Dean Abbott is an internationally recognized thought leader 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 the top pioneering and influential data scientists in the world. Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and coauthor of The IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a popular keynote speaker and bootcamp/workshop instructor at conferences worldwide and serves on advisory boards for the UC/Irvine Predictive Analytics and UC/San Diego Data Science Certificate programs. He holds a bachelors degree in computational mathematics from Rensselaer Polytechnic Institute and a masters degree in 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, 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.

“The future of Logistics is the marriage of Data, Operations Technology, and Advanced Analytics, which will reduce cost and improve services."

Jack Levis is responsible for Product Strategy at ESP Logistics Technologies. This role includes Optimization / Prescriptive Analytics. He is bringing with him 43 years of logistics and technology experience. 

Prior to joining ESP, Jack retired from UPS as a Senior Director of Industrial Engineering. During his 43-year career he was responsible for the development of operational technology solutions including digital twin infrastructure and optimization solutions. These solutions required advanced analytics to reengineer processes, streamline the business, and maximize productivity. 

Jack was the business owner and process designer for UPS’ Package Flow T

echnology suite of systems which includes its award-winning optimization, ORION (On Road Integrated Optimization and Navigation). These tools were a breakthrough change for UPS, resulting in a reduction of 225 million miles driven each year.

ORION alone is providing significant operational benefits to UPS and its customers. UPS estimates that ORION alone is reducing costs by $500M to $600M per year. 

Jack believes ESP can deliver similar gains to 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. 

He is a fellow of the Institute for Operations Research and Management Sciences (INFORMS), receiving their prestigious Kimball Medal and the President’s Award.

Jack is a frequently requested speaker for business executives and organizations. He has been featured in many publications and media productions including a TED talk and a NOVA show on Innovation. 

Jack has held advisory council positions for multiple universities and associations, including the United States Census Bureau Scientific Advisory Committee. 

The role Jack enjoys the most is Grandpa.

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., 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.

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