Speakers

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.

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.

Bob Bress is Head of Data Science at Freewheel, a Comcast Company focused on advanced advertising technologies. In that role he leads teams of data science and analytical staff using their expertise to lead the development of the next generation of advanced targeted advertising products for television and premium video. Bob has over 15 years of analytics experience across industries including work in hospitality, energy, and at GE's Global Research Center in the Applied Statistics Lab.

Bob holds undergraduate and graduate degrees in Industrial Engineering and Operations Research & Statistics from Rensselaer Polytechnic Institute.

Mark leads real-time and near real-time voice interaction and unstructured text analytics Insights Intelligence and data sciences across Microsoft’s multi-vendor, multi audience, multi product and services global support centers. The mission is to provide the right insights, at the right time, for the right purpose, to the right audience for action that drives business impact and ROI. He has deep experience with, and is passionate about, the root-causes of a Company’s customer experience, and the drivers of its satisfaction, affinity, and loyalty for business revenue and health. In an earlier role at Microsoft he led the MVP influencer satisfaction, affinity and loyalty program, moving OSAT from the mid 40’s to consistently over 80% within 2 years. As customers moved in ever increasing numbers to talk about their experiences online, he followed the trend to lead the Consumer Support Social Media Insights and Intelligence team who synthesized hundreds of millions of social data points to track and monitor major product launched like Windows 8, Office, Surface and others. He has led small, agile, performance-driven teams, as well as larger teams of up to over 20, received Customer-Partner Experience Champion Microsoft awards, Industry awards (TMRE Explore), and has been a sought-after conference speaker for over 5 years. Off-work he likes to run off mountains under a paraglider, hike the Himalayas, and has been scuba diving in the USVI. A family man, he has 2 daughters, one of who is an opera singer (look for Serena on YT), and the other a budding business major.

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.

Kim Larsen is the VP of Data at ThirdLove. Kim has experience working in the software and consulting industries, as well as e-commerce and financial services. Throughout his career, he has managed a wide array of data mining and analytical problems including price optimization, media mix optimization, demand forecasting, customer segmentation, and predictive modeling. Kim frequently speaks at data mining conferences around the world in the areas of segmentation and predictive modeling. His main areas of research include additive non-linear modeling and net lift models (incremental lift models).

“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.

Bin Mu is the Vice President, Data Science of MetLife. In this capacity, he is responsible for applying advanced analytics to identify and explore business opportunities, increase topline sales, and improve operation efficiency and effectiveness. He currently leads a team of 20 data scientists that supports MetLife’s business across all the product lines. Before joining MetLife, Bin was the Global Head of Data Analytics at Cigna, responsible for all the analytics to support group business. Prior to that, Bin Mu held various analytics leadership positions at Deloitte, Limited Brands, and The Hackett Group.

Bin Mu is a competitive marathoner and active triathlete.

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.

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.

Shawn Rogers is Chief Research Officer for the Information Management Group at Dell Software. Shawn is an internationally recognized thought leader, speaker, author and instructor on the topics of big data, analytics, cloud, data integration, data warehousing and social analytics.

Shawn has more than 19 years of hands-on IT experience. Prior to joining Dell he was Vice President Research for Business Intelligence and Analytics at Enterprise Management Associates a leading analyst firm. He co-founded the BeyeNETWORK, a global publication covering business intelligence, data warehousing, and analytics. He was also a partner at DMReview magazine.

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.

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.

Mike serves as Head of Data Science at Uber ATG, UC Berkeley Data Science faculty, and head of Skymind Labs the Machine Learning research lab affiliated with DeepLearning4J.  He has led teams of Data Scientists in the bay area as Chief Data Scientist for InterTrust, Director of Data Sciences for MetaScale/Sears, and CSO for Galvanize where he founded the galvanizeU-UNH accredited Masters of Science in Data Science degree and oversaw the company's transformation from co-working space to Data Science organization.  Mike began his career in academia serving as a mathematics teaching fellow for Columbia University before teaching at the University of Pittsburgh. His early research focused on developing the epsilon-anchor methodology for resolving both an inconsistency he highlighted in the dynamics of Einstein’s general relativity theory and the convergence of “large N” Monte Carlo simulations in Statistical Mechanics’ universality models of criticality phenomena.

James Taylor is Executive Partner at Blue Polaris and is a leading expert in how to use business rules and analytic technology to build decision management systems. He is passionate about using decision management systems to help companies improve decision-making and develop an agile, analytic and adaptive business. He provides strategic consulting to companies of all sizes, working with clients in all sectors to adopt decision-making technology. James is an expert member of the International Institute for Analytics and is the author of multiple books and articles on decision management, decision modeling, predictive analytics and business rules, and writes a regular blog at JT on EDM. James also delivers webinars, workshops and training. He is a regular keynote speaker at conferences around the world.