Speakers

Dean Abbott is President of Abbott Analytics and currently is the Bodily Bicentennial Professor in Analytics at UVA Darden School of Business. He is an internationally recognized thought leader and innovator in data science and predictive analytics with more than three decades of experience solving a wide range of private and public sector problems. Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and coauthor of The IBM SPSS Modeler Cookbook (Packt Publishing, 2013).

Anwar is a data engineer for MapR, where he is working on solving day to day big data problems. For the past six years, Anwar has worked in software development and data analysis for a variety of companies, including Stanford University, DST, USDA, and NIPR. Anwar's main interests are in the fields of data science, data engineering and software engineering. Anwar holds a Master's Degree in Computer Science from the University of Missouri in Kansas City.

Julian is a Data Scientist supporting the Marketing teams in Google. His primary focus is using ML Models to solve difficult problems in the Marketing space. He holds a Bachelor's degree in Mechanical Engineering and a Masters in Industrial Engineering from Texas A&M University. He currently resides in California.

Clinton Brownley, Ph.D., is a data scientist at WhatsApp, where he’s responsible for a variety of analytics projects designed to improve messaging and VoIP calling performance and reliability.  Before WhatsApp, Clinton was a data scientist at Facebook, working on large-scale infrastructure analytics projects to inform hardware acquisition, maintenance, and data center operations decisions.  As an avid student and teacher of modern analytics techniques, Clinton is the author of two books, “Foundations for Analytics with Python” and “Multi-objective Decision Analysis,” and also teaches Python programming and data science courses at Facebook and in the Bay Area. Clinton is a past-president of the San Francisco Bay Area Chapter of the American Statistical Association and is a council member for the Section on Practice of the Institute for Operations Research and the Management Sciences. Clinton received degrees from Carnegie Mellon University and American University.

Lawrence is Senior Partner, COO and Customer Insights & Advanced Analytics practice leader with Cicero Group. Lawrence has spent the last decade building Cicero's analytics practice where he has experience helping Fortune 1000 firms solve real business challenges with data, including attrition, segmentation, sales prioritization, pricing, and customer satisfaction. He also leads the firm in predictive analytics and Big Data related engagements, applying Cicero’s deep expertise in strategy execution to ensure data delivers ROI.  He has partnered with companies to help them to shift from reactive to predictive analytics by collecting and analyzing real-time information and distributing it across the organization— allowing management to make better, faster decisions that move the business forward.

Lawrence holds a Master’s of Science in Predictive Analytics from Northwestern University, an MBA with an emphasis in Business Economics from Westminster College, and a BA from Brigham Young University

Dr. Gourab De is the Vice President of Data Science at DataRobot, where his primary focus is helping customers improve their ability to make and implement predictions. Previously, De was part of the data science team at Ginger.io focusing on behavioral analytics in mental health. His professional experience includes statistical genetics, clinical trials, retrospective claims analysis, chart review studies, predictive modeling and pharmacoeconomic modeling. De graduated with honors from the Indian Statistical Institute in Kolkata, India, and received a Ph.D. in Biostatistics from Harvard University.

Paul has 30+ years experience with IBM focused on bringing new and emerging technologies to the mainframe. he is currently responsible for developing and executing IBM's worldwide z Systems big data and analytics portfolio marketing strategy, including the role of z Systems in IBM's Cognitive and Internet of Things (IoT) businesses.

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.

Ken has over 25 years of experience delivering analytic solutions. He started his career in analytics at SPSS, where he served for 14 years most notably as the Vice President of Analytic Solutions and Professional Services. From there, Ken co-founded an analytics consulting practice focused on the convergence of Market Research and Enterprise Data for holistic customer intelligence.

For the past 12 years, Ken has been with Hewlett Packard holding leadership positions within Global Business Intelligence IT, Global Analytics and Enterprise Services. He is currently the Global Director of Analytics within Hewlett Packard Enterprise Services. Ken holds a Ph.D. in Industrial Psychology (with a focus on analytics of course).

Ivan R. Judson is a Senior Engineer at Microsoft. While at Argonne National Laboratory he built high performance computing systems, large format projection displays, and advanced collaborative workspaces. At Montana State University he taught undergraduate and graduate Computer Science and created the Research Computing Group to consolidate, stabilize, and productionize compute and data management services for the $100M research enterprise. He left the university to open an office for Workiva (formerly WebFilings) in Bozeman, MT recruiting 40 of the top developers in the area and establishing five product teams. Ivan has also worked in wireless and mesh technology, earning his Doctorate for work in Resource Allocation Algorithms in Cognitive Wireless Networks. Ivan's current focus is in Mesh Networking, Edge Computing and the Internet of Things, with a focus on connecting devices and extracting actionable knowledge from the data through machine learning.

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).

As the Chief Data Scientist with Oracle's Big Data Pursuit Team, Avishkar Misra helps customers realize the value Big Data and predictive analytics can bring to their organization. His research & development experience spans online retail and advertising, cloud computing, defense and flight simulation & training, as well as medical research. Prior to Oracle he was a machine learning scientist at Amazon, building real-time predictive modeling systems for advertising and product recommendations. Avishkar holds a PhD from University of New South Wales, where he developed techniques to incrementally engineer medical vision systems, enabling them to learn and improve over time.

Ming is a Principal Data Scientist at Linkedin, where she and her team are responsible for building and delivering a wide variety of analysis focus on understanding, increasing growth, retention and engagement at Linkedin. Prior to joining Linkedin, she worked at Cisco System, AT&T and University of California at Santa Barbara. Ming holds a Masters in Computer Science from the State University of New York at Stony Brook, where she studied automated theorem proving.

Haile Owusu is Chief Data Scientist at Mashable where his main responsibility is the development and refinement of the company's proprietary Velocity technology, which predicts and tracks the viral life-cycle of digital media content. Haile specializes in statistical learning as applied to predictive analytics and has a background in theoretical physics, including a Ph.D from Rutgers University, a Masters of Science from King's College, University of London and a B.A. from Yale University.

Rebecca Pang is the senior director of channel strategy and analytics for CIBC, where she leads the retail channel analytics team to develop and evaluate strategic programs or initiatives related to integrated channel strategy. Prior to the current role, Pang was working in the mergers and acquisitions, investment banking and Strategy & Corporate Development teams at CIBC. Pang has also worked as a senior manager for T-Mobile USA, an investor relations officer for China Netcom in Beijing and a business analyst for McKinsey and Company in Hong Kong.

Pang earned her honours bachelor of business administration from the Chinese University of Hong Kong, and then served as an HSBC scholar at Columbia University. She received her MBA from Stanford University's Graduate School of Business and later earned her Chartered Financial Analyst and Chartered Business Valuators designations.

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.

Karl Rexer founded Rexer Analytics in 2002. He and his teams have built an outstanding reputation providing predictive modeling and analytic consulting to clients across many industries. Recent clients include OneBlood, PwC, Boston Scientific, Redbox, ADT Security, Interamericana University, MIT, Forward Financing, SharkNinja, and many smaller companies. In addition to leading client engagements and hands-on data work, Karl is a predictive analytics evangelist, frequently speaking at conferences, colleges, and other events. He also serves on Advisory Boards for the Business Analytics programs at both Babson College and Bentley University. Since 2007 Rexer Analytics has conducted surveys of analytic professionals, asking them about their algorithms, tools, behaviors and  views. Summary reports from these surveys are available as a free download from the Rexer Analytics website. Prior to founding Rexer Analytics, Karl held leadership positions at several consulting firms and two multi-national banks. Karl holds a PhD from the University of Connecticut.

Satadru Sengupta is a Senior Engagement Director, Data Science at DataRobot. In this role, Satadru leads the data science engagement team in the US East Region and he works hands-on with the organizations in the NYC area (healthcare, financial and insurance industry) to integrate DataRobot machine learning platform in their problem-solving environment. Previously, Satadru worked with AIG Science Team as a Senior Manager leading quantitative modeling for global distribution. Prior to that, he worked with Liberty Mutual Insurance and Deloitte Consulting. Satadru holds a Master of Science in Actuarial Science and a Master of Science in Statistics. Satadru lives in Washington, D.C. with his wife.

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.

Mike has 20+ years experience developing advanced analytic, technical, and business process solutions to solve complex marketing problems. Mike has been instrumental in driving key innovations in the automotive marketing and analytics services sector including advanced safety recall, analytically driven real time marketing, retail marketing analytics and customer communications, and extending traditional CRM into the digital, multi-channel ecosystem. Mike is a frequent speaker on advanced automotive marketing and analytics including JD Power AMR, DMAD Automotive Integrated Symposium, TLS Customer Centricity, and WardsAuto's Dealer Business. Mike received his BS from the University of Michigan and has a Kellogg MBA.

As Chief Data Scientist at Hopper, Patrick Surry analyzes flight data to help consumers make smarter travel choices. Patrick is recognized as a travel expert and he frequently provides data-driven insight on the travel industry and trends.

Patrick’s research and commentary have been featured in outlets such as New York Times, USA Today, Bloomberg Businessweek, TIME, and many others. Patrick also regularly appears on various broadcast stations to offer travel insight and tips.

Patrick holds a PhD in mathematics and statistics from the University of Edinburgh, where he studied optimization based on evolutionary algorithms, following an HBSc in continuum mechanics from the University of Western Ontario.

You can also follow Patrick on Twitter at @PatrickSurry.

Mario Vinasco has over 18 years of progressive experience in data driven analytics with emphasis in database programming and predictive models creatively applied to eCommerce, advertising, customer acquisition/retention and marketing investment. Mario specializes in developing and applying leading edge business analytics to complex business problems using big data platforms, including Hadoop, columnar and traditional relational models.

Mario holds a Masters in engineering economics from Stanford University and currently works for Facebook as data scientist in the consumer marketing group; in this role he is responsible for improving the effectiveness of Facebook's own consumer-facing campaigns.

Key projects include ad-effectiveness measurement of Facebook's brand marketing activities, and product campaigns for key product priorities using advanced experimentation techniques.

Prior roles included VP of business intelligence in digital textbook startup, people analytics manager at Google and eCommerce Sr manager at Symantec.

Hans Wolters is a Principal Data Scientist within the Windows and Devices Group at Microsoft. He received an M.S in Applied Math from the University of Goettingen, Germany and a Ph.D. in Computer Science from Arizona State University. Hans joined Microsoft's Xbox Division in 2012 where he was responsible for several features of the XBoxOne console. Prior roles included Sr Scientist at HP Labs, Head of Bioinformatics and Bio-statistics at XDx and Principal Data Scientist at Zynga where he built the foundations for making game play more personalized.

Jing Zhu is a Risk Modeling Analyst at Paychex Inc., a leading provider of payroll, human resource, insurance, and benefits outsourcing solutions for small- to medium-sized businesses. Jing's main responsibility is developing models to help with strategic decisions across all aspects of the business, including effectively targeting retention strategies, assisting in dynamic cross-sell initiatives, and improving collection targets. Jing holds a PhD in Biology from the University of Rochester, where she applied statistics in biological research.