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

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

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

John Ainsworth is a senior data scientist employed by the Universityof Virginia Health System since July of 2014. He is currently workingwith the UVa Medical Center on a variety of predictive analyticprojects including the CMS AI Challenge where his team was selected asone of 25 competitors. Prior to coming to UVA, John designed,implemented, deployed, and monitored predictive analytic solutions fora wide variety of industries for Elder Research, a predictiveanalytics consulting company.

Charlie Berger is Sr. Director of Product Management, for Data Mining and Advanced Analytics at Oracle. He has over 30 years of experience in data analysis software including Oracle, Thinking Machines Corporation, Bolt, Beranek and Newman, Palladian (expert systems), Automatix (robotics and machine vision), Honeywell Computers and IBM. He is responsible for product management and direction of Oracle's in-databases' data mining and predictive analytics technology including data mining, text mining and SQL based statistical functions. He holds a MS in Manufacturing Engineering and an MBA both from Boston University. He holds a BS in Industrial Engineering and Operations Research from the University of Massachusetts at Amherst.

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, 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.

"Through the marriage of technology, information and analytics UPS reduces cost and improves services. These advanced technologies streamline our business processes and ultimately benefit our customers."

Jack Levis, Senior Director of Process Management, drives the development of operational technology solutions. These solutions require advanced analytics to reengineer current processes to streamline the business and maximize productivity.

Under Jack's direction, UPS has completed integration of multiple operations systems, requiring extensive system engineering, usability and analytics provisions. These systems ultimately synchronize the flow of data throughout UPS, allowing the seamless movement of goods, funds and information.

Jack has been the business owner and process designer for UPS' award-winning Package Flow Technology suite of systems, a breakthrough change for UPS, resulting in 85 million fewer miles driven each year.

His team designed UPS' next generation of dispatching technologies which use advanced optimizations. The world-class optimizations and systems, UPS ORION, On-Road Integrated Optimization and Navigation, is in deployment and will provide significant operational benefits to UPS and its customers.

Having earned his Bachelor of Arts in psychology, from California State University Northridge, Jack also holds a Master's Certificate in Project Management from George Washington University.

Jack holds advisory council positions for multiple universities and associations, including the U.S. Census Bureau Scientific Advisory Committee.

In his spare time, Jack enjoys baseball, scuba diving, skiing, home electronics and Corvettes. He lives in York, Pa. with his wife and four children.

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.

Gayatri manages eBay's Data and Analytics Platform Strategy. She is involved in strategic initiatives related to eBay's industry-leading data warehousing systems, map-reduce platforms, analytic products, business intelligence tools, collaboration portals, and fast analytics platforms. She has successfully launched over a dozen enterprise software products at leading organizations, such as Oracle and HP, and having founded an industry-leading complex-event processing (CEP) software company (now part of SAP), Gayatri has thrived for over 25 years on the challenge of matching innovation with high customer impact.

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.

Eric Siegel, Ph.D., founder of the Predictive Analytics World conference series and executive editor of The Machine Learning Times, makes the how and why of predictive analytics understandable and captivating. He is the author of the award-winning Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field.

Eric has appeared on Bloomberg TV and Radio, Business News Network (Canada), Fox News, Israel National Radio, NPR Marketplace, Radio National (Australia), and TheStreet. He and his book have been featured in Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, The Financial Times, Forbes, Forrester, Fortune, Harvard Business Review, The Huffington Post, The New York Review of Books, Newsweek, Quartz, Salon, Scientific American, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch. Follow him at @predictanalytic.

John Whittaker is the executive director of
marketing for Dell Software’s Information Management group, where he oversees
marketing activities for a diverse portfolio of solutions spanning database
management, data integration, business intelligence and big data analytics.
Prior to joining Dell, he was the director of product marketing for Quest
Software’s database management business. Whittaker has over 20 years of
experience with a variety of technology companies, including leadership
positions with companies such as AlertSource, Trinent Internet Solutions and
KnowledgeCentrix. His areas of expertise include database management, business
intelligence, advanced analytics, information security, business continuity and
disaster recovery planning and E-Commerce