Dean Abbott is President of Abbott Analytics and currently is the Bodily Bicentennial Professor in Analytics at UVA Darden School of Business. He is an internationally recognized thought leader and innovator in data science and predictive analytics with more than three decades of experience solving a wide range of private and public sector problems. Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and coauthor of The IBM SPSS Modeler Cookbook (Packt Publishing, 2013).

Natasha received her Master's and Ph.D. in Computer Science from Vanderbilt University with an emphasis in Data Mining from large data sets. Her dissertation focused on creating and applying novel data mining techniques to mobile robots and real time sensor data. She has been with UCSD since 2003. She has also led multiple collaborations across a wide range of organizations in industry, government and academia. She had founded and led the Predictive Analytics Center of Excellence at the Supercomputer Center until 2016. She is currently directing the Interdisciplinary Center for Data Data Science (ICData) at Calit2/Qualcomm institute and lectures at the computer Science Department. Dr. Balac has a number of large and multidisciplinary government and research funded projects including the Center for Medicaid and Medicare Services, NASA, NSF, CPUC, Smart Grid, Smart City, etc. Dr. Balac has founded and serves at the President and CEO of Data Insight Discovery, Inc. DID's charter is enabling businesses to discover actionable insight from vast amounts of data across verticals.

Michael Berry is co-author of some of the most widely read and respected books on data mining including Data Mining Techniques for Marketing, Sales, and Customer Relationship Management which is now in its third edition. These best sellers in the field have been translated into many languages. Michael is an active practitioner of data mining. His books reflect many years of practical, hands-on experience down in the data mines. Michael is Director of Analytics at Tripadvisor for Business, the B2B side of Tripadvisor, the world’s largest travel-related web site. Prior to joining Tripadvisor, he spent many years as a data mining consultant and educator.

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

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

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

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

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

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

John Elder chairs America’s most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina, and Washington DC. 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.

Tom Kern is a Risk Modeling Manager at Paychex, Inc. Under the Risk Management umbrella, Tom helps to coordinate and execute a wide range of projects centered on predictive modeling, optimizing processes in all departments from sales strategy to internal operations and mitigating risk throughout the company.

Tom joined Paychex in 2012. Prior to Paychex, Tom was a Predictive Modeling Analyst with a large digital marketing agency, servicing major clients in the financial services, insurance, and automotive industries. He holds a MA from Boston University in Applied Statistics, and a BA from Boston University in Applied Mathematics. Tom is a four-time PAW speaker.

Mahesh is the Founder and CEO of Tiger Analytics. He started Tiger Analytics with a desire to bring his experience in management science to help organizations achieve superior performance through the application of advanced analytics.Before founding Tiger Analytics, Mahesh was on the faculty of the Smith School of Business and Rutgers Business School.

Mahesh has conducted research in the areas of data mining and statistical modeling and has successfully applied his research to solve problems related to forecasting, pricing, promotions, and customer segmentation for a wide range of businesses across industries. Mahesh holds a Ph.D. in Operations Research and Marketing from MIT, and a B.Tech in Computer Science from IIT Bombay.

Daniel Porter is the cofounder of BlueLabs, a Washington DC based analytics, data and technology company whose clients include political campaigns, nonprofits and corporations.

Prior to founding BlueLabs, Daniel was Director of Statistical Modeling for the 2012 Obama reelection campaign. His team developed individual level statistical models that were used throughout the campaign for fundraising, media buying and state strategy. These models served two primary purposes: to pinpoint which voters were most likely to take an action or hold a belief (i.e. support the President or turn out to vote) as well as to measure the influence a campaign contact had on an individual's likelihood to take such actions or change their beliefs. Combined, these measures helped the campaign optimize their targeting to maximize their return on investment.

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

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

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

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

Karl Rexer founded Rexer Analytics in 2002. He and his teams have built an outstanding reputation providing predictive modeling and analytic consulting to clients across many industries. Recent clients include OneBlood, PwC, Boston Scientific, Redbox, ADT Security, Interamericana University, MIT, Forward Financing, SharkNinja, 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. 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.

Eric Siegel, Ph.D., is a former Columbia University professor who helps companies deploy machine learning. He is the cofounder and CEO of Gooder AI, the founder of the long-running Machine Learning Week conference series, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker. He wrote the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, which has been used in courses at hundreds of universities, as well as The AI Playbook: Mastering the Rare Art of Machine Learning Deployment. Eric’s interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching the graduate computer science courses in ML and AI. Later, he served as a business school professor at UVA Darden. A Forbes contributor, Eric publishes op-eds on analytics and social justice.

Eric has appeared on Bloomberg TV and Radio, BNN (Canada), Israel National Radio, National Geographic Breakthrough, NPR Marketplace, Radio National (Australia), and TheStreet. A Forbes contributor, Eric and his books have been featured in BBC, Big Think, Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, Fast Company, The Financial Times, Fortune, GQ, Harvard Business Review, The Huffington Post, The Los Angeles Times, Luckbox Magazine, MIT Sloan Management Review, The New York Review of Books, The New York Times, Newsweek, Quartz, Salon, The San Francisco Chronicle, Scientific American, The Seattle Post-Intelligencer, Trailblazers with Walter Isaacson, The Wall Street Journal, The Washington Post, and WSJ MarketWatch.

Analyst Sarah Will graduated cum laude from The College of William & Mary in 2010 with a B.S. in Mathematics and a minor in Linguistics. She joined ERI in 2011 in the Washington, D.C. office, where she does work involving fraud detection, data visualization, and text analysis. She previously worked as a Mathematical Statistician for the U.S. Census Bureau. In her free time, she enjoys playing the piano, making jewelry, and is on a recreational floor hockey team. She hopes her knowledge of dead languages (Latin, Old English, and Biblical Hebrew) will come in handy in the near future.