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.

Gary Anderberg has worked in developing predictive analytic applications for workers' compensation insurance since 2007. He is a recognized expert in the use of PA outputs for guiding the handling of complex claims to drive improved claim outcomes. He is the "godfather" of the Waypoint system and its key role in improving overall decision making and the more effective use of claim resources at Gallagher-Bassett. He will speak to the business case for a system like Waypoint and the corporate cultural and practice issues involved in socializing potentially complex PA system outputs with deeply entrenched work patterns at the end user level. He knows first-hand how the most brilliant PA applications can founder when output and practice cultures clash.

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.

Sergo leads global efforts in enterprise technology architecture, analytics, and systems road mapping at Crawford & Company. His responsibilities include providing direction and leadership for development of business intelligence technology and statistical, data mining, and predictive analytic models for claim operations and client stewardship. Sergo has 16 years of technology industry experience; he has proven success in increasing maturity of enterprise technology architecture and in wide adoption of advanced analytics and business intelligence at organizations of various sizes; he earned a master's degree in management science and a bachelor's degree in applied mathematics and computer science.

Madhu Iyer is a Marketing Statistician at Intuit's Data Sciences and Analytics team. She consults with marketers across the company to provide unique insights using the collective data of 50 million customers. Madhu has a background in research, and consulting. Prior to Intuit, she was a Scientist at Exponent working extensively on the application of statistical methods to business environments. Her work covered issues related to the evaluation of passenger vehicle field performance, multivariate analysis, survival analysis, design of experiments, and analysis of survey data.

When Natalie was in 4th grade, she created an idea that became a national commercial for Tide.  Having peaked on the creative side at such a young age, she decided to dedicate the rest of her advertising career to helping business leaders make better marketing decisions based on data and research.

And dedicated she has been. Her resume reads like a Fortune 500 wish list: PwC, IBM, CoreMetrics, Dell, Humana, and The Richards Group.  Her core competencies include everything from pricing and marketing mix modeling to decision science management and data science. But wait, there’s more: Natalie has also invented and patented multiple marketing optimization models, teaches Big Data at conferences, and hosts her own blog celebrating the confluence of mathematics and marketing.

Jim is a semi-retired data scientist specializing in data-driven customer insights. He is currently engaged by One Medical (San Francisco), Li and Fung (Hong Kong), and Leitersburg Cinemas (MD). In 2015 he focused on Lynda.com (a LinkedIn/Microsoft company). Past experience includes Minted.com, Ancestry.com, Responsys, LA Times, 24 Hour Fitness and Sun Microsystems, to name a few.

Jim specializes in using customer behavioral and demographic data to predict propensity to purchase and/or churn, do uplift modeling, segment customers based on cluster analysis, and do routine marketing analytics. Jim is very active in the open-source community; particularly with R-the open-source software environment for statistical computing and graphics. He is a frequent speaker at conferences in the US & Europe.

Chris created, hired, and leads a team of Data Scientists whose charter is to help add statistical firepower to some of Netflix’s more complex analyses (for example demand prediction for how much a movie will be watched to help Netflix's content buyers understand the value of a movie), and assist in algorithmic development for better personalization (for example movie similars, user clustering, and movie ranking). Chris is also an adviser to venture funded startups, including Bonobos, Plum District, and Mahoot.

Inna Shapotina is a Senior Technical Data Analyst at Intuit's Data Sciences and Analytics team. She works across the different functions at Intuit to identify metrics and analyze data that drive the business. Inna has an extensive background in data analysis in various fields. Prior to joining Intuit, among other roles, she worked in a non-profit research organization, clinical trial company, financial and accounting firms.

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.

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.

After 15 years as an accountant and management consultant, Willemse joined Crawford & Company in 1998 as a senior adjuster in South Africa, where he handled property, fidelity guarantee, business interruption and rail transportation claims, including international assignments. In 2004, he was promoted to the position of managing director of operations in sub-Saharan Africa, where he implemented various leadership development and change management programs and managed strategic planning and business development activities.

Bob Wood serves as Merkle's Senior Director â€" Advanced Analytics & Research. He and his team have been involved in numerous analytic and insights projects to support global brands such as MetLife, UnderArmour, Dell, Warner Brothers and Assurant, to help them market more effectively and more efficiently. In addition to having 17 years of leadership experience in research and analytics, Bob has a BS in Math & MS in Applied Math from BYU, MS in Statistics from Wichita State, an MBA from the Marriott School of Management, and is currently a doctoral candidate focusing on consumer psychology at Wichita State University.