Speakers

This page is updated weekly. Please check back frequently for the latest information.

Co-Chairs

Dr. Jerry Oglesby, SAS
Dr. Dirk Van den Poel, Ghent University

Keynote Speakers

Bart Baesens, Katholieke Universiteit Leuven (Belgium) and University of Southampton (United Kingdom)
Michael Berthold, University of Konstanz
John Elder, Elder Research, Inc
Manfred Krafft, University of Münster
Kim Larsen, Charles Schwab & Co
Will Neafsey, Ford Motor Company

Session Speakers

Mattias Andersson, TRE
Philippe Baecke, Ghent University
Chakib Battioui, Eli Lilly
Dr. Tom Bohannon, SAS and Texas A&M University
Stephen Brobst, Teradata
Mark Carmichael, Eclipse International
Gary Class, Wells Fargo & Company
Randy Collica, Hewlett-Packard
Dr. Goutam Chakraborty, Oklahoma State University
Filip Deforce, Accenture
Barry deVille, SAS
Cheryl Doninger, SAS
Martin Ellingsworth, ISO Innovative Analytics
Nick Evangelopoulos, University of North Texas
Robert Golan, DBmind Technologies, Inc.
Viterbo H. Berberena González, Universidad Anahuac
Vincent Granville, AnalyticBridge
Dudley Gwaltney, SunTrust Bank
Guillermo Híjar, Universidad Anahuac
Zainab Jamal, HP Labs
Meredith John, SAS
Dr. Ronald Klimberg, Saint Joseph's University
Hye-Chung Kum, University of North Carolina
Choudur K. Lakshminarayan, HP Laboratories
Randall LaViolette, Sandia National Laboratories
Dr. Carl Lee, Central Michigan University
Michael Leonard, SAS
Bruce Lund, Marketing Associates LLC
Riku Mäkeläinen, TeliaSonera
Colleen McCue, MC2 Solutions, LLC
Punit Mahajan, Infosys Technologies
Robert Moberg, TRE
Peter Pawlowski, Aster Data Systems
Anita Prinzie, Unversity of Manchester
Patrick Ryan, GlaxoSmithKline Research & Development
Sascha Schubert, SAS
Saratendu Sethi, Teragram
David Shamlin, SAS
Dr. Mike Speed, Texas A&M University
Judy Spomer, Sandia National Laboratories
Olivier Thas, Ghent University, Belgium
Shusaku Tsumoto, Shimane University
Maarten Verschuere, dunnhumby
Donald Wedding, SAS
Terry Woodfield, SAS
Katsutoshi Yada, Kansai University, Osaka, Japan
Jun Yan, Deloitte Consulting LLP
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Mattias Andersson Customer Insight Manager at the telecom operator 3 in Sweden. Mattias Andersson is working together with co-speaker Robert Moberg at the Loyalty Management Department with the target to increase loyalty and customer value. The retention strategy, as well as cross and up-sell processes are examples on Robert and Mattias' successful work with DataMining and advanced statistical analysis. Mattias has been working with database analysis and analytical CRM for more than 10 years. Mattias has a history in Stroede Customer Development, Nordea, Vodafone/Telenor and currently at 3. Mattias holds a M Sc. in Business Administration and Economics from Växjö University.
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Philippe Baecke is a Ph.D. candidate in Economics and Business Administration at Ghent University (Belgium). He is a Master in Applied Economics and specialized his research skills during an advanced Master after Master in Marketing Analysis at Ghent University (Belgium). During his academic research he collaborated with several commercial companies like Plan, Tesco, WDM and BIG. His Ph.D. thesis is focused on data augmentation in a Customer Relationship Management context. In this research field he has expertise in enhancing traditional databases with alternative data ( e.g. commercially available data and neighborhood data) by means of several data mining techniques (e.g. random forests and multilevel modeling) in order to improve the predictive performance of CRM models.
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Bart Baesens Dr. Bart Baesens is an assistant professor at the Faculty of Applied Economic Sciences at the K.U.Leuven (Belgium) and the School of Management of the University of Southampton (United Kingdom). He has done extensive research on predictive analytics, data mining, customer relationship management, fraud detection, and credit risk management. His findings have been published in well-known international journals (e.g. Machine Learning, Management Science, IEEE Transactions on Neural Networks, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Evolutionary Computation, Journal of Machine Learning Research, ?) and presented at international top conferences. He is also co-author of the book Credit Risk Management: Basic Concepts, published in 2008. He regularly tutors, advices and provides consulting support to international firms with respect to their data mining, predictive analytics, and credit risk management policy.
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Chakib Battioui graduated from the University of Louisville in May 2007 with PhD degree in Applied and Industrial Mathematics with concentration on Data Mining and Applied Statistics. His work was published and presented at many national and international conferences such as M2006, SESUG, MWSUG, ESRI, Pharmasug and SUGI. He was chosen nationwide to win SAS Student Ambassador Award at SUGI31. Chakib has joined Eli Lilly in November 2007 working as a core member for Data Mining Expert Group.
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Michael Berthold After receiving his PhD from Karlsruhe University, Germany, Michael Berthold spent over seven years in the US, among others at Carnegie Mellon University, Intel Corporation, the University of California at Berkeley, and most recently as director of an industrial think tank in South San Francisco. Since August 2003 he holds the Nycomed-Chair for Bioinformatics and information Mining at Konstanz University, Germany where his research focuses on using machine learning methods for the interactive analysis of large information repositories in the Life Sciences. Most of the research results are made available to the public via the open source data mining platform KNIME.

M. Berthold is Past President of the North American Fuzzy Information Processing Society, Associate Editor of several journals and the President-Elect of the IEEE System, Man, and Cybernetics Society. He has been involved in the organization of various conferences, most notably the IDA-series of symposia on Intelligent Data Analysis and the conference series on Computational Life Science. Together with David Hand he co-edited the successful textbook Intelligent Data Analysis: An Introduction which has recently appeared in a completely revised, second edition.
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Tom R. Bohannon Dr. Tom R. Bohannon is an analytical consultant for SAS specializing in applying analytical methods to business problems in higher education. These applications include overseeing construction of data warehouses and applying data mining methods to enrollment management, retention, and fund raising. Before retiring from Baylor University in April of 2007, Bohannon was Director and Assistant Vice President for the Office of Institutional Research and Testing for twenty years. In 2008-2009, he was a visiting professor in statistics at Texas A&M University teaching courses in SAS programming and data mining.

Dr. Bohannon earned a PhD in Statistics from Texas A&M University in 1976 and an MA in Mathematics from Wake Forest University in 1965. He also holds a BS in Mathematics with a Physics Minor from McNeese State University.
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stephen Brobst Stephen Brobst has specialized in the design and construction of high-end data warehouse solutions for more than 20 years. He performed his Masters and PhD work in Computer Science at MIT with research focused on massively parallel processing. He has published numerous books and journal articles in the area of data management. Stephen is on the faculty at TDWI and has taught courses in High Performance Design and Real-Time Data Warehousing since 1996.
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Mark Carmichael Mark Carmichael is Managing Director of Eclipse GB Ltd, part of a pan-European integrated direct marketing communications company. In 2008, he created the Eclipse Alliance - a gathering of globally recognised expertise in various disciplines in direct marketing ? designed to analyse, facilitate, streamline, customize and track communications better and more effectively.

The Eclipse Alliance was an instant success, securing its first two substantial accounts within weeks of its launch. Today, the Alliance is making data work more effectively to the benefit of marketers and their customers to improve overall marketing performance.

By offering a mix of sophisticated analysis techniques, emerging digital technologies (online and off) and advanced creative, the Alliance offers a new platform through which content is delivered to a customer in a manner far more efficient and effective than traditional DM approaches.

The Alliance also offers a sophisticated Marketing Lab, enabling the testing of multiple changes in creative variables to calculate which permutation of factors produces the greatest return on investment.

Mark has successfully started several businesses in direct marketing, advertising and manufacturing in five countries. His direct marketing programs have sold more than 25,000 automotive vehicles internationally, have raised millions for non-profit organisations and have helped countless clients in the retail, financial services and publishing sectors. He is currently conducting research for a future book on technology-enabled integrated direct marketing.

Mark received BSc degrees in Economics and Business from Syracuse University in 1990. In 2005, he received his MBA from Oxford University. He is also currently studying Biblical and Theological Studies at Oxford Univerisity.

He resides in Oxford, England.
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Goutam Chakraborty Dr. Goutam Chakraborty has a B.Tech (Honors) in Mechanical Engineering from Indian Institute of Technology, Kharagpur, a PGCGM from Indian Institute of Management, Calcutta, a M.S in statistics and a Ph. D. in marketing from University of Iowa. He has held managerial positions with a subsidiary of Union Carbide, USA and with a subsidiary of British American Tobacco, UK. He is currently a professor of marketing at Oklahoma State University where he has taught digital business strategy, web-business strategy, electronic commerce and interactive marketing, data mining and CRM applications, data base marketing, new product development, marketing research, and product and pricing management for the past fifteen years. He has presented numerous programs and workshops to executives, educators, and research professionals in U.S., Europe, Singapore, Hong Kong, Dubai, Abu Dhabi, and India. He has won many teaching awards including "Regents Distinguished Teaching Award" at OSU, "Outstanding Direct Marketing Educator Award" given by the Direct Marketing Educational Foundation, New York, Professor of the Year Award at CIMBA Italy, and Great Executive MBA Instructor award at the University of Iowa, Iowa City. His research has been published in many scholarly journals such as Journal of Interactive Marketing, Journal of Advertising Research, Journal of Advertising, Journal of Business Research, Industrial Marketing Management, etc. He has co-authored the book Contemporary Database Marketing. In addition, he serves(d) on the editorial review board of Journal of Business Research and Journal of Academy of Marketing Science. He has chaired the national conference for direct marketing educators for 2004 and 2005. He has also consulted extensively on issues related to developing digital business strategy, building and managing customer relationships, product development, and management and creation of e-business models with companies such as Aetna, Mercruiser, Thrifty Rent-A-car, Berendsen Fluid Power, Globe Life Insurance, Van guard Realtors, etc.
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Gary Class In his work with the wellsfargo.com management team, Gary Class is responsible for strategic business analysis around the online base of financial service customers. He analyzes customer preferences and behaviors to help Wells Fargo respond to customers' banking needs and develop new financial services that can be accessed anytime, anywhere. Key successes include bank-wide adoption of customer-centric cross-sell potential and probability of attrition risk models.

Prior to joining wellsfargo.com, Mr. Class was responsible for distribution planning & analysis throughout the Wells Fargo franchise.

Mr. Class played a lead role in the development of Wells Fargo's innovative branch delivery strategy, including the supermarket banking program and specialized branch formats serving diverse segments such as the affluent retired, college student and small business customer base.

In addition, Mr. Class was responsible for development of branch staffing & scheduling applications as well as branch-based database marketing and lead delivery tools.

Mr. Class received his MBA from Haas School, University of California, Berkeley and his B.A. cum laude from the University of Pennsylvania.
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Mr. Collica received a B.S. degree in electronic engineering from Northern Arizona University in 1982. He has 16 years experience in the semiconductor manufacturing industry working on yield and product and quality engineering. Since 1998 he has been with Compaq and Hewlett-Packard as a Sr. Business Analyst using Data Mining techniques for targeted marketing and customer analytics in the Customer Data & Knowledge Services department. He has developed customer scoring models and models to estimate corporate IT spending for use in tactical and strategic customer and prospect business intelligence. His current interests are in Clustering and Ensemble models, knowledge and data engineering, missing data and imputation, and text mining techniques for use in business intelligence. He has authored and co-authored 11 articles and has written a book on CRM Segmentation and Clustering using SAS Enterprise Miner. Mr. Collica has been a member of the IEEE since 1979.
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Filip Deforce Filip Deforce is a management consultant for Accenture where he works in the CRM service line. His specializations are customer segmentations and predictive modelling. He has over 5 years of experience on projects in the retail, insurance, telecommunications, airline and pharmaceutical industry. In these projects he has used data mining techniques for customer segmentations, churn and cross sell predictions and to optimize sales force effectiveness. He holds a master in commercial engineering from Leuven University (Belgium) and a master of Marketing Analysis from Ghent University (Belgium)
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Barry deVille is an analytical consultant at SAS who specializes in text mining and analytics. He holds a US Patent in the area of text mining algorithms. He has published extensively on decision trees for data mining in both popular and peer-reviewed media and is the author of Decision Trees for Data Mining and Business Intelligence Using SAS Enterprise Miner and Microsoft Data Mining. His recent work on social media has been presented at SAS Global Forum and M2008.

Barry has been a featured guest on DM Review's DM Radio broadcast, providing listeners examples of real world text mining.
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John Elder Dr. John Elder heads a data mining consulting team with offices in Charlottesville, Virginia and Washington DC (www.datamininglab.com). Founded in 1995, Elder Research, Inc. focuses on investment, commercial and security applications of advanced analytics, including stock selection, image recognition, process optimization, text mining, cross-selling, biometrics, drug efficacy, credit scoring, market timing, and fraud detection. John obtained a BS and MEE in Electrical Engineering from Rice University, and a PhD in Systems Engineering from the University of Virginia, where he's an adjunct professor teaching Optimization or Data Mining. Prior to 15 years at ERI, he spent 5 years in aerospace defense consulting, 4 heading research at an investment management firm, and 2 in Rice's Computational & Applied Mathematics department. Dr. Elder has authored innovative data mining tools, is a frequent keynote speaker, and is co-chair of the 2009 Knowledge Discovery and Data Mining conference, in Paris. John's courses on analysis techniques -- taught at dozens of universities, companies, and government labs -- are noted for their clarity and effectiveness. Dr. Elder was honored to serve for 5 years on a panel appointed by the President to guide technology for National Security. His book on Practical Data Mining, with Bob Nisbet and Gary Miner, will appear in May 2009. John is a follower of Christ and the proud father of 5.
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Cheryl Doninger Cheryl Doninger joined SAS in 1986 and is currently a Research and Development Director. As director of a large product-development group, she plays a key role in setting the company's technical direction in scalability, grid and cloud computing. During her career at SAS, she has served as technical lead and manager for software products that are the foundation for SAS' large-scale parallel processing capabilities. As a leading advocate for distributed technologies, Cheryl is a frequent speaker on grid and cloud computing, has served on several conference program committees, and has authored several technical papers on this technology area. She is a member of the Advisory Committee for the Open Grid Forum (OGF) and is an Area Director for the Enterprise Adoption Focus Area.

Cheryl earned a bachelor's degree in Computer Science from Bowling Green State University and a master's degree in Computer Studies from North Carolina State University.
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Marty Ellingsworth Marty Ellingsworth is president of ISO Innovative Analytics (IIA), a unit of ISO focused on advanced predictive modeling tools for the property/casualty insurance industry. Mr. Ellingsworth joined IIA from Full Capture Solutions, Inc., where he was cofounder and executive vice president. He has more than ten years of experience in the property/casualty insurance industry, with a focus on applied analytics and claims. For five years, he served the Fireman's Fund Insurance Company. Mr. Ellingsworth's 24-year career also includes positions at RiskData/HNC Software, Workers Compensation Research Institute, Beech Street Managed Care, and the U.S. Air Force. He received his bachelor of science degree in operations research from the United States Air Force Academy and his master of science degree in operations research from the Air Force Institute of Technology.

IIA is devoted to developing innovative decision-support tools based on predictive modeling and scoring. Drawing on ISO's vast resources and expertise in actuarial science, data management and integration, statistical modeling, and information technology, IIA delivers leading-edge analytic tools that reflect ISO's broad experience and deep understanding of risk. Initial product offerings include ISO Risk Analyzer Personal Auto, a predictive model that helps insurers more accurately classify, segment, and price their personal auto risks, and ISO Risk Analyzer Homeowners, a perils-based risk-assessment and evaluation model that will help insurers identify prospects more closely aligned with their business strategies.
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Nick Evangelopoulos Nick Evangelopoulos (Ph.D., Washington State University) is an Associate Professor with the Department of Information Technology and Decision Sciences at the University of North Texas. Dr. Evangelopoulos research interests include Probabilistic Modeling, Applied Statistics, and analysis of Textual Data. Dr. Evangelopoulos has published a number of research articles that appear in prominent journals and national or international conference proceedings. His articles appear in MIS Quarterly, Communications in Statistics - Simulation & Computation, Computational Statistics & Data Analysis, and other research journals.

Dr. Evangelopoulos has taught a number of courses in Business Statistics, Management Science, Advanced Java and Object-Oriented Programming, and Data Mining. He is currently a member of the Decision Sciences Institute and a Fellow of the Texas Center for Digital Knowledge. He can be contacted at Nick.Evangelopoulos@unt.edu.
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Robert Golan In the early 80's Robert Golan received his BSC in Computer Science from the University of Regina, Saskatchewan, Canada. As a student consultant Robert documented the computer investment procedures used by the Alberta's Heritage Trust Fund while integrating part of the Canadian Securities Course. Ten years later Robert completed his MSC in Computer Science on the topic of Stock Market Analysis utilizing Rough Set Theory (AI). Over that time period Robert worked in many technical positions as a Systems Analyst, Researcher, and Developer in the Finance, High Tech, Energy, and Agriculture Industries. In 1995, Robert started up a company called DBmind Technologies, which specializes in the architecture, design, and development of Web Services (SOA) Rules based Data Warehouses and Meta Data Repositories with a BI and Data Mining theme. He has a number of AI publications on Data Mining and Visualization. Algol Trading and RuleML with focus on AI integration mechanisms are his latest challenges. At RuleML 2009/Businss Rules Forum, Robert is the Cross Industry Standards Track Chair. Robert is also the 2009 Technical Chair for Computational Finance and Economics for the IEEE Computational Intelligence Society.
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Viterbo H. Berberena González Viterbo H. Berberena González, Ph.D., is a Professor of Analytics at Universidad Anahuac in Mexico. He graduated in Chemical Engineering from Universidad Central de Las Villas in 1985, and specialized in advanced analytic methods at Mendeleev Institute, in Moscow, in 1989. Given his great passion for the analytics area, he pursued graduate studies in Process Analysis, obtaining his Ph.D. with honors in 1991. He has taught classes at Universidad Central de Las Villas (UCLV), Instituto Politécnico Nacional (IPN), Instituto Tecnológico y de Estudios Superiores de Monterrey (ITESM), Universidad Iberoamericana (UI), Instituto Tecnológico Autónomo de México (ITAM), both at the graduate and undergraduate levels. Dr. Berberena has pioneered the Master in Analytical Intelligence program at Universidad Anahuac, and has also vastly reengineered the graduate programs for the Management Center in Engineering and Technology at that institution. He has published extensively in the areas of marketing analytics and data mining at Segmento and Datos, Diagnósticos y Tendencias, both journals published by ITAM and the Mexican Association of Research Agencies (AMAI) respectively. He has collaborated with SAS Institute Mexico since 2000 and leads many data mining projects for companies in the financial, telecommunications, retail and others industries in Mexico. Currently he serves as a Senior Consultant on Analytics for Banco Santander (Mexico) in the areas of analytical marketing, credit card risk and marketing intelligence. He presented as a session speaker at 11th annual Data Mining Conference (M2008, Las Vegas) on the topic Modeling and Optimization Marketing Campaigns.

Dr. Berberena is one of most important academics in Mexico in promoting the "Competing on Analytics" framework with both academia and business community.
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Dr. Vincent Granville Dr. Vincent Granville has successfully solved problems for 15 years in data mining, text mining, predictive modeling, business intelligence, technical analysis, keyword and web analytics. Vincent is widely recognized as the leading expert in click scoring and web traffic optimization. Over the last ten years, he has worked in real-time credit card fraud detection with Visa, advertising mix optimization with CNET, A/B testing with LowerMyBills, online user experience with Wells Fargo, query intelligence with InfoSpace, click fraud detection with major search engines and large advertising clients.

Vincent was formerly Chief Science Officer at Authenticlick, where he developed patent pending technology. In the last few years, he successfully launched DataShaping, AnalyticBridge, AnalyticBrain, AnalyticTalent, Frenchlane and many other websites. Vincent is a former post-doctorate of Cambridge University and University of North Carolina at Chapel Hill. He was among the finalists at the Wharton School Business Plan Competition and at the Belgian Mathematical Olympiads.

Watch Vincent's Webinar, Predictive Keyword Scores to Optimize Online Advertising Campaigns.
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Involved in data mining since 1995, for the past eight years Dudley Gwaltney has been with Modeling Analytics in the Customer Information Group of SunTrust Bank, a top 10 financial institution.

With a background on both the consulting and client side, Dudley has extensive experience in a wide array of data mining areas, including predictive modeling, segmentation, program analysis, design, implementation and maintenance of data marts, and software development. The majority of his career has been focused on the financial services industry.

Using data mining and statistical analysis, Dudley works with SunTrust's Marketing and Product Management departments to improve overall performance by enhancing existing programs and creating new ones.

Dudley currently serves on the Industry Advisory Board for the Institute for Advanced Analytics at North Carolina State University. He received degrees from North Carolina State in Business Management, Economics, and Computer Science.
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Guillermo Híjar Guillermo Híjar, M. Sc., is a Professor of Strategic Planning at Universidad Anahuac in Mexico. He graduated in Mechanical Engineering from Universidad Anáhuac in 1976, and obtained his Masters' Degree in Mechanical Engineering from the Massachusetts Institute of Technology in 1979. Throughout the first twelve years of his professional career he worked for a large industrial group in Mexico City first, as the Strategic Planning Director and afterwards as the General Manager of Quimic, a chemical company. Later he held a position as General Manager of New Balance de Mexico, a footwear manufacturer. Afterwards, he worked for another twelve years for Mine Safety Appliances Company, a global supplier of industrial safety equipment, as the Managing Director of its subsidiary in Mexico. Five years ago he retired from the industry to fulfill his true passion: to work in the academic environment and to write text books. He is about to publish his first book in strategic planning, Foresight; and he is preparing the second one, Insight. His books are about promoting analytic and systemic tools in the business environment for improving decision making. Professor Híjar patented a devise to simulate the behavior of various financial indices and ratios.
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Zainab Jamal Zainab Jamal joined HP Labs (Business Optimization Lab) as a research scientist in 2007 after completing her Phd in Marketing Science from UCLA Anderson Business School. Her area of research at UCLA was in empirical marketing modeling and looked at developing models to improve the diagnosis and prediction of customer retention (customer churn) rates at an individual level and to establish the empirical impact of different factors in the context of the customer-firm relationship. Her broader research interests are in the understanding of customer relationship management (customer retention, customer churn, customer acquisition, customer lifetime value), modeling customer behavior on the internet and other interactive media and not-for-profit marketing. She has used discrete choice modeling, survival/hazard modeling and econometric modeling frameworks in her research. Prior to joining the PhD program at UCLA she worked for nearly 4 years in brands and product development for companies in India (GlaxoSmithKlineBeecham, go4i.com and CRY - Child Relief and You) after completing her MBA from Indian Institute of Management at Ahmedabad (IIMA) and Masters in Economics from Delhi School of Economics (Delhi University).
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Meredith John Dr. Meredith John, SAS Advanced Analytics product manager for forecasting and econometrics, is responsible for shaping the future strategic direction of the SAS Analytics Forecasting Technologies program.

Before joining SAS, John spent 12 years with HP as a senior statistician and systems strategist. Prior to joining HP, she held faculty positions at Stanford University, Princeton University, and the University of California at Berkeley, and is the author of numerous journal articles and books on a wide variety of subjects ranging from quantitative economic history to mathematical population biology.

John earned a Ph.D. in Economics from Princeton University, where she was also post-doctoral fellow in mathematical demography. She earned a Bachelor of Science degree in Chemistry from the University of Texas at Austin, as well as a Bachelor of Arts degree in Philosophy, Politics and Economics as a Rhodes Scholar at Oxford University.
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Ronald K. Klimberg, Ph.D. is a Professor in the Decision and System Sciences Department of the Haub School of Business at Saint Joseph's University, USA. Professor Klimberg received his B.S. in Information Systems from the University of Maryland, his M.S. in Operations Research from George Washington University, and his Ph.D. in Systems Analysis and Economics for Public Decision-Making from the Johns Hopkins University. Before joining the faculty of Saint Joseph=s University in 1997, he was a professor at Boston University (10 years), an operations research analyst for the Food and Drug Administration (FDA) (10 years) and a consultant (7 years). Ron was the 2007 recipient of the Tengelmann Award for his excellence in scholarship, teaching, and research.

His research has been directed toward the development and application of quantitative methods, e.g., statistics, forecasting, data mining, and management science techniques, such that the results add value to the organization and the results are effectively communicated. Dr. Klimberg has published over 30 articles and made over 30 presentations at national and international conferences in the areas of management science, information systems, statistics, and operations management. His current major interests include multiple criteria decision making (MCDM), multiple objective linear programming (MOLP), data envelopment analysis (DEA), facility location, data visualization, data mining, risk analysis, workforce scheduling, and modeling in general. He is currently a member of INFORMS, DSI, and MCDM.
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Manfred Krafft Manfred Krafft is respected as a scholar with special interests in Customer Relationship Management (CRM), Direct Marketing, and Sales Management. He is known for his applied research that had an impact on both science and practice. His work has won prestigious prizes such as the INFORMS Society for Marketing Science Practice Prize, and was finalist in the Franz Edelman Award. His paper on financial effects of CRM is currently the most heavily cited paper in Journal of Marketing Research.

Manfred holds the Marketing Chair at the University of Münster, considered to be Germany's premier research university, and Visiting Professorships at Università Bocconi in Milan, Italy and Loughborough University, England. He enjoys an international reputation for his award-winning research that has been published in leading journals in Marketing such as Journal of Marketing, Journal of Marketing Research and Marketing Science. In his research, Manfred collaborates with scholars from around the world. He received his doctoral degree in business administration and holds an MSc and BSc in business and economics.

Manfred shares his insights with executives, scholars and students in university programs as well as at conferences in Europe and around the world. Manfred has developed executive programs for 3M and Metro Group, and gives advice to companies such as Bertelsmann, Daimler, Deutsche Bahn, Deutsche Post, GfK, Johnson & Johnson, Lufthansa, and TNS Infratest. His books on "International Direct Marketing" and "Retailing in the 21st Century" have appeared in French, English, German, Korean and Russian (forthcoming).
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Dr. Hye-Chung Kum Dr. Hye-Chung Kum is a research assistant professor at the department of Computer Science and the School of Social Work at the University of North Carolina at Chapel Hill (UNC-CH). She received her MS and PhD in Computer Science from UNC-CH. In her PhD program, she also minored in Social Work and completed her MSW from UNC-CH. She has done extensive research on sequential pattern mining, data mining, digital government, and the use of KDD technology on administrative data from social welfare for program evaluation and policy analysis. Her findings have been published in well-known international journals (e.g. Data Mining and Knowledge Discovery, Data and Knowledge Engineering, Information Sciences, Government Information Quarterly, Child Maltreatment) and presented at international conferences (e.g. SIAM International Conference on Data Mining, PAKDD, ACM International Conference on Digital Government Research, Foundations of Data Mining and Knowledge Discovery, The National Child Welfare Data and Technology Conference, The National Association for Welfare Research and Statistics Workshop and Conference) both in the field of computer science and social work. Her work in sequential pattern mining has also been published as a chapter in the book Mining Sequential Patterns from Large Data Sets Series: The Kluwer International Series on Advances in Database Systems, Vol. 28. She is a member of the program committee for the ACM International Conference on Digital Government Research and a regular reviewer for international journals such as Data and Knowledge Engineering, Knowledge and Information Systems, IEEE Transactions on Knowledge and Data Engineering, and Information Sciences.
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Choudur K. Lakshminarayan Choudur K. Lakshminarayan is a research staff member in the Intelligent Information Management Lab at HP laboratories in Palo Alto, focused on problems related to data mining, data compression, and analysis of structured and unstructured data. He works in a variety of areas including information management, Information extraction, web mining and analytics, marketing optimization, semiconductor manufacturing and research, customer relationship management and others. He conducted the popular Business Knowledge Series (BKS) seminars sponsored by the SAS Institute around the world in India, Hong Kong, and China. He holds a Ph.D. in Mathematical Sciences and lives in Austin, Texas.
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Kim Larsen Kim Larsen is a Director in the Advanced Analytics group at Charles Schwab & Co., in San Francisco. The Advanced Analytics team works directly with partners in marketing, finance, and product management to solve business problems through statistical analysis and optimize the impact of business levers.

He has more than eight years of experience in data mining and statistical modeling in the financial services industry. Throughout his professional career he has worked on a wide array of data mining problems including customer segmentation, forecasting, price optimization and predictive modeling for various applications.

Kim holds a BS in mathematics and economics and an MS in statistics.
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Dr. LaViolette Dr. LaViolette received the Ph.D. in Chemistry from the University of California, Berkeley in 1984, after receiving the B.A. in Chemistry-Mathematics from Reed College in 1979. Following a postdoctoral appointment at Bell Laboratories (Murray Hill, 1984-1986), he joined the technical staff at the Rockwell International Science Center in 1986. He joined the Idaho National Laboratory in 1991 as Technical Leader of the Theoretical Chemistry Project and led research in theoretical chemistry, molecular modeling of materials, surfaces, and clusters, fate and transport of contaminants in the subsurface, and alternative automotive fuels. He joined Sandia National Laboratories (NM) in 2005, where he has begun to apply results from "network physics" to studies of infrastructure resiliency. He has more than 50 peer-reviewed articles published in peer-reviewed journals or proceedings.
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Carl Lee Carl Lee received his Ph.D. in Statistics from Iowa State University in 1984. Currently, he is a professor of Statistics and the Director of the Graduate Certificate Program in Data Mining at Central Michigan University, and serves as a senior research fellow for the Business Intelligence Group at Central Michigan University Research Cooperation. He has over 25 years of consulting experience in both academic and business environments. He is a Fellow of the American Statistical Association, an elected member of International Statistics Institute, and a Dow Chemical Company's certified Sigma Black Belt.
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Bruce Lund Dr. Bruce Lund has an extensive background as an automotive industry practitioner of database development and database marketing, including the strategic utilization of data mining for marketing applications. In 2002 Bruce became the Manager of Database Marketing for Marketing Associates LLC, a marketing, risk management, and technology company headquartered in Detroit. He retired in 2007 to start an independent database marketing consultancy, working primarily at Ford Motor Company on behalf of Marketing Associates.

Before joining Marketing Associates in 2002, Bruce worked at Ford Motor Co. for 22 years and served as a driving force in the development of Ford's customer database and database marketing applications. Prior to that, he was an associate professor of mathematics and statistics at the University of New Brunswick, Canada. Bruce received a BS in Mathematics from the University of Illinois and a PhD in Mathematics from Stanford University.
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Riku Mäkeläinen Riku Mäkeläinen, Senior Dataminer, Broadband Strategy & Portfolio, is responsible for data mining activities with TeliaSonera Sverige AB. He has worked with customer intelligence and data mining projects including dm-tool evaluation, dm-tool implementation, database administration, predictive modeling, and evaluation of data mining methods with both TeliaSonera Sweden and TeliaSonera Finland. Riku Mäkeläinen has M. Sc in mathematics from University of Turku.
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Dr. Colleen McCue Dr. Colleen McCue, President & CEO of MC2 Solutions, brings over 18 years of experience in advanced analytics and the development of actionable solutions to complex information processing problems in the applied public safety and national security environment. Dr. McCue's areas of expertise include the application of data mining and predictive analytics to the analysis of crime and intelligence data, with particular emphasis on deployment strategies, surveillance detection, threat and vulnerability assessment and the behavioral analysis of violent crime. Her experience as the Crime Analysis Program Manager for the Richmond, Virginia Police Department and pioneering work in operationally relevant and actionable analytical strategies has been used to support a wide array of national security and public safety clients. Dr. McCue has authored a book on the use of advanced analytics in the applied public safety environment entitled, "Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis." Dr. McCue earned her undergraduate degree from the University of Illinois at Chicago and Doctorate in Psychology from Dartmouth College, and completed a five-year postdoctoral fellowship in the Department of Pharmacology & Toxicology at the Medical College of Virginia, Virginia Commonwealth University. Dr. McCue can be reached at colleen@mc2solutions.net or 804.894.1154.

MC2 Solutions, LLC specializes in the provision of public safety and national security research, analysis and training.

Watch Colleen's Webinar, Why Just Count Crime When You Can Prevent It?
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Robert Moberg Customer Insight Manager at the telecom operator 3 in Sweden. Robert Moberg is working together with co-speaker Mattias Andersson at the Loyalty Management Department with the target to increase loyalty and customer value. The retention strategy, as well as cross and up-sell processes are examples on Robert and Mattias' successful work with DataMining and advanced statistical analysis. Robert has been working with analytics and analytical CRM since the 90's at SPSS, SAS, Carat and currently at 3. Robert has a B Sc. Degree in statistics from Linköping University.
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Will Neafsey Mr. Neafsey is the Brand DNA and Consumer Segmentation Manager for Ford Motor Company. During his last 16 years with Ford, he has worked in Market Research, New Business Creation and Incubation, Information Technology, Operations Research, Manufacturing, and at Ford Financial. He holds a Bachelors and Masters Degree in Operations Research from Cornell University, as well as an MBA from Cornell's Johnson School.
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Jerry Oglesby Jerry L. Oglesby holds a Ph.D. in Statistics from Texas A&M University, an M.S. in Mathematics from Lamar University, and a B.S. in Mathematics from the University of Mississippi. He currently works for SAS as the Director of Higher Education Consulting and Global Certification within the Education Division. This department is charged with supporting SAS in the university wide community. It has, as its major goal, the introduction of SAS training materials and software in the curriculums of courses across many units within the universities. Prior to starting this group, he was Director of Analytical Consulting within the Professional Services Division. As Director of Analytical Consulting he grew the Department from its formation to approximately forty modelers and business analysts whose primary function was to provide analytical support and expertise to SAS' sales force and customers. This group was largely responsible for the support of the successful launch of SAS' award winning data mining solution, Enterprise Miner.

From 1990 until joining SAS in July of 1996, Jerry was employed by Monsanto Chemical Company as plant statistician and Manufacturing Technologist. He was CEO and founding President of SCI Data Systems from 1977 to 1990. Following completion of his doctorate at Texas A&M in 1971, he was a professor of Statistics at the University of West Florida where he established the Institute for Statistical and Mathematical Modeling for doing analytical and computational consulting for clients on and off campus.

Jerry serves on several advisory boards in support of statistics and data mining:
  • Data Mining Advisory Board, College of Arts & Sciences, University of Central Florida
  • Central Michigan University Research Corporation, Center for Applied Research & Technology, Central Michigan University
  • Center for the Management of Information Systems, Department of Information & Operations Management, Mays Business School, Texas A&M University
  • Master of Marketing Research Program, Coca-Cola Center for Marketing Studies, Terry College of Business, University of Georgia
  • Institute of Business Intelligence, Department of Information Systems, Statistics, and Management Science, Culverhouse College of Commerce and Business Administration, The University of Alabama
  • Department of Statistics & Operations Technology, Daniels College of Business, University of Denver
  • Industry Advisory Committee, North Carolina Community College System
  • Information Technology Advisory Committee, Pennsylvania College of Technology
  • Computer Information Systems Division Advisory Board, Wake Technical Community College
  • Decision Sciences & Center for Quality & Productivity Advisory Board, Business Computer Information System, College of Business Administration, University of North Texas
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Anita Prinzie Anita Prinzie is a post doctoral researcher in Economics and Business Administration at Manchester Business School, University of Manchester, UK. She is a visiting Professor at Ghent University, Belgium, from which she received her Masters degree in Marketing Analysis and Planning as well as her PhD. Her PhD thesis investigated the use of sequence-analysis methods for CRM purposes (churn and cross-sell analysis). She worked as a visiting academic at Monash University, Australia. Her current research interests include 1) testing the external validity of the new Random Multinomial Logit algorithm for choice analysis, 2) understanding and optimising customer decision processes from a marketing-action perspective and 3) assessing the value of sequential information for aCRM models. Her papers have been published in Decision Support Systems (DSS), European Journal of Operational Research (EJOR), Expert Systems with Applications (ESwA), Journal of Intelligent Information Systems (JIIS), Lecture Notes in Computer Science (LNCS) and Lecture Notes in Artificial Intelligence (LNAI).
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Patrick Ryan Patrick Ryan is a Manager of Statistical and Quantitative Sciences at GlaxoSmithKline Research and Development, where he has led several efforts to develop and apply exploratory analysis methods to better understand the effects of medicines. He currently serves as the Co-Investigator of the Observational Medical Outcomes Partnership, where he is conducting methodological research to assess the appropriate use of observational healthcare data to identify and evaluate drug safety issues. OMOP is a public-private partnership managed by the Foundation of the National Institutes of Health and chaired by the Food and Drug Administration. Patrick received his B.S. in Computer Science and Masters of Engineering in Operations Research & Industrial Engineering from Cornell University.
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Sascha Schubert As a member of the SAS Global Technology practice, with a specific focus on Analytics, Sascha Schubert is responsible for the growing the global market share and the strategic development direction of SAS Analytic technologies with a specific focus on data and text mining solutions. He has been involved in many projects involving the application of analytical techniques to address specific business challenges in various industries, including: banking and finance, telecommunications and the public sector.

Schubert supports SAS customers in solving business problems such as: customer attrition and churn, cross-selling, customer segmentation and market basket analysis. Other main areas of his analytical expertise are fraud detection and anti-money laundering. He also provides direction and support to the research and development team to ensure that market requirements are reflected in product development.
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Saratendu Sethi Mr. Sethi, Director of Engineering, manages the software engineering efforts at Teragram. Mr. Sethi holds a Master’s degree in Computer Science from Boston University and a Bachelor’s degree in Computer Science and Engineering from the Indian Institute of Technology, Bombay. Mr. Sethi has extensive experience in software engineering, natural language processing technologies and is an expert in text processing statistical algorithms and techniques. Mr. Sethi manages the research and development of Teragram lines of products including Teragram concepts extraction, categorization, summarization, and syntactic parsing. Previously to joining Teragram, Mr. Sethi held research positions at IBM Almaden research center and Boston University specializing on the use of statistical techniques for a content–based search tool using statistical categorization and feature extraction techniques. He holds several academic honors in mathematics and is the author of many publications in multimedia information retrieval.
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Professor Michael Speed is the Director of Online Learning in the Department of Statistics at Texas A&M University. Mike's research interests are in the fields of linear models and the use of technology in the classroom. As the Associate Dean of Technology Mediated Instruction in the College of Science, he assists the University faculty in improving the learning environment by using technology.

Mike has considerable consulting experience, principally in the application of statistical methods to business, environmental and ecological data. He consults with state and federal agencies as well as individuals and corporations.

In 2006, Mike was named a fellow of the American Statistical Association. He received the Shewell and the Jack Youden awards as well as the H. O. Hartley and the W.S. Connor awards. As a NASA engineer, he received the Sustained Superior Performance Award in 1969.

In addition to the usual service activities to the statistical profession, Mike has been very active in the civic and business community. He has held public offices and has worked on committees at the local, state and national levels. Michael holds a BS and MS degree from St. Mary's University in San Antonio and a Ph. D. from Texas A&M University.
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Judy Spomer Judy Spomer is a Senior Member of Technical Staff at Sandia National Laboratories. At Sandia, she is engaged in text analysis research and has developed models to forecast safety incidents, aid in the development of ergonomics evaluations, and in the area of security. Prior to employment at Sandia, Ms. Spomer worked as a Risk Modeler for American General Finance, developing customer credit scoring models, and behavioral models aimed at reduction of customer delinquency. She has a B.S. in Computer Science from Indiana University of Pennsylvania, and an M.S. in Data Mining from Central Connecticut State University.
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Olivier Thas Olivier Thas is Associate Professor of Biostatistics at Ghent University, Belgium. His research focuses on nonparametric statistics and applications in environmental sciences and genomics. He recently published two books (with Wiley and Springer) on informative nonparametrical methods for comparing distributions. He is co-founder of Stat-Gent CRESCENDO, a knowledge platform that unites statistical expertise at Ghent University and facilitates contract research for government and industry.
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Shusaku Tsumoto Shusaku Tsumoto graduated from Osaka University, School of Medicine in 1989. After a resident of neurology in Chiba University Hospital, He was involved in developing hospital information system in Chiba University Hospital from 1991. He moved to Tokyo Medical University in 1993 and started his research on rough sets and data mining in biomedicine. He received his Ph.D (Computer Science) on application of rough sets to medical data mining from Tokyo Institute of Technology in 1997 and has become a Professor at Department of Medical Informatics, Shimane University in 2000. His interests include approximate reasoning, data mining, fuzzy sets, granular computing, knowledge acquisition, mathematical theory of data mining, medical informatics and rough sets (alphabetical order). He served as President of International Rough Set Society from 2000 to 2005 and served as a PC chair of RSCTC2000, IEEE ICDM2002, RSCTC2004, ISMIS2005 and IEEE GrC2007, as a Conference chair of PAKDD 2008.
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Dirk Van den Poel Dr. Dirk Van den Poel is professor of marketing modeling at the Faculty of Economics and Business Administration of Ghent University, Belgium. He heads a competence center on analytical customer relationship management (aCRM)/customer intelligence/customer data mining. He received his degree of management/business engineer as well as his PhD from K.U.Leuven (Belgium). His main interest fields are the quantitative analysis of consumer behavior (CRM), data mining (genetic algorithms, neural networks, random forests, random multinomial logit: RMNL), text mining, optimal marketing resource allocation (DIMAROPT) and operations research. He published more than 30 articles in academic peer-reviewed journals including Information & Management, Decision Support Systems, Journal of Business Research, European Journal of Operational Research, Journal of the Operational Research Society, International Journal of Intelligent Systems and Expert Systems with Applications.

He is a 20+ years SAS user, and has been teaching SAS for the past 10 years in the Master of Marketing Analysis. He has given more than 100+ talks at academic conferences as well as business conferences all over the world.
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Maarten Verschuere For the past two and a half years, Maarten Verschuere has been working at dunnhumby as an Insight Analyst. Currently, he work in the Tesco Trade team where he is responsible for reporting weekly Trade in Tesco and investigating the specific impact key trade drivers (promotion, direct mailing, ?) have on the Tesco customer. Before that, he worked for various CPG manufacturers on a range of projects including segmentation, range optimization, customer switching behavior and media mix optimization. Prior to his marketing career, he spent two years in Supply Chain Management working as a Vendor and Production planner for Tyco Electronics. He holds a Masters degree in Applied Economics (KULeuven, 2004) and Marketing Analysis (Ghent University, 2007). In February 2009 he obtained the SAS Base and SAS Advanced Professional Certification.
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Donald Wedding Donald Wedding, Ph.D. is employed as a Systems Engineer for SAS working in financial services. Before joining SAS, he has worked as both a software engineer in the defense industry and as a data miner in the financial services industry (banking, insurance, and capital markets). He holds a Ph.D. in Engineering from the University of Toledo where he studied software engineering, machine learning, and statistics. Dr. Wedding also holds an M.S. in Management from the University of Akron and an M.S. in Data Mining from Central Connecticut State University.
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Terry Whitlock is an employee of BlueCross BlueShield of Tennessee. He has more than 15 years of analytical experience in managed care. He has utilized SAS for nearly 13 of his 15 years over a wide variety of research in the field of managed care. Over his career he has been published in Managed Care Interface and presented research at Best of Blues as well as Academy Health Research.
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Terry Woodfield Terry Woodfield is a Statistical Services Specialist in the Education Division of SAS Institute, Inc. and served as co-chair for M2003, SAS' 6th annual data mining conference. Dr. Woodfield has more than 29 years of SAS programming experience and has provided training and mentoring services in the areas of statistical forecasting, predictive modeling, and data mining. At SAS, Dr. Woodfield has developed courses in statistical forecasting, Web mining, and text mining. He is also active in the statistics profession, presenting papers at numerous statistical conferences and professional meetings, and he has served on steering committees in data mining and forecasting. He has helped develop forecasting and predictive modeling solutions for insurance, energy, and retail companies and been an expert witness in utility ratemaking hearings. Before joining SAS, Dr. Woodfield was Chief Statistician at HNC Software and other prior experience includes statistical software development in SAS/ETS Research and Development and university teaching and research.
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Katsutoshi Yada Katsutoshi Yada is Professor of Management Information Systems in the Faculty of Commerce, Kansai University, Osaka, Japan. He was previously an Assistant Professor in the Department of Business Administration, Osaka Industrial University, Osaka, Japan, from 1997 to 2000. He received his M.A. and Ph.D. in Business Administration from Kobe University of Commerce, Hyogo, Japan, in 1994 and 2002, respectively. He was a visiting scholar of School of business at Columbia University from 2006 to 2007. He is currently the director of Program on "Data Mining and Service Science for Innovation" at Kansai University, supported by MEXT. His present research interests include data mining for marketing, and information strategy concerning data mining. His papers have appeared in several journals, including Data Mining and Knowledge Discovery, Soft Computing, Decision Support Systems and others. He had been a guest editor of special issues in Information Science. He has been chairman and member of various program committee in many international data mining conferences and workshops, including TC chair of IEEE SMC, ICDM and others. He is a member of IEEE, AMA and AMS.
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Jun Yan Mr. Yan is a specialist leader in the Advanced Quantitative Service (AQS) Group of Deloitte Consulting LLP. Mr. Yan has more than 15 years experience in Property and Casualty insurance industry. He joined Deloitte Consulting in January, 2005.

After joined Deloitte, Mr. Yan, as one of the leading modelers in AQS of Deloitte, developed sequence of predictive models for various commercial lines and personal lines of business.

Before joining Deloitte, Mr. Yan was a Sr. Research Consultant in Hartford Insurance Group (HIG) for more than seven years. His experience in HIG was developing class plan for personal auto and homeowners, credit scoring, growth and profitability projection, and claim level loss development. He also received numerous awards and nominations for his contributions to The Hartford's business.

Mr. Yan is a frequent speaker in Casualty Actuarial Society (CAS)'s seminars and conferences. He is a co-instructor of CAS Limited Attendance Predictive Modeling Seminar from 2006 to 2009.

Mr. Yan holds a Ph.D. in Statistics from Indiana University in Bloomington, Indiana.
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