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.

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.

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.

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.

Ashok Ramani is currently the product lead for eBay Inc.'s data solutions. His focus is to create new business opportunities and disruptive innovations from the massive commerce data sets across PayPal, eBay Enterprise and eBay Marketplace businesses, which collectively enabled $205bn in global commerce in 2013. Prior to eBay, the entrepreneur in Ashok led him to found Wazzin, a social platform for private local communities. Before that, he was product lead for Yahoo!'s large-scale content platforms that powered Yahoo! Sites globally. Prior to Yahoo!, as a software developer, he has contributed to numerous platforms and industry standards (B2B, e-Commerce, security) at IBM and several enterprise companies. Ashok has co-authored a book on Java Network Security.

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.

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.