Halim is a high tech innovator who spearheaded world-class data science projects at game changing techs like eBay and Teradata. Formally educated in Machine Learning, his professional expertise span Information Retrieval, Natural Language Processing, and Big Data. Halim has a proven track record of applying state of the art data science techniques across industry verticals such as eCommerce, web & mobile services, airline, BioPharma, and the medical technology industry. He currently leads the AI department at Cognoa, a data driven behavioral healthcare startup in Palo Alto.

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).

Afsheen Alam has successfully implemented several data and analytics solutions to drive results. She has lead successful teams and implementations through collaborative processes. Afsheen has been quick to introduce new technologies in the newly changing environment to drive change.

Bryan Bennett is a professor for Northwestern University's School of Professional Studies where he is a predictive analytics subject matter expert and is responsible for the development and teaching of predictive analytics courses domestically and internationally. Additionally, he teaches leadership, healthcare marketing and consumer behavior courses at the graduate and undergraduate levels for other Universities.

Professor Bennett is also the Executive Director for the Healthcare Center of Excellence (healthcarecoe.org), a privately-funded healthcare research and consulting firm, where he researches and consults on transformation, advanced analytics and leadership issues for healthcare organizations. He is the author of the books, "Competing on Healthcare Analytics: The Foundational Approach to Population Health Analytics" and "Prescribing Leadership in Healthcare", as well as contributing the Data Stewardship chapter to the book "Adaptive Health Management Information Systems".

Bryan's work has appeared in several publications such as, DM News, Health Data Management, Becker's Hospital Review and Capco's Journal of Financial Transformation.

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.

Dr Thomas Brandenburger is an Associate Professor of Statistics at South Dakota State University and credit risk researcher and consultant. He has developed new methods for credit risk scorecards that address many of the unique issues encountered which are unique to scorecards. Edward Krueger is a senior manager of credit risk at Bluestem Brands, Inc. Allison Lempola is a Senior Data Scientist and consultant for RProfet specializing in credit risk scorecards. They collaborate to build open source credit scoring tools, which address issues in credit scorecards that often are overlooked in proprietary platforms.

James Casaletto is studying bioinformatics and biomedical engineering at UC Santa Cruz.  Previously, he worked at MapR Technologies where he designed, implemented, and deployed complete solution frameworks for big data. He has written and delivered courses on MapReduce programming, data engineering, and data science on Hadoop to thousands of students around the world.

Morgane Ciot is a data visualization engineer at DataRobot, where she specializes in creating interactive and intuitive D3 visualizations for data analysis and machine learning. Morgane studied computer science and linguistics at McGill University in Montreal. Previously, she worked in the Network Dynamics Lab at McGill, answering questions about social media behavior using predictive models and statistical topic models.

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.

Robert Grossman is a partner at Analytic Strategy Partners and a professor at the University of Chicago.  From 2002 to 2016, he was the Founder and Managing Partner of Open Data Group, which provided data science consulting services to a wide variety of companies, including those in financial services, location services, computational advertising and cybersecurity. From 1996 to 2001, he was the Founder and CEO of Magnify, which developed predictive analytic software for the financial services and computational advertising industries.  Magnify was sold to ChoicePoint in 2003 and is now part of the RELX Group.  He is the Frederick H. Rawson Professor of Medicine and Computer Science and the Jim and Karen Frank Director of the Center for Translational Data Science at the University of Chicago, where he leads a data science research group that is developing systems and algorithms for managing, analyzing and sharing large biomedical and environmental datasets.

Jeanne G. Harris is on the faculty of Columbia University of New York, where she teaches a graduate level course on Business Analytics Management.  Jeanne is also executive research fellow emerita of the Accenture Institute for High Performance. Before retiring, she was the Global Managing Director of Information Technology Research at the Accenture Institute for High Performance in Chicago. At Accenture, she led the Institute's global research agenda in the areas of information, technology, and analytics.

She is the co-author with Tom Davenport of the extensively updated new edition of "Competing on Analytics: The New Science of Winning" which will be published by Harvard Business Review Press, September, 2017. "Competing on Analytics, 2nd ed." demonstrates how high performance businesses are successfully leveraging big data, machine learning, AI, optimization and other analytical techniques; thereby building competitive strategies around data-driven insights that are generating outstanding business performance. Harvard Business Review editors named the first edition of the book one of the top breakthrough ideas of the 21st Century.  In 2009, Jeanne received Consulting Magazine's Women Leaders in Consulting award for Lifetime Achievement.

Lauren Haynes is currently Associate Director at the Center for Data Science and Public Policy at the University of Chicago. Her prior experience includes 3.5 years as a consultant in Accenture’s Technology Labs, IT Manager and Interim CIO at the Ounce of Prevention Fund, and Product Manager at GiveForward. Lauren focuses on the use of Human Centered Design and usability for social good.

William Komp is the Principle Data Scientist at Komplytics LLC.. He has over 2 decades of experience in academia, health care, marketing analytics, transportation, logistics, Oil&Gas, Food&Beverage, environmental management, renewable energy and public utilities. He was the technical editor for Applied Predictive Analytics (J. WIley and Sons 2014). He holds a PhD Physics with areas of research in Gravitation, Cosmology and Quantum Field Theory in Curved Spacetime.

Max Kuhn is a software engineer at RStudio. a leading company for R software and tools. He is currently working on improving R's modeling capabilities. He has a Ph.D. in Biostatistics.

Max was a Director of Nonclinical Statistics at Pfizer Global R&D in Connecticut. He was applying models in the pharmaceutical and diagnostic industries for over 18 years. Max is the author of eight R packages for techniques in machine learning and reproducible research and is an Associate Editor for the Journal of Statistical Software. He, and Kjell Johnson, wrote the book Applied Predictive Modeling, which won the Ziegel award from the American Statistical Association, which recognizes the best book reviewed in Technometrics in 2015.

He has taught courses on modeling, including many classes for Predictive Analytics World, the useR! conference, the Open Data Science Conference, the India Ministry of Information Technology, and others.

Kwan is currently CTO at AcademicMerit leading efforts in architecting software to understand student outcomes and student/teacher interactions in large scale online environments.  In his previous role he has been engineering and architecting data driven software to enhance sourcing and tracking of growth stage B2B software companies targeting the US market. He is an expert in social computing and has published peer reviewed papers and built many systems that provide insights through computational algorithms, distributed computing and human participation. Prior to AcademicMerit, he was at OpenView Venture Partners and Redstar Ventures that inspired his work on analyzing data and building software to make better decisions and enhance team, product and technology for startup companies. He has also worked at Bose, Intuit, Bank of America and GTE. Kwan completed his S.M. and Ph.D. degrees from MIT Media Lab and M.Eng. and B.S. degrees in computer science from Cornell University.

Nick is data scientist for the City of Chicago, and before that he spent a decade as a government attorney and senior official in both state and local government. Nick has spent considerable time working on litigation related to the foreclosure crisis and advising cabinet-level officials on policy development and legal issues. Nick also served as a chief administrative law judge, overseeing Illinois' legal appeals system for millions of people enrolled in Medicaid and many other federal healthcare and human service programs.

As a data scientist, Nick joins his operational and technical knowledge to identify impactful projects, and applies advanced analytics to create insights tailored for human-actionable decisions. Throughout his time in government, Nick has used data analytics to bring about quick and significant impact, streamlining processes and improving services.

Nick has a law degree and a master's degree in computer science from DePaul University, and a bachelor's degree from Ohio State University.

Holly Lyke-Ho-Gland is a principal research lead at APQC, with over ten years of business research and consulting experience. Her focus has predominantly been on best practices in business processes, change management, corporate strategy, and R&D. In her role as principal research leas for process and performance management at APQC, she is responsible for conducting and publishing research on process management , continuous improvement, benchmarking, strategic planning, and organizational performance management.

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.

Allison is deeply involved in all aspects of the modeling process. She is a subject matter expert in credit modeling as well as the development of the regular reporting processes and documentation necessary to create data driven decisions.

Her deep data skills combined with expert modeling techniques is a rarity in the analytics world. Allison earned a BA in Mathematics Education and an MS in Statistics. In her research she developed new statistical power calculations for measuring mixtures of non-normal distributions to measure the profitability in A/B testing in credit card customer behavior.

Dr. Jennifer Lewis Priestley, Ph.D., is a Professor of Applied Statistics and Data Science at Kennesaw State University, where she is the Director of the Center for Statistics and Analytical Services. She oversees the Ph.D. Program in Advanced Analytics and Data Science, and teaches courses in Applied Statistics at the undergraduate, Masters and Ph.D. levels. In 2012, the SAS Institute recognized Dr. Priestley as the 2012 Distinguished Statistics Professor of the Year. She served as the 2012 and 2015 Co-Chair of the National Analytics Conference. Datanami recognized Dr. Priestley as one of the top 12 "Data Scientists to Watch in 2016."

She has authored dozens of articles on Binary Classification, Risk Modeling, Sampling, Applications of Statistical Methodologies for Problem Solving as well as several textbook manuals for Excel, SAS, JMP and Minitab. Prior to receiving a Ph.D. in Statistics, Dr. Priestley worked in the Financial Services industry for 11 years. Her positions included Vice President of Business Development for VISA EU in London, where she was responsible for developing the consumer credit markets for Irish and Scottish banks. She also worked for MasterCard International as a Vice President for Business Development, where she was responsible for banking relationships in the Southeastern US. She also held positions with AT&T Universal Card and with Andersen Consulting.

Dr. Priestley received an MBA from The Pennsylvania State University, where she was president of the graduate student body, and a BS from Georgia Tech. She also received a certification from the ABA Bankcard School in Norman, OK, and a Certification in Base SAS Programming, and a Business Analyst Certification from the SAS Institute.

Sri Raghavan is a Senior Global Product Marketing Manager for Teradata with more than 20 years of experience developing products, leading advanced analytics/data science agendas, and delivering marketing and sales initiatives that drive the performance and profitability of organizations across the Big Data Applications, Financial Services, Healthcare, and Management Consulting industries.

Sri has a history of managing multiple data science and advanced analytics projects across industries and big data programs to effectively align technology with business goals and financial objectives. Sri has built, trained and supported top-performing global IT teams and has presented and demonstrated a variety of analytic functionality and solutions to customers and in conferences across the U.S. and overseas

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.

Federico Rosenhain has been working in the information business for the last 15 years and specifically in finance for the last 10. He currently leads big data and data science projects, and their integration with data warehouse development by way of a variety of tools.

He also designed and coordinates the Big Data and Analytics program at the Universidad de Palermo.

Thomas Schleicher is a results-focused executive with nearly 20 years of experience in delivering actionable, data-based insights and profit-optimizing results for various high-profile clients across multifaceted, competitive industries. He is currently Senior Director of Measurement Science at National Consumer Panel, a joint venture of Nielsen and IRI. NCP is the largest longitudinal consumer panel in the world, and it provides the quality data its parent companies leverage to share consumer insights with their respective clients.

Prior to his current role, Tom has had stints at Ipsos-ASI, Bayer HealthCare (Pharmaceuticals), and smaller analytic shops including Symphony Marketing Solutions and Spire, a Loyalty Marketing Analytics firm. Trained as an Experimental Social Psychologist (Ph.D. earned at the University of Wisconsin - Milwaukee), he is currently augmenting his statistical and social research methods expertise as he nears completion of his online Certificate in Predictive Analytics at UC-Irvine.

As Chief Data Officer at Auspice Analytics, Edward S. Shihadeh, PhD is internationally recognized for the results of his cutting-edge predictive analytic techniques. During his tenure as Professor of Sociology at Louisiana State University, he published extensively in leading journals, won numerous university awards, including the exclusive Senior Rainmaker Scholar Award and the Chancellor's Technology Transfer Award for his college student retention algorithms. He has also amassed an impressive record of external funding totaling in the millions. His data science techniques, which are unique in their consideration of structural factors, are used in the most accurate election predictions this election cycle, reduced the homicide rate in Baton Rouge by 26% in 2013 and by 48% in 2016, increased college student retention in a major university to record levels, and optimized student recruitment in that university.

Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI Applications Summit, 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. Eric also 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. Eric and his books have been featured in Big Think, Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, Fast Company, The Financial Times, Forbes, 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.

Michael Sims is researcher and writer who explores data and analytics and process and performance management best practices and innovations. With an MBA from Rice University and a background in business analysis and process improvement, Michael considers himself a lifelong consumer and sharer of knowledge. Michael's passion for analytics stems from love for efficiency, his undying basketball fandom, and analytics' unparalleled ability to optimize both.

Steve Ulinski has over 22 years' experience in information technology. He has a bachelor's degree in General Studies with minors in Computer Information Systems and Psychology. For the past 11 years' he has worked at Health Care Service Corporation in the security operations center supporting the security analysts. Currently he is focusing on researching and applying AI, knowledge management, big data, and predictive analysis to cyber security.

Jim is a Human Resources Business Partner and Organizational Development leader and practitioner, with approximately 20 years of experience at AT&T, America Online, Microsoft, Nokia, and Nokia Siemens Networks. Jim is presently a Global Program Manager in Organizational Development at Nokia focusing on HR Analytics; he has experience on enterprise-wide projects which span 150 countries. Jim has worked on the cultural integrations of divisions of Siemens and Motorola, and Alcatel-Lucent into Nokia, along with other innovative change management initiatives.

Jim has a Master's Degree in Human Relations from the University of Oklahoma and a doctorate degree in Organizational Leadership from Argosy University-Sarasota; his dissertation study focused on creative problem solving within a business context.

Chao is a Senior Data Scientist at Microsoft. Prior to Microsoft, Chao was the Lead Data Scientist at Scopely, a mobile gaming company in LA. Chao was a Ph.D. ABD (all but dissertation) in Mathematics from Michigan Technological University. He holds a M.S. degree in Financial Engineering from Temple University, and a B.S. degree in Computer Science from Beijing University of Aeronautics and Astronautics. His current research interests include (deep) machine learning for customer journey and customer lifetime value, (deep) reinforcement learning for interactive customer behavior modeling.