Business Knowledge Series Instructors
Dr. Bart Baesens, is an assistant professor at the Department of Decisions Sciences and Information Management of
the K.U. Leuven in Belgium, as well at the School of Management of the University of Southampton in the United Kingdom. His
research focuses on the use of data mining and machine learning techniques for credit scoring and customer relationship
management (CRM) applications. He has published in journals worldwide and has presented at top international conferences.
Bart regularly tutors, advises and provides consulting support to international financial institutions with respect to
their credit risk management and credit scoring policy. He also organizes events, workshops, and conferences on his
research topics.
Mark Bailey, Statistical Training and Technical Services VI, 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.
Michael Berry, together with his colleague, Gordon Linoff, has authored some of the most widely read and respected books on data mining. These best sellers in the field have been translated into many languages. Michael is an active practitioner of data mining. His books reflect many years of practical, hands-on experience down in the data mines.
A data mining educator as well as a consultant, Michael is in demand as a keynote speaker and seminar leader in the area of data mining generally and the application of data mining to customer relationship management in particular.
Prior to founding Data Miners in December, 1997, Michael spent 8 years at Thinking Machines Corporation. There he specialized in the application of massively parallel supercomputing techniques to business and marketing applications, including one of the largest database marketing systems of the time.
Michael has both US and UK passports and may legally reside and work in the EU. Michael possesses reading and limited speaking knowledge of French and Spanish. He believes that to understand data, one has to be close to the business that generated it and to the people who make use of it so he is happy to travel to client locations around the world.
Representative engagements include
- building a "best next offer" recommendation system to improve cross selling for a large US bank
- analyzing the performance of competing acquisition channels over time
- performing customer segmentation based on behavioral and demographic variables
- building a model to score the profit potential of any geographic area in the United States for a property and casualty insurer
- scoring customers for attrition risk for a credit card issuer
- analyzing web log data to characterize the differences between registered and unregistered users
- helping data mining software companies improve their products
- providing expert witness testimony and litigation support for law suits involving data mining.
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.
Patricia B. Cerrito is a senior biostatistician at the Jewish Hospital Center for Advanced Medicine and the
University of Louisville, with numerous collaborations in the use of data mining to examine health outcomes. Recently, she
was the project director for an NSF grant to combine Geographic Information Systems and environmental details with data
mining to investigate the need for treatment for shortness of air in a hospital emergency room. Dr. Cerrito is using SAS
Text Miner to investigate chart notes in patient records. She is collaborating with the SAS developers in the use of SAS
Text Miner.
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, 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 17 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 and Wendell H. Bailey Faculty Excellence 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; Great Executive MBA Instructor Award at the University of Iowa, Iowa City; and Outstanding Marketing Teacher Award, given by the Academy of Marketing Science, Coral Gables, Florida.
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 cochaired 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, etc. He is the founder of the SAS/OSU Data Mining Certificate program at Oklahoma State University.
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 Institute Inc. 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.
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.
Michael Forno, Vice President with the Financial Risk Group, a firm focused on implementation and business advisory services for various areas of risk
management, has over 10 years of experience with SAS Risk Dimensions. Mr. Forno has experience in market, credit, and operational risk management,
throughout the US, Europe, and, Canada. Mr. Forno spent 8 years working at SAS, where he was the global risk technical support lead, risk management
consulting practice manager, and the global lead risk trainer. He designed, developed, and delivered the first risk training courses for SAS and continues
to contribute to the risk management curriculum at SAS. Mr. Forno holds a B.S. and M.S. in Economics from North Carolina State University, where he studied
Economics, Statistics, and Oceanography.
Ronald Holanek, Founder and President of the Financial Risk Group since 2002, has been a SAS user or developer for 24 years out of his 27-year career.
Prior to the Financial Risk Group, Mr. Holanek spent 16 years working at SAS in the Research and Development area, where he was one of the original members
of the SAS Risk Dimension design and development team. Ronald also participated in development of the SAS Credit Risk Management System and was involved in
the first implementation in Australia and many more worldwide. For the past 11 years, Mr. Holanek has conducted worldwide training seminars and implemented
SAS Basel II, market, credit, and operational risk solutions in US, Europe, Australia, Canada, and Asia. Mr. Holanek's clients have included energy and
commodity firms, money-center and investment banks, hedge funds, and large corporate companies. Mr. Holanek received his undergraduate degree in computer
science from North Carolina State University and an MBA from North Carolina State University's Jenkins Graduate School of Management.
Regitze Ladekarl, a Senior Risk Consultant with the Financial Risk Group, specializes in market and credit risk management, Basel II,
asset/liability management, and regulatory compliance. Ms. Ladekarl is certified as a Financial Risk Manager with the Global Association of Risk
Professionals. Regitze is SAS certified in Base SAS and advanced programming for SAS 9. She has over 10 years of experience in risk management, from
implementing financial models and risk solutions to supervising regulatory compliance. Ms. Ladekarl is a designer and developer of training material as
well as a worldwide presenter and trainer of risk management courses. Ms. Ladekarl has previously held positions at SAS Institute Inc., the Danish FSA, and
Accenture. She is a graduate of the University of Copenhagen in Financial Economics, and she co-authored a World Bank Policy research working paper titled
"The Use of Derivatives to Hedge Embedded Options: The Case of Pension Institutions in Denmark."
Gordon 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.
The talk presented here is based on his most recent book, Data Analysis with SQL and Excel, which is published by Wiley and due out at the end of 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., a consulting group focused on data mining. Prior to 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, Statistical Training and Technical Services, SAS Institute, has a PhD in
Statistics from Colorado State University and over 27 years experience as an applied statistician. Dr. Lucas 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. During his tenure at SAS Institute, Dr. Lucas has developed and taught advanced
statistics; time series, data mining, and mathematical optimization classes as well provided 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.
Chris Murtha may be new to SAS, but she is no stranger to teaching. She has more than 20 years of teaching experience in the fields of programming,
statistics, and mathematics.
Chris was introduced to SAS during her graduate program at N.C. State University. She always thought teaching SAS would be a fun job, but with 5 kids, traveling was out of the question. Once her youngest left the house however, Chris decided to revisit the idea and she is glad she did.
Before joining SAS, Chris taught SUDAAN software classes with RTI International; and prior to that, she worked with a major pharmaceutical company. She earned her bachelor's degree in mathematics from UNC 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, she often calls on her students during class (though, if they do not want to answer the question, they can defer it to someone else). Chris says that "this makes the class fun and really forces people to interact with each other." She says that it is fun to watch a group of complete strangers come together over 3 days. "I sometimes hear stories of students keeping in touch with each other after the class is over, which is great."
Students love Chris's interaction with them. One student said, "I love Chris' sense of humor. It definitely helps you get through complicated material." Another said "Chris is knowledgeable and adds personal experience to make the course more interesting."
In her spare time, Chris enjoys dancing, reading, downhill skiing, and traveling to see her kids.
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.
Dr. Bruce Schaalje is a professor in the Department of Statistics at Brigham Young University. Prior to his appointment at BYU in 1992, he was a statistician and research scientist at Agriculture Canada for 12 years. Dr. Schaalje has master's degrees from Brigham Young University in Zoology and the University of Washington in Biostatistics. He earned his Ph.D. in Statistics and Biomathematics from North Carolina State University. Dr. Schaalje has coauthored over 130 research articles in a wide variety of journals, including several articles on small sample inference in mixed linear models. He is the coauthor with Alvin Rencher of the Wiley textbook Linear Models in Statistics. He was selected by students as the Statistics Department teacher of the year in 1995.
Rajesh Selukar is a developer of procedures for analyzing time series data at SAS. He has a Ph.D. in Statistics from
the University of North Carolina at Chapel Hill. His recent work has mainly centered on a variety of time series modeling
techniques such as ARIMA, UCM, and State Space models. He has also worked on strategies of automating the usage of these
models in large-scale forecasting projects. On several occasions, he has provided consulting help in developing large-scale
forecasting systems for SAS customers in different industry areas such as retail, manufacturing, and hospitality.
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.
Dr. Catherine Truxillo has been a Statistical Training Specialist at SAS since 2000 and 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, and cluster analysis. Although she primarily works with advanced statistics topics, she also teaches SAS courses using SAS/IML (the interactive matrix language), Enterprise Guide, and JMP software.
Catherine's previous experiences with teaching, statistical consulting, and software design led her to a job teaching statistics for SAS.
Before moving to SAS, Catherine completed her Ph.D. in Social Psychology with an emphasis in Statistics at The University of Texas at Austin. While at UT Austin, she completed an internship with the Math and Computer Science department's statistical consulting help desk and taught a number of undergraduate courses. While teaching and performing her own graduate research, she worked for a software usability design company conducting experiments to assess the ease-of-use of various software interfaces and website designs.
She moved to Cary, North Carolina to join SAS in 2000, where she lives in the forest with her husband and two children. Her personal interests include bicycling, hiking, dancing, and singing.
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 a statistical services specialist 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 mining. His primary interests and research concern the problems organizations face to improve their business decisions through data analysis, including predictive analytics and the selling of the results. Jeff has consulted with industry leaders in manufacturing, retail, public health, science, finance, nutrition and utilities. He is an instructor for SAS Institute Inc. A frequent guest lecturer at universities on the topic of applying analytics to business, he serves on the board of the Institute for Business Intelligence at The University of Alabama.
As a recognized expert on neural networks and a broad range of exploratory data mining tools Jeff has authored papers on neural networks, exploratory data mining, and the implementation of those techniques in organizations. He is the developer of exploratory approaches and techniques that have been used worldwide by Fortune 500 companies, independent researchers, government agencies, and over 30 universities worldwide. His approaches have been applied in areas as diverse as improving manufacturing processes, analyzing market research, tasting wines, searching for oil, controlling river flow, sizing electric transformers, and classifying stars.
Aiman Zeid has 23 years experience in information 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 information 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 information 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.