Business Knowledge Series Instructors
Bart Baesens, Ph.D., is an assistant professor at K.U.Leuven (Belgium), and a lecturer at the University of Southampton (United Kingdom). Bart has done extensive research on predictive analytics, data mining, customer relationship management, Web analytics, fraud detection, and credit risk management. His findings have been published in international journals such as the Machine Learning Journal, the Management Science Journal, IEEE Transactions on Neural Networks, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Evolutionary Computation, and the Journal of Machine Learning Research. Bart has presented at numerous international conferences, and he is also co-author of the book Credit Risk Management: Basic Concepts, which was published in 2008. Bart regularly tutors, advises, and provides consulting support to international firms on data mining, predictive analytics, and credit risk management policy.
For more information, see www.dataminingapps.com; Twitter: DataMiningApps; and Facebook: Data Mining with Bart.
Mark Bailey, Analytical Training Consultant, initially began computing on mainframes, but expanded his academic accomplishments in graduate school at the University of Rochester studying hemoglobin action in blood. He learned how to program the entire laboratory computer for real-time data acquisition and data reduction. Most of his computing now is in JMP, SAS, Smalltalk or StarLogo on Windows and Macintosh. Bailey's teaching focus is primarily in the JMP curriculum: design of experiments and scripting.
Patricia Berglund is a senior research associate in the Survey Methodology Program at the Institute for Social Research at the University of Michigan. She has extensive experience in the use of SAS and related computing systems for data analysis and data management. She is currently working in the mental health field using data from the National Comorbidity Surveys, World Mental Health Surveys, and various other national and international surveys. In addition, she is involved in development, implementation, and teaching of analysis courses and SAS training programs at the Survey Research Center/ISR. Patricia holds a B.A. and an MBA from Northwestern University in Chicago, Illinois.
Dr. Oral Capps, Jr. is a demand and price analyst, with particular expertise in econometric modeling and forecasting methods. Dr. Capps is a nationally and internationally recognized leader in demand analysis, specializing in working with large data bases. Applied research areas include analyses of expenditure patterns of preprepared foods and foods eaten away from home, analyses of health and nutrition issues, uses of scanner-derived information for managerial decision-making in food retailing, and analyses of regional, national, and international markets for the agricultural, agribusiness and financial sectors. In addition, he specializes in unilateral price effects of mergers and acquisitions as well as evaluations of agricultural checkoff programs.
Currently Dr. Capps is a full professor and holder of the Southwest Dairy Marketing Endowed Chair in the Department of Agricultural Economics at Texas A&M University as well as co-director of the Agribusiness, Food, and Consumer Economics Research Center (AFCERC). He also is founder and managing partner of Forecasting and Business Analytics, LLC, an economic consulting firm. Dr. Capps was educated at Virginia Tech, where he earned a B.S. in Mathematics, an M.S. in Agricultural Economics, an M.S. in Statistics, and a Ph.D. in Agricultural Economics. He has authored 115 refereed journal articles, and co-authored four books: Food Demand Analysis: Implications for Future Consumption; Introduction to Agricultural Economics, Fifth Edition; Economic Impact of Country-of-Origin Labeling on the U.S. Beef Industry; and Changes in the Sheep Industry in the United States: Making the Transition from Tradition. Another book, A Step-by-Step Approach to Economic Modeling and Forecasting, is forthcoming.
Dr. Capps is a survivor of the San Francisco earthquake on October 17, 1989, and the New York City World Trade Center attack on September 11, 2001. His areas of special interest include econometrics, market analysis for agricultural commodities, applied statistics, and major league baseball.
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, an M.S. in statistics and a Ph. D. in marketing from the 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 a professor of marketing at Oklahoma State University, where he has taught data mining and CRM applications, advanced data mining, database marketing, new product development, marketing research, digital business strategy, Web-business strategy, electronic commerce, and interactive marketing and product and pricing management for the past 20 years. Goutam has presented numerous programs and workshops to executives, educators, and research professionals in the U.S., Europe, Singapore, Hong Kong, Dubai, Abu Dhabi, and India. He has won many teaching awards including Regents Distinguished Teaching Award, Richard. W. Poole Faculty Outreach Excellence Award, Kenneth D. and Leitner Greiner Teaching Award and Wendell H. Bailey Faculty Excellence Award at OSU; Outstanding Direct Marketing Educator Award, from the Direct Marketing Educational Foundation, New York; Professor of the Year Award at CIMBA Italy; Great Executive MBA Instructor Award at the University of Iowa, Iowa City; Outstanding Marketing Teacher Award, from the Academy of Marketing Science, Coral Gables, Florida; and Excellence in Teaching and Faculty Service award from UPCEA central region, St. Louis, Missouri.
Goutam's 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, and Industrial Marketing Management. He coauthored the book Contemporary Database Marketing. In addition, Goutam has served 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 in 2004 and 2005 and co-chaired the M2007 data mining conference. Goutam 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, Vanguard Realtors, Hilti, Love's Travel Stops, etc. He is the founder of the SAS and OSU Data Mining Certificate program as well as SAS and OSU Business Analytics Certificate program at Oklahoma State University.
Peter Christie provides customer training and mentoring as well as course development services. He brings experience from working as a SAS Consultant, Product Manager, Technical Services Manager and musician to his current position as Senior Analytical Training Consultant. Some of his areas of interest include data mining, predictive modeling, forecasting, and risk management.
Prior to SAS, Christie worked in the retail, banking, entertainment, chemical, and pharmaceutical industries. He holds an MBA with a concentration in information technology from the University of North Carolina at Chapel Hill.
Ron Cody, Ed.D., is a retired professor from the Robert Wood Johnson Medical School who now works as a private consultant and a national instructor for SAS. A SAS user since 1977, Ron's extensive knowledge and innovative style have made him a popular presenter at local, regional, and national SAS conferences. He has authored or co-authored numerous books, such as Learning SAS by Example: A Programmer's Guide; SAS Programming by Example; Applied Statistics and the SAS Programming Language, Fifth Edition; The SAS Workbook; The SAS Workbook Solutions; Cody's Data Cleaning Techniques Using SAS Software; Longitudinal Data and SAS: A Programmer's Guide; and SAS Functions by Example, as well as countless articles in medical and scientific journals.
Chris Daman is an Analytical Training Consultant and course developer in the Education Division at SAS. She has more than 20 years of teaching experience, both nationally and internationally, in the fields of programming, statistics, and mathematics. She was introduced to SAS during her graduate program at N.C. State University and has used it extensively since then. She has taught classes at N.C. State University, worked in the pharmaceutical and financial industries, and she most recently worked with a major research organization as a survey statistician before joining SAS in 2005. She currently teaches courses covering design of experiments and analysis of complex data, such as longitudinal data, multilevel data, or data from complex surveys. She has a bachelor's degree in mathematics from the University of North Carolina at Greensboro and a master's degree in statistics from N.C. State University.
Chris's favorite part of teaching is the interaction with the students. To keep them involved with the material and each other, she often uses a variety of teaching techniques rather than the standard instructor-to-student lecture format. She enjoys watching a group of individuals come together over three days as they journey through statistical material. As a result, students give high ratings to her classes with such comments as "I enjoyed Chris's teaching style very much. She did an excellent job of engaging the class and fostering interactions between all the students and herself." or "I love Chris's sense of humor. It definitely helps you get through complicated material."
In her spare time, Chris enjoys dancing, reading, spending time with her family, and traveling.
David Dickey is currently a professor in the Department of Statistics at North Carolina State University. He has a master's degree in Math from Miami University in Oxford, Ohio, and a Ph.D. in Statistics from Iowa State University. His research focuses on time series analysis, dealing with data taken over time. In addition to writing four books, Dr. Dickey has been published in numerous papers and has given over 50 presentations at a variety of professional events and organizations. He has also been recognized as a member of the Academy of Outstanding Teachers at North Carolina State University.
Craig Dickstein, an independent Consultant, works with clients and select project teams to implement customized business solutions for the healthcare industry. He has significant past experience managing and developing SAS applications and has been a SAS user since 1978. With a Masters Degree in Statistics and meaningful work experience in medical research, health insurance, and national catalogue sales, he brings benefit by resolving specific client business needs. Craig has a long history of SAS user group involvement as both an organizer and invited speaker. John F. Elder IV, Ph.D., heads Elder Research, Inc. (ERI), a leading data mining consulting firm, with offices in Charlottesville, VA, and Washington, DC. Since 1995, ERI has focused on applying advanced analytics to achieve high ROI for investment, commercial, and security clients in fields from text mining and stock selection, to credit scoring and fraud detection. John holds engineering degrees from Rice and the University of Virginia, where he is an adjunct professor. He has created innovative software tools, is a frequent keynote speaker, and chairs international analytics conferences. Appointed by President George W. Bush, John served five years on a panel to guide technology for national security. He co-authored Handbook of Statistical Analysis and Data Mining Applications, which won the PROSE award for the best mathematics book of 2009, and also co-authored books on ensemble modeling and practical text mining.
Elder obtained a BS and MEE in electrical engineering from Rice University and a PhD in systems engineering from the University of Virginia, where he teaches optimization and data mining. Prior to his 15 years at ERI, he spent five years in aerospace defense consulting, four years heading research at an investment management firm, and two years in Rice University's Computational and Applied Mathematics Department.
Elder has authored innovative data mining tools, is a frequent keynote speaker and was co-chair of the 2009 Knowledge Discovery and Data Mining conference in Paris. His courses on analysis techniques taught at dozens of universities, companies and government labs are noted for their clarity and effectiveness. Elder was honored to serve for five years on a US presidential panel to guide technology for national security. His book with Bob Nisbet and Gary Miner, Handbook of Statistical Analysis & Data Mining Applications, won the PROSE award for Mathematics in 2009. His book with Giovanni Seni, Ensemble Methods in Data Mining: Improving Accuracy through Combining Predictions, was published in February 2010. His book on Practical Text Mining - with Drs. Miner, Delen, Fast, Hill, and Nisbet - was published in January 2012.
Howard Friedman works as a statistician and health economist for the United Nations, currently focused on the areas of maternal and newborn child health, health expenditures, and fertility at UNFPA. He has been a lead modeler on a number of key United Nations projects including the ICPD @ 15 Costing, High Level Task Force on Innovative Financing, and the Adding It Up reports. He is credited with being the lead developer of the tool used for costing the Health-related Millennium Development Goals within UNDP.
Prior to joining the United Nations, Friedman ran Analytic Solutions LLC which provides consulting services in areas of designing, developing and modeling data. This work also included teaching taught data mining and modeling techniques for major international corporations and foreign governments. Before owning Analytic Solutions, LLC, he was a director at Capital One where he led teams of statisticians, analysts and programmers in various areas of operations and marketing.
Howard is the author of over 35 scientific articles and book chapters in areas of applied statistics, health economics where recent publications have appeared in the American Journal of Gastroenterology, Current Medical Research & Opinion, Clinical Therapeutics, Inflammatory Bowel Disease, Journal of Managed Care Pharmacy, Clinical Drug Investigation and Value in Health.
Howard Friedman received his BS from Binghamton University in Applied Physics. He receives a Masters in Statistics and Ph.D. in Biomedical Engineering from Johns Hopkins University.
Michael Gilliland is Product Marketing Manager for SAS forecasting software, and author of The Business Forecasting Deal. He has over 20 years of forecasting experience in the food, apparel, and consumer electronics industries, and as a consultant. Mike wrote a quarterly column on "Worst Practices in Business Forecasting" for Supply Chain Forecasting Digest, and has published articles in Supply Chain Management Review (where he introduced Forecast Value Added analysis in 2002), Foresight: The International Journal of Applied Forecasting, Journal of Business Forecasting, Analytics, and APICS magazine. Mike holds a BA in Philosophy from Michigan State University, and Master's degrees in Philosophy and Mathematical Sciences from Johns Hopkins University. You can follow his blog, The Business Forecasting Deal. Mike also blogs monthly for the Institute of Business Forecasting at www.demand-planning.com.
G. Terry Hawkins provides consulting services in the warranty and service contract business and runs a private law practice in Kentucky. He began his professional career as Director for Instructional Communications for the University of Louisville, then moved into the global renewable energy field as President of McDonnell Douglas Energy Systems. Leaving energy for a private law practice, he represented a number of commercial clients, including General Electric. That representation grew into high-level positions in warranty management for GE Consumer and Industrial and Assurant Solutions. Hawkins has a degree in general science from Indiana University and a Juris Doctor from the University of Louisville.
Tao Hong, Ph.D. is an Industry Consultant at SAS, where he leads the forecasting vertical of the utilities business unit. His major areas of expertise are in forecasting and optimization. He has applied various statistical and optimization techniques to the development of algorithms and tools for utility applications of analytics, such as energy forecasting, power system planning, renewable integration, reliability planning and risk management, etc. He has been providing consulting services to numerous large and medium utilities in Americas, EMEA and AP. The long term spatial load forecasting methodology implemented in his MS thesis and the short term forecasting methodology proposed in his PhD dissertation have been commercialized and deployed to many utilities worldwide.
Dr. Hong currently serves as the Founding Chair of the IEEE Working Group on Energy Forecasting, where he leads the efforts of improving the forecasting practice of the utility industry. He has organized, chaired, and participated in many forecasting related sessions in several major conferences sponsored by IEEE Power and Energy Society and INFORMS. He is a reviewer of Fuzzy Optimization and Decision Making and several IEEE Transactions, such as Power Systems, Power Delivery, Sustainable Energy, and Smart Grid.
Dr. Hong is an adjunct instructor at NC State University teaching load forecasting and demand response related topics at both Electrical & Computer Engineering department and the Institute for Advanced Analytics. He is also an instructor at SAS teaching the Business Knowledge Series course "Electric Load Forecasting: Fundamentals and Best Practices."
Dr. Hong received his B.Eng. in Automation from Tsinghua University, Beijing, a M.S. in EE, a M.S. with co-majors in OR and IE, and a Ph.D. with co-majors in OR and EE from North Carolina State University. He is a member of Omega Rho International Honor Society.
Mark Jordan began his computing career on mainframes in 1972 but soon set course for a 20-year career in the US Navy as a nuclear power plant operator in submarines and surface ships. Upon retirement, he worked for five years at a large shipyard developing SAS/AF FRAME applications on mainframes, then four years as Group Manager for BI Tools at a Fortune 500 financial services company. Jordan joined SAS' Latin America division in 2003, going on to serve as Director of Technical Services. He began his current role in SAS Education in 2006, where he teaches and develops SAS Foundation programming classes. He co-authored the classes SAS SQL1: Foundations and SAS SQL2: Processing Data Efficiently in Real-World Scenarios, and he sporadically posts "Jedi SAS Tricks" on the SAS Training Post blog.
Kim Larsen is a VP of Analytical Insights at Market Share Partners, a leading marketing science company based in Los Angeles. Prior to Market Share Partners, he worked in the advanced analytics department of a Fortune 500 financial services institution. Kim has worked in the area of data mining and statistical modeling industry since 2001 and programmed in SAS since 1995. Throughout his professional career, he has worked on and 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).
Kim holds a B.S. in mathematics and economics and an M.S. in statistics.
Gordon S. Linoff has had a keen interest in understanding and analyzing large data sets and in applying the results to business problems since he was a student at the Massachusetts Institute of Technology. Gordon is a practitioner, thought-leader, and teacher in the area of data mining.
His most recent book, Data Analysis with SQL and Excel, was published by Wiley in 2007. His earlier books, written with his colleague Michael Berry, include Data Mining Techniques for Marketing, Sales, and Customer Relationship Management and Mastering Data Mining: The Art and Science of Customer Relationship Management.
Gordon is a Founder and Principal of Data Miners, Inc. Prior to co-founding Data Miners in 1998, he also worked at Naviant Technology Solutions and Thinking Machines Corporation. He has consulted for a wide range of companies including Bank of America, BT, The Limited, The New York Times, T-Mobile, The Teaching Company, and Pfizer. Dr. Robert M. Lucas, PhD, Director of Analytical Education at SAS, has a PhD in statistics from Colorado State University and over 32 years' experience as an applied statistician. He worked for 17 years at Research Triangle Institute, applying statistical techniques to collect and analyze data for a broad range of scientific and business problems. At SAS, he has developed and taught advanced statistics, time series, data mining and mathematical optimization classes, as well as providing customized training or consulting in many industries, including government, pharmaceuticals, banking, manufacturing and retail.
Dr. Christophe Mues is an assistant professor at the School of Management of the University of Southampton (UK). One of his key research interests is in the business intelligence domain, where he has investigated the use of decision table and diagram techniques in a variety of problem contexts, most notably business rule modeling and validation. Two other key research areas are knowledge discovery and data mining, with a strong interest in applying data mining techniques to financial risk management and, in particular, credit scoring. He has cooperated with public services, companies, and financial institutions in each of these areas, and his findings have been published in various journals and presented at international conferences. He has taught training courses on Credit Scoring for Basel II in several European and Asian countries, all in collaboration with SAS.
Walter R. Paczkowski has a Ph.D. in economics (Texas A&M University, 1977) with specialities in econometrics and statistics. Dr. Paczkowski worked in various quantitative positions at AT&T, such as their business research and forecasting divisions. He also worked at AT&T Bell Labs (and later AT&T Labs) in the Consumer Lab Division where he applied advanced statistical techniques (such as conjoint and discrete choice models) to identifying consumer preferences and willingness-to-pay for telecommunications services.
Dr. Paczkowski founded the statistical consulting firm Data Analytics Corp. This practice focuses on applying advanced statistical methodologies to a variety of complex business problems - primarily pricing - across an array of industries such as: banking, beverages, clothing, direct marketing, food, jewelry, package goods, pharmaceuticals, and publications, and various technologies.
Dr. Paczkowski is an adjunct professor of economics at Rutgers University (specializing in econometrics) and was formerly an adjunct professor of mathematics and statistics at The College of New Jersey (specializing in statistics).
Mike Patetta is a senior instructor and course developer in the Education Division at SAS. A respected instructor, Mike has taught more than 300 analytical and statistical courses during his tenure at the company. Mike's uncanny ability to relate course material to a customer's business problems makes him one of the division's most requested instructors.
But teaching is not his only passion; Mike is also a prolific course developer, serving as the primary developer for some of the division's most popular courses in the SAS analytics curriculum. Since joining SAS in 1994, Mike has served as the primary author for such courses as Categorical Data Analysis Using Logistic Regression, Longitudinal Data Analysis with Discrete and Continuous Responses, and Survival Analysis Using the Proportional Hazards Model. He co-authored the Predictive Modeling using Logistic Regression course and has written a number of specialty courses including Fitting Poisson Regression Models Using the GENMOD Procedure and Determining Power and Sample Size Using SAS/STAT Software.
When he's not teaching or writing, Mike can be found providing technical advice to a number of SAS' largest customers. During his career at SAS, Mike has served as a consultant for a wide range of industries, including pharmaceutical, market research, healthcare, financial services, and retail. His consultative and mentoring services have helped Fortune 500 companies improve their analytical practice, build better models and implement efficient and standard procedures in their analytical endeavors.
Prior to coming to SAS, Mike was a statistician for NC State's Center for Health Statistics, where he maintained Medicaid databases and assisted medical examiners and the tuberculosis control branch on a variety of statistical projects. As an epidemiologist with the state, he helped supervise public health program consultants and establish a head and spinal cord surveillance system.
Mike's serious side is balanced by time spent with his wife and three young daughters. Favorite hobbies include hiking, swimming, reading, camping and visiting various U.S. National Parks.
Mike holds a Bachelor of Arts degree from Notre Dame University and a Master's degree from the University of North Carolina.
Gerhard Pilcher, Senior Scientist at Elder Research Inc., enjoys data mining, especially in the areas of fraud detection and risk management, using various analytical methods, working with people, leading change and timely management of complex projects. His work experience spans both private and government sectors, including international experience.
Pilcher has extensive experience in the construction and telecommunication industries both as a business owner and executive. He is a recognized expert in three dimensional roadway modeling and automated machine guidance using Global Positioning Satellite systems. In his role as Chief Technology Officer and VP of Engineering for Pulse Communications, Pilcher directed the design of early digital subscriber line systems (internet over the telephone line) and was a member of the international forum defining the standards for DSL implementation. Prior to Pulse Communications, he was Director of Operations for Bell Northern Research, leading the design and delivery of hardware and software for large-scale telephony switching and fiber optic systems.
Pilcher has served on various boards, including the Strategic Advisory Board for the Computer Science Department at North Carolina State University (NCSU). He has an MS in analytics (Institute for Advanced Analytics, NCSU) and a BS in computer science from NCSU.
Heath Rushing, Principal Consultant and co-founder of Adsurgo LLC, an analytics consulting company, is a former professor from the Air Force Academy. He holds a Master's degree in Operations Research from the Air Force Institute of Technology and has used JMP since 2001. After teaching at the Academy, Heath was a quality engineer and Six Sigma Black Belt in both biopharmaceutical manufacturing and R&D where he designed and delivered training material in Six Sigma, Statistical Process Control (SPC), Design of Experiments (DOE) and Measurement Systems Analysis (MSA) using JMP. In addition, Heath has been a symposium speaker at both national and international pharma and medical device conferences. Heath is an American Society of Quality (ASQ) Certified Quality Engineer and teaches most courses in the JMP curriculum, including a new course on Quality by Design (QbD) that he developed.
Naeem Siddiqi has 15 years experience in credit risk management, both as a consultant and as a risk manager at financial institutions.
At SAS, Naeem has played a key role in the development of SAS Credit Scoring, and continues to provide worldwide support for this initiative. His responsibilities range from pre-sales support to consultancy for various projects. Naeem is the author of Credit Risk Scorecards: Developing and Implementing Intelligent Credit Scoring (Wiley and Sons, New York, 2005) and is a frequent speaker on credit risk topics.
Naeem has an Honours Bachelor of Engineering from Imperial College of Science, Technology and Medicine at the University of London, and an MBA from York University in Toronto.
F. Michael Speed, Ph.D., is currently a professor of statistics at Texas A&M University. He holds a Ph.D. in Statistics from Texas A&M and a master's degree in Mathematics from St. Mary's University of San Antonio. Currently, Dr. Speed is also the Associate Dean of Technology Mediated Instruction in the College of Science at Texas A&M. He received the College AFS Teaching Award in 2001, as well as the H.O. Hartley Award in 1999. Dr. Speed has also refereed papers for Technometrics, American Statistician, and Journal of the American Statistical Society. He has also served as the associate editor of Communications in Statistics. His current research interests include analyzing harvest data and fresh water inflows in Galveston Bay as well as designing low cost experiments for analyzing exhaust emission data.
Jeffrey R. Thompson, PhD, is an Analytical Training Consultant in the Education Division at SAS. Thompson's first exposure to SAS software came in the early 90s while attending Stetson University in Deland, FL, as an undergraduate math major. He continued using SAS extensively throughout graduate school for both research and educational duties. He holds a master's degree in computational statistics from the University of Central Florida in Orlando, and a PhD in statistics from the University of Florida in Gainesville. His dissertation research was in the area of measurement error models.
Thompson started his career in academia with the Department of Statistics at North Carolina State University in Raleigh, where he received an outstanding teacher award and achieved the rank of associate professor. He has publications in American Journal of Perinatology, International Statistical Review, Austrian Journal of Statistics, The Journal of Heart and Lung Transplantation, Florida Health Care Journal, and other peer-reviewed journals. He is also author of the teacher's edition to David Moore's The Basic Practice of Statistics (4th Ed). Thompson has given numerous research talks and seminars, including presentations at regional, national and international statistical conferences and at universities such as Ludwig-Maximilians-University in Munich, Germany, and the Technical University Graz in Austria.
Mike Thurber, Senior Data Miner at Elder Research Inc., is an analysis professional who listens carefully to his clients' business objectives and challenges and has a passion for extracting relevant and valuable insights from available data. Examples of Mike's successes include gleaning insights on how complex consumer choices impact sales, predicting profitability of prospective customers, showing how call center interactions affect customer retention, and forecasting recovery of losses due to default. Mike earned a BS degree in Chemical Engineering from Brigham Young University and a Master's degree in Statistics from Virginia Commonwealth University. Prior to joining ERI he developed engineering modeling software, consulted on Business Intelligence applications, advised on many data warehousing projects, and served in several analytic roles in manufacturing and finance. He is an expert data analyst, comfortable with diverse data sources in diverse industries.
Paul W. Thurman, a Columbia MBA valedictorian, service award winner, and multiple teaching award recipient, has extensive management consulting and line management experience helping a variety of Fortune 500 firms realize value from innovative and coordinated business, operations, and technology strategies. He has held senior positions at Booz Allen Hamilton and American Express and has served public and private sector clients on five continents.
Paul has consulted to several global financial services, health care, retail, and consumer products firms across a broad set of business disciplines. His consulting work has focused mostly on analytical modeling to support strategic planning and decision-making, corporate cost management, and technology and business integration. He has also developed solutions around customer segmentation, demand modeling, profitability, and experience mapping. He currently runs his own general management and executive education consultancy and is a frequent conference presenter.
Paul currently teaches strategic management and data analysis courses at Columbia's School of International and Public Affairs and at its Mailman School of Public Health. He also serves as Executive Director of the Columbia University Alliance for Healthcare Management, coordinating research, academic, and industry programs among Columbia's graduate schools of Public Health, Medicine, and Business. Paul has taught courses in decision, risk, and operations in the full-time and Executive MBA Programs at the Columbia, London, and University of California, Berkeley business schools, and has been a Healthcare Research Fellow, Professor, and MBA Director at the Moscow School of Management SKOLKOVO in Russia. In addition, Paul has held visiting professorships in China, India, Greece, Saudi Arabia, Singapore, Brazil, and Iceland.
In addition to his faculty appointments, Paul serves as a clinical professor and affiliated researcher at the National Cancer Institute's Center for Cancer Research at the National Institutes of Health. His recent peer-reviewed research has focused on scientific collaboration and its effect on research quality, and also on cancer drug patents, FDA approvals, and market pricing. He is the author of MBA Fundamentals of Statistics, (Kaplan, 2008), Pocket Guide to Data Analysis (Kaplan, 2009), and co-author (with Thomas P. Ference) of MBA Fundamentals of Business Strategy (Kaplan, 2009). He is also lead editor, with colleagues from Greece, of Female Immigrant Entrepreneurs, and Father-Daughter Succession in Family Businesses, two research compendia to be published in 2011 by Gower (UK). He is also author of a forthcoming book on international business and strategic management, focused on "BRIC" economies, due to be released in 2012 (also by Gower).
Finally, Paul has served on the boards of the Greenburgh (New York) Nature Center, the Scarsdale (New York) Teen Center, and currently sits on the advisory boards of a number of entrepreneurial ventures. Paul received his BS in mathematics from Stanford University and his MBA (highest honors) from Columbia.
Catherine Truxillo, PhD is manager of Analytical Education at SAS and has been teaching for SAS since 2000. She has written or co-written SAS training courses for advanced statistical methods including multivariate statistics, linear and generalized linear mixed models, multilevel models, structural equation models, multiple imputation methods for missing data, statistical process control, design and analysis of experiments, advanced business analytics and cluster analysis. Although she primarily works with topics in SAS/STAT, she also teaches SAS courses using SAS/IML (the interactive matrix language), SAS/QC, SAS Enterprise Guide, SAS Enterprise Miner, SAS High-Performance Forecasting, SAS Forecast Studio, and JMP software.
Truxillo completed her PhD in social psychology with an emphasis in statistics at the University of Texas at Austin. She enjoys working with SAS users from a wide variety of industries, including insurance, finance, manufacturing, pharmaceuticals, behavioral research, marketing, and retail.
Peter Westfall is the Paul Whitfield Horn Professor of Statistics and the James Niver Professor of Information Systems and Quantitative Sciences at Texas Tech University.
Dr. Westfall has consulted with various companies and government agencies for 20 years and has published more than 100 articles and three books on statistical theory and practice. He is the lead author of the books Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment (Wiley, 1993), Multiple Comparisons and Multiple Tests Using the SAS System (SAS Books by Users, 1999), and Multiple Comparisons and Multiple Tests Using the SAS System Workbook (SAS Books by Users, 2000).
Dr. Westfall received the "Most Outstanding Applications Paper Award" from the American Statistical Association, developed the SAS/STAT procedure PROC MULTTEST, and won the 2005 Excellence in Continuing Education Award from the American Statistical Association.
The Center for Advanced Analytics and Business Intelligence, of which Dr. Westfall is the Associate Director, was cited for its contributions to grid computing technology. Peter is a past editor of The American Statistician, is a Fellow of the American Statistical Association, and is a Fellow of the American Association for the Advancement of Science.
Terry Woodfield is an Analytical Training Consultant in the Education Division of SAS and served as co-chair for M2003, SAS' sixth annual data mining conference. Dr. Woodfield has more than 28 years of SAS programming experience and has provided training 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 has been an expert witness in utility rate-making hearings. Before joining SAS, Dr. Woodfield was the chief statistician at HNC Software, and other prior experience includes statistical software development in SAS/ETS Research and Development and university teaching and research.
Werner Wothke is an applied statistician with extensive experience in software development, software publishing, and training with both small companies and Fortune 500 companies. Werner currently serves as principal statistician at the American Institutes for Research in Washington, DC. A native of Germany, Werner holds a Ph.D. in Methodology of Behavioral Sciences from the University of Chicago.
Werner sees statistics as an interdisciplinary effort that brings together concepts and modeling approaches from different sciences. The recent advances in statistical applications have been rather dramatic, and today we have the computing power to conduct many more interesting and realistic analyses than we had only 10 or 20 years ago. Werner is interested and experienced in communicating statistical concepts and results to non-statisticians, and in how modern statistical visualization can help. He has taught scores of structural equation modeling workshops throughout the US, Europe, and Japan.
Jeff Zeanah is the President of Z Solutions, Inc., a firm focused on the support of organizations through predictive analytics and exploratory data analysis. His primary interest and research addresses the problems that organizations face in improving their business decisions through data analysis, neural networks, predictive analytics, exploratory data analysis and the selling of the analytical results. Jeff has consulted with industry leaders in manufacturing, high tech, retail, public health, science, finance, nutrition, and utilities. He is the developer of exploratory approaches and techniques that have been used by Fortune 500 companies, independent researchers, government agencies, and over 30 universities worldwide. Jeff's practice has been in areas as diverse as sizing electric transformers (for which he holds a U.S. patent), market research, fraud detection, health systems, and wine making. In addition to delivering the Business Knowledge Series course that he developed, he is also a contract instructor for SAS, and he serves on the board of the Institute for Business Intelligence at The University of Alabama.
Aiman Zeid has 23 years experience in data management, technical implementation of business intelligence and performance management solutions, and management consulting. Aiman is the lead developer of the SAS global Business Intelligence Competency Center program and services. He also contributed to the development of the SAS Information Evolution Model Assessment methodology and services. Using SAS information evolution model as a benchmark, Aiman has worked with customers to help them assess the effectiveness and readiness of their current data management practices, human capital resources, processes, and culture. He also has worked with customers to develop and implement a plan to maximize the business value from the investment in technology, and to develop a Business Intelligence Competency Center to help them achieve their organizational objectives.
During the last few years, Aiman has conducted market research in data management, worked with many thought leaders and industry analysts, and participated in marketing webcasts and customer events.
Aiman holds a master of science degree in engineering administration (MBA) from George Washington University, a bachelor's degree in civil engineering, and a diploma in computer science. He has authored several SAS papers and presentations for the SAS Global Forum conferences. He also has authored a paper for The Data Warehouse Institute that provides a blueprint and best practices for establishing and evolving a Business Intelligence Competency Center.