporting, predictive modeling, client-facing system enhancement and support, and loss control consulting and OSHA administration. Mr. Higdon holds two Bachelor of Science degrees in the social sciences from Northern Illinois University and a master’s degree in information technology and management from Illinois Institute of Technology. He is a board member, and former Chairman, for the Center for Employee Health Studies associated with the School of Public Health at the University of Illinois at Chicago. Mr. Higdon supports industry development through participation in regional and national conferences and has published on key topics including integrated disability management, the data lifecycle, and predictive modeling over the years. He is also a volunteer mentor and guest speaker at YearUp, a community college based program for economically disadvantaged students.

Keith Higdon is speaker of the following session:

Connor Jennings Ph.D.
Connor Jennings Ph.D.

Senior Data Scientist, AI Model Development Center of Excellence

Connor is a Senior Data Scientist at Wells Fargo and led AI projects around credit card collections and fraud detection. Before Wells Fargo, he was a researcher at the National Science Foundation: Center for e-Design and worked on industrial/ manufacturing focused machine learning research projects with Boeing, John Deere, GE, and other companies. Connor holds a Ph.D. in Industrial Engineering from Pennsylvania State University. He also holds B.S. degrees in Industrial and Manufacturing Systems Engineering and Economics and a M.S. degree in Industrial Engineering from Iowa State University.

Connor Jennings Ph.D. is speaker of 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 speaker of the following session:

Sravan Kasarla
Sravan Kasarla

Chief Data Officer

Seasoned industry recognized Data Analytics leader with over 25 years of experience in Information Management, Analytics and Enterprise Architecture Leadership. As Technology Leader and Head of Data Management delivered results for Fortune 100 Insurance, Financial Services and Retail companies. Proven track record of running complex IT operations, providing innovative solutions and developing business aligned strategies. Core expertise spans running Enterprise Architecture, Information Strategy, Business Intelligence and Master Data Management. 

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.

Aric LaBarr is speaker of the following session:

Richard Lee
Richard Lee

Director of Data Science, US EOIT Advanced Analytics & AI

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.

Victor Lo
Victor Lo

AI and Data Science Center of Excellence Leader, Workplace Investing

Victor S.Y. Lo is a seasoned Big Data, Marketing, Risk, and Finance leader with over 25 years of extensive consulting and corporate experience employing data-driven solutions in a wide variety of business areas, including Customer Relationship Management, Market Research, Advertising Strategy, Risk Management, Financial Econometrics, Insurance, Product Development, Transportation, and Human Resources. He is actively engaged with causal inference and is a pioneer of Uplift/True-lift modeling, a key subfield of data science.

Victor has managed teams of quantitative analysts in multiple organizations. He currently leads the AI and Data Science Center of Excellence, Workplace Investing at Fidelity Investments. Previously he managed advanced analytics/data science teams in Personal Investing, Corporate Treasury, Managerial Finance, and Healthcare and Total Well-being at Fidelity Investments. Prior to Fidelity, he was VP and Manager of Modeling and Analysis at FleetBoston Financial (now Bank of America), and Senior Associate at Mercer Management Consulting (now Oliver Wyman).

For academic services, Victor has been a visiting research fellow and corporate executive-in-residence at Bentley University. He has also been serving on the steering committee of the Boston Chapter of the Institute for Operations Research and the Management Sciences (INFORMS) and on the editorial board for two academic journals. He is also an elected board member of the National Institute of Statistical Sciences (NISS). Victor earned a master’s degree in Operational Research and a PhD in Statistics, and was a Postdoctoral Fellow in Management Science. He has co-authored a graduate level econometrics book and published numerous articles in Data Mining, Marketing, Statistics, Analytics, and Management Science literature, and is completing a graduate level book on causal inference in business.

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 speaker of the following session:

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.

Mei Najim is speaker of the following session:

Mei Najim is moderator of the following session:

Andreas Petrides
Andreas Petrides

Quantitative Researcher

Andreas is working as a Quantitative Researcher at Goldman Sachs Quantitative Execution Services, with an emphasis in machine learning techniques for execution algorithms. Andreas has received a PhD in Information Engineering at the University of Cambridge, focusing on the interface of stochastic control theory and Bayesian machine learning, where he developed graph theoretic tools for predicting the shapes of the probability distributions to arise in the observable time-series due to the underlying non-linear stochastic interconnections. Andreas’ teaching experience included several engineering undergraduate courses, including Inference and Machine Learning, Linear Algebra, Probability, Control and Signal Processing. During his PhD, he has also worked at Informetis Europe as a Machine Learning Algorithm Engineer, developing efficient Bayesian inference techniques for smart electricity meter applications. 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 The Technology Partnership (TTP) awards, while his Master’s thesis was done in collaboration with British Cycling, developing a racing cyclist fitness predictor. 

Andreas Petrides is speaker of the following session:

Alex Sanchez
Alex Sanchez

Global Head of Risk Strategy and Analytics

Alex Sanchez is speaker of 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 speaker of the following session:

William WIlkins
William WIlkins

Chief Risk and Data Analytics Officer

William (Bill) Wilkins is a multi-purpose actuary for the Safety National Casualty Corporation(SNCC). He is a CERA, FCAS, ASA and MAAA.  While his main focus is on Enterprise Risk Management and Predictive Analytics, Bill has experience in pricing insurance, reinsurance, credit risk products, risk management, reserving and broker management.  He is currently Co-Chair of the SNCC Data Analytics Committee.  The Data Analytics Committee is a cross-functional group tasked with all aspects of data for SNCC.  The Committee works on data to be collected, how it is collected, where it is collected from, how it stored, standards and practices of usage, etc.  This includes the populating items like benchmarking reports or how best to create and use predictive analytics.  The goal is to establish a process that is repeatable and adaptable so SNCC can deliver both internally and externally.

William WIlkins is speaker of the following session:

PAW Healthcare

Halim Abbas
Halim Abbas

Vice President of Data Science

Halim is a high tech innovator who spearheaded world-class data science projects at game changing techs like eBay and Teradata. Formally educated in Machine Learning, his professional expertise span Information Retrieval, Natural Language Processing, and Big Data. Halim has a proven track record of applying state of the art data science techniques across industry verticals such as eCommerce, web & mobile services, airline, BioPharma, and the medical technology industry. He currently leads the AI department at Cognoa, a data driven behavioral healthcare startup in Palo Alto.

Halim Abbas is speaker of the following session:

Gil Arditi
Gil Arditi

Former Product Lead, Machine Learning, Lyft

Gil serves as the head of Lyft's Machine Learning Platform. Previously he was co-founder of Octarine, a security startup, and VP Product of Reflektion, an e-commerce personalization company, and AppDirect, the largest B2B app marketplace. Gil also spent a few years in product positions at Google in the Ads group, where he helped integrate YouTube and DoubleClick after their acquisition.

Yu Chen
Yu Chen

Research Advisor

Yu Chen is a Research Advisor of Outcomes and Translations Research at Eli Lilly and Company.  He applies data mining, machine learning, and systems biology approaches in translational medicine study. He has 15+ years of R&D experience in industry. Yu completed his PhD in Bioinformatics from the joint program by University of Tennessee and Oak Ridge National Laboratory and performed his post-doctoral research at Novartis Pharmaceuticals Corporation.

Daniel Chertok PhD
Daniel Chertok PhD

Sr. Data Scientist

Daniel Chertok, Ph.D., is a Sr. Data Scientist at NorthShore University HealthSystem. He is responsible for developing predictive models for population health management, operational cost containment and staffing optimization. Additionally, Daniel provides thought leadership on best analytical practices and has authored an internal standard operating procedures manual implemented by the Clinical Analytics team. His previous experience includes work in quantitative finance. Daniel holds a Ph.D. in Applied Mathematics from Simon Fraser University in Canada and an Eng. Math in Applied Mathematics from Peter the Great St. Petersburg Polytechnic 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.

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.

Jeff Deal is speaker of the following session:

Todd Dewees
Todd Dewees

Associate Professor of Biostatistics, Radiation Oncology

Dr. DeWees is an Associate Professor of Biostatistics at Mayo Clinic in Arizona and serves as the lead biostatistician for Radiation Oncology across the Mayo Clinic enterprise.  He is involved in all aspects of radiation oncology; working with departmental researchers from fields including: biologists, physicists, clinicians, residents, and students.  He is responsible for design, monitoring, analysis, interpretation, and reporting for genetic, biological, animal, human, and machine trials.  He aids in the design, implementation and publication of grants, prospective, and retrospective trials.  Dr. DeWees’ research focuses on the optimization and utilization of statistical methodology for clinical data and patient reported outcomes.

Colleen Farrelly
Colleen Farrelly

Co-Founder & Chief Scientist

Quantopo LLC

Colleen Farrelly is a co-founder and the Chief Scientist of Quantopo, LLC.  She was the lead statistician working with the Malian government on the 2014 Ebola outbreak and public health response, and her prior industry work has spanned TRICARE contracts for the US Navy, research and development at Cypher Genomics for the Genome England Competition and Celgene failed drug revival pipeline, consulting work within cardiology analytics and clinical trials, and predictive analytics work at Graham Holdings (Kaplan Higher and Professional Education), as well as educational work at Purdue University Global on their new analytics program. She is a writer for KDnuggets and is attempting her first lay audience analytics book at the moment.

Colleen Farrelly is speaker of the following session:

Jen Gennai
Jen Gennai

Head of Responsible Innovation, Global Affairs

Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.

Michael Golafshar
Michael Golafshar

Statistical Programmer Analyst

Bob Nisbet
Bob Nisbet

Instructor

Trained originally in Ecosystem Analysis & Modeling, Dr. Nisbet modeled forests at the University of California, Santa Barbara.  He moved to NCR in 1994, developing configurable data mining applications for customer Churn, Propensity-to-buy, and Customer Acquisition in Telecommunications.  He has worked also in Insurance, Banking, Credit, membership organizations (e.g. AAA), and Health Care industries. He is lead author of the award-winning Handbook of Statistical Analysis & Data Mining Applications (Academic Press, 2009, 2017), and a co-author and general editor of the award-winning "Practical Text Mining" (Academic Press, 2012) and Practical Predictive Analytics and Decisioning Systems in Medicine (Academic Press, 2015).  A new book on Effective Data Preparation is available from with Cambridge University Press.  Currently, he serves as an Instructor in the University of California at Irvine Predictive Analytics Certificate Program, teaching many online and on-campus courses each year in Effective Data Preparation and Predictive Analytics Applications.

Zeydy Ortiz
Zeydy Ortiz

CEO

DataCrunch Lab

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 speaker of the following session:

Matthew Pietrzykowski
Matthew Pietrzykowski

Principal Data Scientist

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 speaker of 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.

Vickie Rice
Vickie Rice

Vice President of Innovative Strategies

Vickie Rice is a 20-year veteran of the benefits business and an expert in healthcare claims, analytics and product management. Rice spent a decade in key administrative roles at Blue Cross and Blue Shield of Oklahoma and then served as Product Manager for Data and Analytics at Benefitfocus where she helped create innovative data tools to help both benefits administrators and consumers make fact-based decisions about their healthcare benefits.  

In her current role as VP of Innovative Strategies for CareATC, Rice has brought her passion of using data and technology to help patients live their healthiest lives to the Product Strategy team, leading them in their mission of offering world class healthcare services and solutions to our patients, providers and employer clients.

Michael Thompson
Michael Thompson

Executive Director, Enterprise Data Intelligence

Michael Thompson has over 30 years of using analytics to unleash hidden stories within data.  The quest has led him to use a variety of data warehousing, visualization, statistical, data mining methodologies, and analytic modeling creations.  The work of his teams has been shared in the Wall Street journal, industry symposiums, and publications over the years. With a personal goal to help others on their journey to find opportunities hidden in their data, Mike has led analytic teams across large financial and healthcare organizations.   

Currently, Mike leads a multi-disciplined team (physicians, nurses, statisticians, data scientists, data analysts, data engineers, and data warehouse developers) to fulfill the insatiable financial, operational, clinical, quality, and population health analytic needs of the organization as the Executive Director of Enterprise Data Intelligence at Cedars-Sinai in Los Angeles, CA.

Michael Thompson is speaker of the following session:

PAW Industry 4.0

Gil Arditi
Gil Arditi

Former Product Lead, Machine Learning, Lyft

Gil serves as the head of Lyft's Machine Learning Platform. Previously he was co-founder of Octarine, a security startup, and VP Product of Reflektion, an e-commerce personalization company, and AppDirect, the largest B2B app marketplace. Gil also spent a few years in product positions at Google in the Ads group, where he helped integrate YouTube and DoubleClick after their acquisition.

Rajagopalan Chandrasekharan
Rajagopalan Chandrasekharan

Senior Engineer

With over 34 years of experience in solving engineering problems, Raja currently works as a Senior Engineer in the Global Research arm of General Electric (GE) in Bangalore, India. He is an 'Engineering Predictive Analytics' professional with deep expertise in Artificial Intelligence, Machine Learning, Data Science, and Physics across multiple verticals including Aviation, Healthcare, Oil and Gas, Nuclear, Thermal, Steam, Renewables, and Transportation. 

In GE Global Research, he tackles cutting-edge technology problems using Machine Learning and Artificial Intelligence, to create fused text mining and numerical predictive analytics algorithms. Combining text, numerical data, video and images opens up new ways to solve practical yet complex engineering problems. This combination acts as a force-multiplier in bringing out engineering insights that are otherwise not easy to obtain. Raja specializes in monetizing these insights. Raja holds 18 patents and trade secrets in this area, and has authored several pioneering papers with over 100 citations

Rajagopalan Chandrasekharan is speaker of the following session:

Martin Elstner
Martin Elstner

Expert Chemoinformatics

Martin is trained as a chemist and focused on data analytics and scientific computing in his master program. After some years as a freelancing data scientist in various industries, Martin joined Covestro, a great place to solve problems like recycling of polymers and energy saving.

Martin Elstner is speaker of the following session:

Jen Gennai
Jen Gennai

Head of Responsible Innovation, Global Affairs

Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.

Samira Golsefid
Samira Golsefid

Principal Data Scientist

Samira Golsefid is a Principal data scientist at Paypal, she is responsible for leading merchant on boarding and risk evaluation for risk as Service. In addition to that she is managing the key customer portfolio of Paypal risk platform. Samira joined Paypal in early 2018 and brings 15 years industry experience in Machine Learning and Artificial Intelligent.

In 2007 she founded her own company with a focus on predicting customer lifetime value and international market segmentation. Prior to Paypal, she led data science projects at Flybits and Toshiba. Samira holds a PhD degree in Industrial Engineering from Amirkabir University of Technology (Tehran Polytechnic), Iran. She is an expert in unsupervised learning and uncertainty modeling and has published around 30 papers in this area.

Samira Golsefid is speaker of the following session:

Rohit Kewalramani
Rohit Kewalramani

Data Scientist

Rohit Kewalramani is a Data Scientist at KPIT Technolgies. He is currently hacking a way to use Bayesian Learning to create Automotive Learning Platform. He graduated as a Computer Engineer in 2015 and since then he has worked as Data Scientist into multiple domains such as Life Sciences, Automotive and Consulting. He has been rapidly taking POCs to Production. In a short span of career he has already filed for 2 patents and has a few publications under his name. Rohit expertises in developing large scale Deep / Machine Learning models over unstructured data such as sensors(Automotive / IIoT), Textual Data (NLP), etc.

Rohit Kewalramani is speaker of the following session:

Andrei Khurshudov
Andrei Khurshudov

Director, Advanced Analytics

Dr. Andrei Khurshudov is a Director of Advanced Analytics at Caterpillar Digital. Andrei specializes in Big Data Analytics, the Internet of Things, Cloud storage and computing, in-memory computing, and data storage reliability and technology. Andrei has spent more than 10 years at Seagate, where he was a Chief Technologist and managed various R&D organizations in such areas as data analytics, cloud technology, quality and reliability, and others. While at Seagate, Andrei created the Big Data Analytics and Insights organization, which focused on applying advanced analytics and machine learning concepts to product quality, reliability, manufacturing, and remote device monitoring, as well as finances, sales, pricing, and other critical areas where data-driven decisions are important. 

In the recent past, Dr. Khurshudov served as a Chief Data Officer at Formulus Black, a New Jersey-area startup that is developing software for in-memory computing and as a CTO and Chief Data Officer at Alchemy IoT, a Boulder-area startup creating cloud-based analytics solutions for the Internet of Things. Andrei has a Ph.D. in Engineering and, before joining Seagate, worked at such companies as IBM, Hitachi Global Storage, and Samsung. Andrei has numerous publications, patents, conference presentations, and a book.

Andrei Khurshudov is speaker of 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.

Terry Miller
Terry Miller

Global Digital Strategy and Business Development

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 speaker of the following session:

Vadim Pinskiy PhD
Vadim Pinskiy PhD

VP of R&D

Vadim Pinskiy is the VP of Research and Development at Nanotronics, where he oversees product development, short term R&D and long term development of AI platforms. Vadim completed his doctorate work in Neuroscience, focused on mouse neuroanatomy using high throughput whole slide imaging and advanced tracing techniques. Prior to that, completed Masters in Biomedical Engineering from Cornell and Bachelor's and Master’s in Electrical and Biomedical from Stevens Institute of Technology. Vadim is interested in applying advanced AI methods and systems to solving practical problems in biological and product manufacturing.

Vadim Pinskiy PhD is speaker of the following session:

Andy Ramlatchan
Andy Ramlatchan

Senior Computer Scientist

Andy Ramlatchan is a member of the Data Science team at NASA Langley Research Center where he works with researchers and engineers to develop data driven models to supplement and validate physics based models for computational materials science research. He previously worked within the Intelligence Community for the United States government in the area of cyber security. Andy is currently a PhD candidate in Computer Science at Old Dominion University, in Norfolk, Virginia where his research work focuses on matrix factorization and higher dimensional tensor completion for data recovery.

A Charles Thomas
A Charles Thomas

Chief Data & Analytics Officer

Charles is an Enterprise Data and Analytics leader who maximizes the impact Data, Insights, and Artificial Intelligence have on business results, operational efficiency & effectiveness, and fact-based cultural change.  A rare three-time Chief in the data domain, he’s led large scale data and analytics efforts for brands such as HP, USAA (where he was its first Chief Data and Analytics Officer), and Wells Fargo (its first Chief Data Officer and Head, Enterprise Data & Analytics).

He has expertise leveraging data to drive strategy across B2B and B2C segments, digital and traditional routes to market, multiple regions, and industry verticals such as energy, high-tech, pharma, retail, financial services and automotive.

Charles is committed to increasing the role of "Activist Analysts" in organizations, and driving a diversity and inclusion agenda in technology, particularly in the Data Sciences.  He formerly sat on the University of California at Berkeley’s School of Information advisory panel and currently serves as a Director at the United Negro College Fund, Inc. in Washington, DC.

He holds a PhD in Sociology (with a concentration in Organizational Behavior & studies in Quantitative Methods) from Yale University, is headquartered in Detroit, and lives in Austin with his wife and two children.  Select external communications Charles is featured in are listed below. 

A Charles Thomas is speaker of the following session:

Deep Learning World

Zulfiqar Ahmed
Zulfiqar Ahmed

Zulfiqar earned his Masters degree in Computer Science from University of Washington, with his research primarily focused on Deep Learning based solutions in the cyber security industry. He collaborated with Infoblox, an IT automation and security firm, during his graduate degree to work in the Explainable AI domain. His research project titled “Interpretation of Deep Learning based Domain Generation Algorithms classifiers” focused on visualizing the feature extraction process of trained DGA classifier models currently deployed by Infoblox to provide a detailed analysis and better interpretability of neural network models utilized as DGA classifiers. During his summer internship with REI Systems, he worked on a Computer Vision based solution to assess and evaluate the damage in areas affected by natural disasters from satellite imagery. Zulfiqar's research interests include XAI, Natural Language Processing, Recommendation Systems and Computer Vision.

Zulfiqar Ahmed is speaker of the following session:

Anthony Alford
Anthony Alford

Lead Software Engineer

Anthony is a lead software engineer at Genesys where he is working on several AI and ML projects related to customer experience. He has over 20 years experience in designing and building scalable software. Anthony holds a Ph.D. degree in Electrical Engineering with specialization in Intelligent Robotics Software and has worked on various problems in the areas of human-AI interaction and predictive analytics for SaaS business optimization.

Gil Arditi
Gil Arditi

Former Product Lead, Machine Learning, Lyft

Gil serves as the head of Lyft's Machine Learning Platform. Previously he was co-founder of Octarine, a security startup, and VP Product of Reflektion, an e-commerce personalization company, and AppDirect, the largest B2B app marketplace. Gil also spent a few years in product positions at Google in the Ads group, where he helped integrate YouTube and DoubleClick after their acquisition.

Piyush Chandra
Piyush Chandra

AI Product Management

Piyush leads AI Product Management at Nauto. In his role, he is responsible for building the next wave of AI-based features that enhance road safety. He focuses on exploring novel research ideas in the field of computer vision and vehicle safety and productizing them to make roads safer for drivers and pedestrians. 

In his previous roles, Piyush led the development of NLP platforms at Adobe and SAP. He also helps startups in the field of AI with product/market fit, strategy, and user experience.

Piyush Chandra is speaker of the following session:

Geeta Chauhan
Geeta Chauhan

AI Partnerships

Geeta Chauhan is leading AI Partnerships at Facebook with expertise in building resilient, anti-fragile, large scale distributed platforms for startups and Fortune 500s.

She is winner of Women in IT – Silicon Valley – CTO of the year 2019, an ACM Distinguished Speaker and thought leader on topics ranging from Ethics in AI, Deep Learning, Blockchain, IoT. She is passionate about promoting use of AI for Good.

Geeta Chauhan is speaker of the following session:

Justin Chien
Justin Chien

Senior Data Scientist

6sense

Justin Chien is a Senior Data Scientist at 6sense, a marketing technology startup in San Francisco. Justin went from studying biology and music at Boston College to mastering in epidemiology at UCLA where he discovered predictive modeling. Combining this new-found statistical “magic” with his passion in cutting-edge technology, Justin found machine learning and is now trying to utilize new ways to make old ways easier. His free time is spent on a never-ending quest to find delicious foods with his wife and streaming himself building mechanical keyboards.

Ilke Demir
Ilke Demir

Senior Research Scientist

Ilke Demir earned her Ph.D. in Computer Science from Purdue University, focusing on 3D vision approaches for generative models, urban reconstruction and modeling, and computational geometry for synthesis and fabrication. Afterwards, she joined Facebook as a Postdoctoral Research Scientist working with Ramesh Raskar from MIT. Her research included human behavior analysis and deep learning approaches in virtual reality, geospatial machine learning, and 3D reconstruction at scale. In addition to her publications in top-tier venues (SIGGRAPH, ICCV, CVPR), she has organized workshops, competitions, and courses in the intersection of deep learning and computer vision. She has received several awards and honors such as Jack Dangermond Award, Bilsland Dissertation Fellowship, Industry Distinguished Lecturer, and GHC Fellow, in addition to her best paper/poster/reviewer awards. Currently she is a Senior Research Scientist at DeepScale, exploring efficient temporal deep learning architectures for autonomous driving tasks.

Ilke Demir is speaker of the following session:

Jason Gauci
Jason Gauci

Engineering Manager

Jason Gauci leads the Applied Reinforcement Learning team @ Facebook AI. Jason has 13 years of experience building machine learning systems at Facebook AI, Apple, Google Research, and Lockheed Martin Applied Research, and has a PhD in computer science from UCF with a focus on Neuroevolution.

Jason Gauci is speaker of the following session:

Jen Gennai
Jen Gennai

Head of Responsible Innovation, Global Affairs

Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.

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.

Luba Gloukhova is speaker of the following session:

Vishal Hawa
Vishal Hawa

Principal Scientist

Vishal (_‘Vish’_) Hawa is Principal Data Scientist at The Vanguard Group. Vish has over 15 years of experience in Retail and Financial services industry and works closely with Marketing Managers , financial plan designers through propensity, life-time valuations and financial modeling. Vish works on creating data-products in machine intelligence space that utilize consumer attributes to generate consumer insights. Vish is thought leader and has spoken at many regional and national conferences in applied machine learning with the idea of promoting data driven decisions and harnessing actionable insights. Vish has executive management from Wharton school of business, post-graduation degrees in Information sciences, Statistics and Computer engineering from Indian Statistical Institute and Bachelors in Engineering from National Institute of Technology-India.

Vishal Hawa is speaker of the following session:

Sean Hendryx
Sean Hendryx

Machine Learning Engineer

At Standard Cognition, Sean works on research and engineering of machine learning systems that ship deep neural networks to production with reduced generalization error. He has a background in machine learning, information theory, and complex systems. Previously, he was a machine learning engineer at Explorer.ai building maps for self-driving cars and before that he worked in machine learning research as a graduate student at the University of Arizona.

Drew Hodun
Drew Hodun

Machine Learning Specialist - Google Cloud

Drew Hodun is an ML specialist on the Google Cloud professional services team, where he advises financial, autonomous, and tech customers implementing cutting-edge ML use cases and systems on Google Cloud and in hybrid environments. His work ranges from operationalizing ML to GPU/TPU perf tuning.

Navid Imani
Navid Imani

Applied Researcher

Dr. Navid Imani is an Applied Researcher with Shipping Science at eBay Corp. specializing on architecting scalable NLP solutions as well as using operations research for industrial planning and optimization. Prior to joining eBay, Dr. Imani had held multiple industry and academic research positions such as at Microsoft. He holds a Ph.D. in Computing Science from Simon Fraser University and has co-authored over 25 research publications in various areas of Machine Learning, Applied Mathematics and Distributed Computing.

Navid Imani is speaker of the following session:

Manoj Kumar Krishnan
Manoj Kumar Krishnan

Software Engineer and Tech Lead

Dr. Krishnan currently works as a software engineer and tech lead in the Facebook AI Infra team. Previously, Dr. Krishnan worked at VMware and Pacific Northwest National Laboratory in the area of High Performance Computing. Dr. Krishnan has authored and co-authored over 40 peer-reviewed conference and journal papers. Dr. Krishnan's research interests include Artificial Intelligence, Deep Learning, Recommendation Systems, Distributed Systems, Parallel Computing, High Performance Computing.

Manoj Kumar Krishnan is speaker of the following session:

Bryan Larish Ph.D.
Bryan Larish Ph.D.

Director of Technology

Bryan Larish is the Chief Security Architect for Verizon’s networks.  In that role he leads a team that plans and architects the future security capabilities of Verizon’s networks.  His team also develops artificial intelligence and machine learning capabilities that improve the performance of Verizon's networks.

Prior to joining Verizon, Bryan was Technical Director for Enterprise Connectivity & Specialized IT Services at a U.S. Government agency where he was responsible for setting the technical direction of the development and operation of the agency's global network infrastructure.  Bryan also worked in the Chief Engineer’s office at the U.S. Navy’s Space and Naval Warfare Systems Command (SPAWAR) where he implemented engineering techniques used to manage, architect, and plan the U.S. Navy’s communications/IT systems portfolio.  Bryan’s other experience includes Technical Director for Navy engineering policy and various engineering roles at SPAWAR.

Bryan holds a Ph.D. and M.S. in electrical and computer engineering from the Georgia Institute of Technology and a B.S.E. in electrical engineering from Arizona State University.

Bryan Larish Ph.D. is speaker of the following session:

Kumaresan Manickavelu
Kumaresan Manickavelu

Sr. Product Manager, NLP

Kumaresan is currently responsible for strategy and roadmap of the Core NLP and Machine Translation products at eBay. Previously he has launched and managed multiple products across eBay's internal cloud stack ranging from developer frameworks to network security.

Kumaresan Manickavelu is speaker of 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.

Patrick Miller
Patrick Miller

Software Engineering Manager

Patrick Miller is the engineering manager of Google's Enterprise Machine Learning team in New York City. 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 Congnoma, a cancer genomics ML research tool. Patrick has a Master's in Computer Science from the Georgia Institute of Technology.

Patrick Miller is speaker of the following session:

Shweta Shrivastava
Shweta Shrivastava

Chief Product Officer

Shweta is chief product officer at Nauto and oversees product and design for Nauto’s fleet, insurance, and automotive offerings. Prior to Nauto, she was the head of product management for Amazon Web Services, as well as various strategy and product management leadership roles at NetApp and Cisco, where she drove the

productizing and launch of Cisco’s IoT platform for smart cities. Shweta has an MS in CS from Penn State University and an MBA from INSEAD, France.

Shweta Shrivastava is speaker of the following session:

Mohamed Sidahmed
Mohamed Sidahmed

Machine Learning and AI Manager

Mohamed Sidahmed, Ph.D., IEEE Senior Member, is subject matter expert in machine learning & AI, data-driven modeling and optimization with both theoretical and applied skills. He is the Machine Learning and AI R&D Manager at Shell’s Data Science CoE, where he is leading a multidisciplinary research group with passion for delivering innovation and excellence. He is deriving the vision for advancement of ML & AI research portfolio and technology development across Subsurface, Production & Operations, and New Energies. He has numerous publications and book chapters in the areas of pattern discovery, deep learning representation, and modeling & reasoning across multiple domains.

Nikolay Sorokin
Nikolay Sorokin

Data Scientist

Nikolay Sorokin is a data scientist at REI Systems Inc. He is coming from mechanical engineering background which he studied at City College of New York, then completed an IT master's degree program at Towson University. Nikolay is passionate about computer vision applications and knowledge extraction from unstructured text documents.

Nikolay Sorokin is speaker of the following session:

Said Soulhi
Said Soulhi

Distinguished Member of the Technical Staff

Dr. Said Soulhi, PhD, is a Distinguished Member of the Technical Staff working in the Wireless AI Innovation group at Verizon. He has established an excellent track record demonstrating the use of emerging networking paradigms (SON, Autonomic Management, SDN, NFV, etc). He is now focusing on how Artificial Intelligence and Machine learning can be used to improve network performance.

Said Soulhi is speaker of the following session:

Shams Zaman
Shams Zaman

Principal Data Scientist

Shams Zaman is a Principal Data Scientist in Network Capital Management group within Verizon. There, he is leading the efforts for developing predictive and prescriptive analytics to ensure optimum allocation of resources. He is developing network business intelligence by developing forecasting models from multivariate time series data sourced from networking cell sites, customer experience and geospatial data. Prior to joining Verizon, he was a Machine Learning Scientist at AI lab, Philips Healthcare. There he developed predictive models from longitudinal Electronic Health Record data for improving patient care. He also worked with advance pre-trained language models to develop state of the art NLP solutions for clinical concept recognition, concept disambiguation, data de-identification etc.

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