Michael Hardin, University of Alabama
Jerry Oglesby, SAS
Keynote Speakers
Bill Kahn, Capital One
Bill DuMouchel, Lincoln Technologies
Trevor Hastie, Stanford University
Andreas S. Weigend, formerly of Amazon.com
Session Speakers
Mihael Ankerst, Boeing
Jason Bargen, Hallmark Cards, Inc.
Joe Bartling, H&R Block
Eugenia Bastos, SAS
Robert Chu, SAS
B. Jay Coleman, University of North Florida and Allen Lynch, Mercer University
Jim Cox, SAS
Perry Drake, Drake Direct
Rhonda Drake, Drake Direct
David Duling, SAS
Jim Georges, SAS
Paolo Giudici, University of Pavia, Italy
Brian Gray, University of Alabama
Patrick Hymel, MedMined, Inc.
Claudia Imhoff, Intelligent Solutions, Inc.
Roger Jones, Complexia
Dmitri V. Kuznetsov, Sigma Marketing
Larry S. Lai, Directv, Inc.
Daymond Ling, CIBC (Canadian Imperial Bank of Commerce)
Huan Liu, Arizona State University
David Madigan, Rutgers University
Ed Malthouse, Northwestern University
Manya Mayes, SAS
Sreelatha Meleth, University of Alabama at Birmingham
Brendan Murphy, Trinity College, Dublin
Will Potts, Data Miners
David Press, Greenbrier & Russell
Bruce Ratner, DM STAT-1 Consulting
Brett Russ, Blue Cross and Blue Shield of North Carolina
Vineet Singh, HP
Robert Stine, Wharton School, University of Pennsylvania
Steve Tanner, University of Alabama at Huntsville
Marietta Tretter, Mays Business School, Texas A&M University
John Wallace and Phil Corrin, Business Researchers
Cary White, University of North Carolina
(This is only a partial list as speakers are currently being finalized. Please visit again soon.)
Mihael Ankerst is a recognized
leader in visual data mining. This new area focuses on novel data mining
architectures which tightly integrate a visualization component with a
mining component. The core idea of visual data mining is a user-centric
mining approach that enables the user to specify hypotheses and domain
knowledge on-the-fly and to steer and monitor the data mining process in
order to discover patterns of her interest. Mihael has led several data
mining projects which included consulting, design and development of new
data mining solutions. The applications range from aircraft maintenance,
manufacturing, supplier management to homeland security. Mihael studied
computer science at the university of Munich, Germany and received his
Ph.D. in 2000. Since 2001, he has worked as Advanced Computing Technologist
in the Data & Text Mining group for the Boeing Company. Mihael has
given tutorials and invited talks at major conferences, research labs and
universities about visual data mining. He is also serving as program
committee member or session/tutorial chair for various related conferences
and journals.
Jason Bargen joined Hallmark in June of 2003 and works in the Consumer
Research Division at Hallmark Cards, Inc. The Consumer Research Division
provides consumer insights to the Corporation that are key to improving
business processes, making marketing, product and distribution decisions
and maintaining our leadership position in personal expression products.
Jason helps address a variety of issues in his role at Hallmark (e.g.,
segmenting consumers, maximizing consumer value, predicting consumer churn,
targeting mailings, and designing and analyzing retail tests).
Jason has a B.S. in Mathematics from Doane College and received his M.S. in Statistics at Kansas State University in May 2003. Jason's interest in academia included mixed models and design of experiments.
Joe Bartling is the Director of Enterprise Analysis at H&R Block. Joe's
group is responsible for enterprise wide Client Value Measurement, Client
Segmentation, and the design and analysis of market tests. In addition, his
group conducts modeling and analysis activities in support of H&&R Block's
Financial Advisor and Mortgage businesses.
Prior to joining H&R Block Joe was at Hallmark Cards Inc. where he managed the database analysis activities for Hallmark's Gold Crown Card program, one of the largest loyalty programs in America.
Joe has a BS in Statistics with minors in Mathematics and Watershed Science from Colorado State University, and a MA in Economics from the University of Missouri at Kansas City.
With a PhD in Epidemiology and a Masters in Biostatistics, Eugenia
Bastos brings a unique set of skills to the Health and Life Sciences
Division at SAS. She has developed an extensive knowledge of data mining,
risk analysis, forecasting, bioinformatics and the Micro Array Solution. As
a senior statistical consultant, she has offered seminars in data mining
for in-depth analyses of clinical trial data, including the development of
predictive models for pharmaceutical customers. In the bioinformatics
field, she has worked in analyses of gene expression data, such as variable
selection and dimension reduction of wide data sets.
Working previously in the academic environment, she has experience with reproductive health and cardiologic clinical trials, involving study design and sample size determination, as well as developing models of risk factors and costs of diseases using health services utilization databases.
Robert Chu is a Software Manager in the SAS Enterprise Miner
Research and Development group and has been with SAS for more than 16
years. His focus is on model assessment, model management, and model
deployment. He received a Master's degree in Computer Science and a
Master's degree in Statistics from North Carolina State University; and a
Bachelor's degree in Business Administration from National Cheng Kung
University. He also spent one year in the PhD program of Operations
Research at North Carline State University. He represents SAS Institute to
serve on the following industrial standards working groups and committee:
Data Mining Group (that publishes PMML specifications), JSR-073 Java Data
Mining API Specification Expert Group, Data Mining SIG of XML for Analysis
Council (currently served as the SIG Lead), and ACM Data Mining Standards
Committee.
B. Jay Coleman is the Richard deRaismes Kip Professor of Operations
Management and Quantitative Methods in the Coggin College of Business at
the University of North Florida, whose faculty he joined in 1988. Dr.
Coleman earned his M.S. (1985) and Ph.D. (1988) in Industrial Management
from Clemson University. He was named the Outstanding Graduate Faculty by
1995-1996 alumni of the Coggin College's masters programs, and received
university teaching awards in 1991, 1993, 1996, and 2000. In 2003, he
received both the University Outstanding Scholarship Award and the
University Outstanding Service Award.
Dr. Coleman is actively involved in research involving a wide variety of quantitative modeling applications, most notably in operations, finance, and sports management. His academic publications include articles in 17 different journals, including Decision Sciences, Production and Operations Management, Interfaces, Industrial Relations, and the Journal of Financial Research. A 1996 article in the Journal of Operations Management ranked Dr. Coleman's research productivity among the top 75 in the field of operations management in the United States.
In addition, his research has often caught the eye of the business and popular press. BusinessWeek, Forbes, and Individual Investor have highlighted his research on financial applications. Moreover, his work with Allen Lynch on modeling the decisions of the NCAA Tournament Selection Committee has been featured by the Wall Street Journal, Forbes, Investor's Business Daily, the New York Times, the Associated Press, and USA Today, well as over 50 other major media outlets, including UPI, CNN, the Sporting News, and CBS SportsLine.
Jim Cox manages the development of SAS Text Miner. Before that, he
was one of the designers and developers of SAS Enterprise Miner. In 1989,
he received a Ph.D. in Cognitive Psychology and Computer Science from the
University of North Carolina, and has over ten years research experience in
Natural Language Understanding.
Allen Kenneth Lynch, Associate Professor of Economics and Quantitative Analysis, earned a bachelor's degree at the University of North Florida and his master's and doctorate degrees at Florida State University. He has taught at the University of North Florida and worked as a Senior Demographic Research Analyst for Blockbuster Entertainment Group prior to joining the Mercer University faculty in 2000.
In his four years with Mercer University, Lynch has twice been named the Stetson School of Business and Economics' Distinguished Professor. He has published numerous journal articles, ranging from "Identifying the NCAA Tournament Dance Card," a statistical model which accurately predicted 94 percent of college basketball teams that earned at-large bids for the NCAA tournament over the last 10 years (coauthored by B. Jay Coleman of the University of North Florida), to "Proximity, Neighborhood and the Efficacy of Exclusion," recently published in Urban Studies (coauthored by David W. Rasmussen). While research related to crime and real estate markets dominate his research agenda, interest in the NCAA article resulted in substantial media attention. Over the last two years, stories related to this research appeared in The New York Times, Investors' Business Daily, The Wall Street Journal, as well as several Associated Press outlets.
Perry D. Drake has been involved in the direct marketing industry for
17 years. He is currently the Vice President of Drake Direct, a database
marketing consulting firm specializing in response modeling, customer file
segmentation, lifetime value analysis, customer profiling, database
consulting and market research. Prior to this, Perry worked for
approximately eleven years in a variety of roles at The Reader's Digest
Association.
Perry's initial position at The Reader's Digest Association was as a statistician in the quantitative analysis department, applying segmentation, response modeling, test design and multivariate techniques. Later, moving into a product line role as Associate Director of Magazine Circulation Marketing, Perry assumed full strategic responsibility for all acquisition efforts including mailings to house and outside lists as well as renewal and billing efforts. More recently, Perry assumed the role of Marketing Services Director where he was responsible for a staff of 40 database marketing professionals.
In addition to consulting, Perry is an Associate Professor at New York University in the Direct Marketing Master's Degree program since Fall, 1998 currently teaching "Statistics for Direct Marketers," "Data Mining and Analysis" and "Advanced Data Mining and Analysis" to future direct marketers. Perry was the recipient of the "Outstanding Master's Faculty Award." Perry also lectures on testing and marketing financials for Western Connecticut State University and Mercy College.
Perry is also a Published author. His new book, Optimal Database Marketing, was released in April of 2002 by Sage Publications. This new book, which has received rave reviews by industry professionals, delves into topics including lifetime value, segmentation and response modeling. It is a "how to" book geared solely for the marketer wanting to better understand the practices and principals of database marketing.
Perry earned a Masters of Science in Applied Statistics from the University of Iowa and a Bachelor of Science in Economics from the University of Missouri.
Rhonda Knehans Drake has been involved in the direct marketing
industry for over 16 years. She is the President and founder of Drake
Direct, a leader in the strategic use of customer information, specializing
in response modeling, customer file segmentation, lifetime value analysis,
test design and analysis and database consulting. Current and recent
clients include American Express, BMG Music and Video Club, Bookspan, Danone
Waters Division, Deutsch Advertising, Disney, Guideposts Publications,
Weider Publication, Primedia and The Reader's Digest Association.
Rhonda's background includes experience in all aspects of direct marketing from conceptualization of strategy to test market design and implementation in roll-out. Rhonda's experience emphasizes the importance of leveraging information to make marketing decisions. This experience has enabled her to assess the most effective and efficient ways to improve marketing efforts.
Prior to founding Drake Direct, Rhonda was employed by The Reader's Digest Association as Director of Customer Database and List Management. At The Reader's Digest Association, Rhonda was a part of the management team which led the effort in developing a new strategic business aimed at marketing to young families with children. Before this assignment, Rhonda was a senior account executive at Information Resources, Inc. In this role, Rhonda lead two of IRI's largest account teams: Clairol and Bristol Myers. Rhonda has also worked for Columbia House Music and Video Club, Citicorp POS and Arbitron Ratings.
In addition to consulting, Rhonda is an Associate Professor at New York University in the Direct Marketing Master's Degree program since Fall 2000 teaching "Statistics for Direct Marketers."
Rhonda earned a Master of Science in Applied Statistics from the University of Iowa and a Bachelor of Science in Economics from the University of Missouri. You can learn more about Drake Direct at www.DrakeDirect.com.
David Duling is the software development manager for SAS/Enterprise Miner.
He has worked at SAS since 1996 developing various components for EM including
the process flow diagram, scoring functions, neural network, ensemble models,
and link analysis. David has degrees in Physics and Statistics and previously
worked for the National Institutes of Health developing and publishing methods of
numerical analysis in simulations of magnetic resonance spectroscopy.
William DuMouchel received the Ph.D. in Statistics from Yale
University in 1971 and has held a number of positions in academia and
industry. His most recent academic appointment was as Professor of
Biostatistics and Medical Informatics at Columbia University from 1994 to
1996. Before that he held faculty positions at MIT, U. of Michigan, and
UC, Berkeley. During the period 1984-1991 he was responsible for the
overall statistical design aspects of the RS/Explore and RS/Discover data
analysis and experimental design computer advisory systems produced by BBN
Software Products Corporation.
Until September 2004, Dr. DuMouchel served as Technology Consultant, Statistics Research, at the AT&T Shannon Laboratory in Florham Park, New Jersey, conducting research on data mining, Bayesian modeling and other statistical methods. His methodology for detecting and measuring associations in transactional databases, called the Gamma-Poisson Shrinker (GPS), has been applied to adverse drug reaction databases by many researchers at the FDA and elsewhere. Two papers describing this and related work have won Best Application Paper awards at the 2001 and 2003 International Conferences on Knowledge Discovery and Data Mining (KDD). Dr. DuMouchel is coprogram chair of the KDD-2004 conference held August 22-25 in Seattle, Washington. Currently, Dr. DuMouchel is the director and senior advisor at Lincoln Technologies.
Jim Georges is a statistician and instructor in the Education
Division of SAS Institute. He has helped to develop many of the courses in
the Division's data mining curriculum including Predictive Modeling Using
SAS Enterprise Miner 5, Advanced Predictive Modeling Using SAS Enterprise
Miner 5, and Data Preparation for Data Mining. He has also fostered the
creation of SAS Data Mining Certificate program.
His current research interests include application of Bayesian methods in predictive modeling and representational modeling.
Jim has B.S. degrees in Mathematics and Physics from California Polytechnic State University, San Luis Obispo and a PhD in Mathematics and Statistics from Boston University.
Paolo Giudici (Msc in statistics, Minnesota, 1989; Phd in statistics,
Trento, 1993) is Associate Professor of Statistics at the Faculty of
Economics of the University of Pavia. He is a coordinator of an
International Master of the School of Excellence of the University of Pavia
(IUSS) on "Complexity and its interdisciplinary applications" and
responsible for the E-learning activities of the Faculty of Economics of
the University of Pavia. He has authored about 65 scientific papers, among
which 2 research books, 30 articles appeared in international journals
(ISI) and 33 papers in refereed proceedings and volumes. His research
themes can be classified into: statistical models for data mining,
multivariate graphical models, bayesian statistics and Markov Chain Monte
Carlo computational methods. In 2001 he has founded the data mining
laboratory of the University of Pavia that carries out research, applied
and foundational, in collaboration with research institutions and
companies.
J. Brian Gray is Professor of Statistics in the Applied Statistics Program
and in the Department of Information Systems, Statistics, and Management
Science at The University of Alabama.
Dr. Gray's research interests are in the areas of exploratory data analysis, data mining, regression analysis, statistical computing, and statistical graphics. His current research activity is in the applications of genetic algorithms to statistics and data mining. He has published research articles in journals including the Journal of Computational and Graphical Statistics, Computational Statistics and Data Analysis, Statistics and Computing, Journal of Statistical Computation and Simulation, Technometrics, and The American Statistician. Dr. Gray received the Wilcoxon Prize for Best Practical Application Paper in Technometrics in 1984.
Dr. Gray teaches a variety of statistics courses at the undergraduate, masters, and doctoral levels. Dr. Gray has taught MBA and Executive MBA statistics courses for the past 20 years and has received several teaching awards from the MBA and Executive MBA Associations of The University of Alabama and Texas Christian University. He co-authored the books Basic Statistical Ideas for Managers (Hildebrand, Ott, and Gray 2005) and Business Cases in Statistical Decision-Making: Computer Based Applications (Peters and Gray 1994).
Dr. Michael Hardin is the Director of the Institute of Business
Intelligence with the College of Business at the University of Alabama, as
well as a professor of statistics at the University. He has authored or
co-authored over 80 papers in various journals including the Lancet, the
Journal of the American Medical Association, the Journal of the American
Medical Informatics Association, the American Journal of Epidemiology, the
American Statistician, the Journal of Statistical Computation and
Simulation, and Communications in Statistics. He is the author or co-author
of over 150 abstracts presented at national meetings and has given over 75
invited lectures or talks. He is the author of several book chapters
dealing with database design and decision support systems.
Dr. Hardin often serves as a consultant to healthcare organizations in the areas of data mining, sampling, and program integrity. Additionally, he is an instructor and consultant for SAS in the areas of data mining and time series analysis. He is Adjunct Professor of Biostatistics and Adjunct Professor of Health Informatics at the University of Alabama at Birmingham. He has served as Scholar in Residence in the Center for Information Management, Department of Information Systems and Operations Management, Loyola University, Chicago, and Visiting Professor in the Department of Management and Information Sciences and Statistics at Trinity College, Dublin, Ireland.
A member of numerous professional associations including the American Statistical Association, the Biometric Society, and the Institute of Mathematical Statistics, Hardin's specialty areas include data mining and knowledge discovery, data visualization, data warehousing, machine learning, statistical classification models, data management and collection methodologies, research design, informatics, the applications of statistical methodologies in the study of aging, and biostatistics.
Hardin earned a B.A. from the University of West Florida, an M.S. from Florida State University and an M.A. and Ph.D from the University of Alabama.
Trevor Hastie was born in South Africa in 1953. He received his university
education from Rhodes University, South Africa (BS), University of Cape
Town (MS), and Stanford University (Ph.D Statistics 1984).
After graduating he returned to South Africa for a year, and then returned in March 1986 and joined the statistics and data analysis research group at what was then AT&T Bell Laboratories. After 9 enjoyable years at Bell Labs, he returned to Stanford University in 1994 as Professor in Statistics and Biostatistics.
His main research contributions have been in the field of applied nonparametric regression and classification, and he has written two books in this area: Generalized Additive Models (with R. Tibshirani, Chapman and Hall, 1991) and Elements of Statistical Learning (with R. Tibshirani and J. Friedman, Springer 2001). He has also made contributions in statistical computing, co-editing (with J. Chambers) a large software library on modeling tools in the S-plus language (Statistical Models in S, Wadsworth, 1992). His current research focuses on applied problems in biology and genomics, medicine and industry, in particular data mining, prediction and classification problems.
Patrick Hymel, MD is co-founder and Chief Medical Officer of MedMined, Inc. MedMined provides proprietary data mining services to hospitals to identify quality breakdowns which are causing hospital-acquired infections. MedMined's services have been proven to reduce the incidence and cost of these infections.
MedMined serves more than 80 hospital clients across the U.S. and has been recognized by MIT's Technology Review, Fortune magazine, Modern Healthcare and other respected publications.
Dr. Hymel received his medical degree from Louisiana State University, and completed residency training in Emergency Medicine at Charity Hospital in New Orleans. His research interest is the interface between Knowledge Discovery technologies, clinical decision making, and healthcare quality improvement.
A thought leader, visionary, and practitioner in the rapidly growing fields
of business intelligence and customer focused-strategy — Claudia
Imhoff, Ph.D. is a popular and dynamic speaker and internationally
recognized expert on analytical CRM, business intelligence, and the
infrastructure to support these initiatives - the Corporate Information
Factory (CIF Dr. Imhoff has co-authored five highly-regarded and popular
books on these subjects and writes monthly columns (totaling more than 60)
for technical and business magazines. She has served on the Board of
Advisors for DAMA International and was chosen by the DAMA organizations to
receive the 1999 Individual Achievement Award. She is an advisor and a
faculty member for The Data Warehousing Institute and serves as an advisor
for several technology and commercial companies. Dr. Imhoff delivers
keynote addresses at conferences sponsored by software companies and their
user groups, The Data Warehousing Institute, The Economist, COMDEX, and
many international o rganizations. She has appeared repeatedly on World
Business Review, Microsoft's Getting Results programs, and web casts
sponsored by DM Review, Better Management, and several technology vendors.
She is a member of the Advisory Board of the Daniels School of Business at
the University of Denver and is on several technology companies' advisory
councils.
Dr. Imhoff founded Intelligent Solutions, Inc. (www.IntelSols.com), a well respected Business Intelligence and CRM consulting and education firm in 1992. Her company has successfully implemented over 150 Corporate Information Factory architectures in all industry areas. Dr. Imhoff obtained her Doctorate degree from the University of Tennessee, Oak Ridge, her Master's degree from the University of Colorado, Boulder and her Bachelor's degree from Duke University, Durham, NC.
Roger Jones serves as Chairman and Chief Executive Officer for Complexica and Chairman of CommodiCast and Assuratech. A rare combination of entrepreneur and scientist, Dr. Jones founded Complexica in 1999 with a mission to hatch spin-off companies using complexity science and other advanced data mining techniques that deliver real solutions and a competitive advantage in complex business environments.
Well-known in the advanced computing academic and scientific communities, Dr. Jones earned a Ph.D. in physics from Dartmouth College in 1979 where his early interests included biological physics and the basis of learning, plasma physics and fusion. Dr. Jones joined Los Alamos National Laboratory (LANL) in 1979, working within the Laser Fusion Program at LANL. During his tenure at LANL, he founded the Nonlinear Adaptive Computation effort ? which focused on developing software data mining and control systems that had the capacity to learn from data as the systems interacted with the data. He was a member of the Executive Board of the Center for Nonlinear Studies at Los Alamos where he led the development of projects with a number of industrial and government partners including Du Pont, General Motors, Citicorp,the Department of Transportation, the Department of Defense, Texas Instruments, LAN Research, the Internal Revenue Service, and the Laser Institute of America.
While at the lab, his projects ranged from the development of auto anti-lock braking systems, patented adaptive processes for control of chemical plants and integrated circuit manufacture, laser welding as well as data mining projects that identified and predicted loss rates in credit card portfolios, identified and found objects in satellite imagery and sonar signals, and detected fraud in electronic filing of tax returns.
Dr. Jones has been an active participant in the scientific application of complexity science to an array of hard-to-solve business problems. Following the Latin American debt crisis, leading bankers looked to Los Alamos-based scientists for new ideas in preventing a future crisis, leading to an array of informatics and complexity-based solutions. As a result, Dr. Jones founded the Center for Adaptive Systems Applications (CASA) in 1995, focusing primarily in assisting clients in the financial sector predict and protect against risk.
In April 1999, Complexica signed a strategic partnership agreement with BiosGroup, a joint venture of Ernst and Young's Center for Business Innovation. In March 2000 Complexica and BiosGroup created CommodiCast, Inc., a complexity-based company that provides commodity price forecasting for hedgers and speculators. In the summer of 2001 Complexica formed Assuratech to commercialize capital flow modeling tools.
Dr. Jones received a Los Alamos Distinguished Performance Award for work associated with development and application of his inventions.
A BiosGroup fellow, Dr. Jones has authored numerous published works including scientific papers in the fields of Classical, Quantum, and Relativistic Plasma Physics; Elementary Particle Physics; Biophysics; Finance; Machine Learning; Automated Adaptive Control; Nuclear Fusion; Banking; and Laser-Matter Interaction including medical applications to angioplasty and lithotripsy of kidney stones and gallstones. He also serves as board member for Santa Fe Economic Development, Inc.
Bill Kahn is the Chief Scoring Officer for Capital One Financial. In
that role, Bill leads the governance and quality of statistics across the
organization. Prior jobs have included significant stints in both
financial services strategy consulting and industrial statistics.
He has his BA in Physics and MA in Statistics both from U.C. Berkeley and his Ph.D. in Statistics from Yale.
Hobbies include recreational juggling, slow jogging, and flying his Cessna 182.
Dr. Dmitri Kuznetsov is Senior Statistical Consultant in Expert Team
of Sigma Marketing Group. He has Ph.D. degree in theoretical physics and
mathematics from Moscow State University. Dr. Kuznetsov is an author of
over 60 papers in various journals. He has a joint experience in academic
and business environments: consulting at Sigma Marketing Group, KSS Group,
and supermarket chain Giant Eagle; and research at University of
Pittsburgh, University of Waterloo (Canada), and Institute of Russian
Academy of Sciences.
Larry S. Lai has more than 20 years of experience in data mining and
customized modeling. He is currently, the Director of Principle Statistics
at DIRECTV, Inc., where he primarily works on projects related to churn
prediction, modeling and analysis for CRM activities, and data mining for
target marketing. He also teaches the class, "Data Mining and Database
Marketing" for MBA program at Loyola Marymount University. Previous to
DIRECTV, Lai was a Senior Statistician at Household Credit Services, Inc.,
where he worked on Delinquency and Bankruptcy Prediction and modeling and
analysis for target marketing, and at Applied Statistician at Loral
Aerospace (Formerly Ford Aerospace), where he worked on manufacturing
simulation, Total Quality Management implementation, and yield modeling and
analysis.
Lai has his Ph.D. Mathematics/Statistics from UCLA.
Daymond Ling is the Director, Modeling & Analytics at Canadian
Imperial Bank of Commerce. Daymond's group is responsible for generating
high quality sales leads, ensuring effective direct marketing spend, and
customer centric analysis across the majority of the bank's lines of
business and sales channels. He is also heavily involved in the
architecture and business processes of CIBC's CRM platform.
Prior to CIBC, Daymond worked for American Express Canada in Risk Management with focus on New Accounts, Authorizations, Credit, Collection, and Fraud.
Daymond has over 20 years of experience in Data Mining and System Technology, focusing on bringing about real world business impact and process improvements.
Daymond has a BS in Physics and a MS in Operations Research, both from University of British Columbia.
Professor Huan Liu of Computer Science and Engineering at Arizona
State University researches and teaches data mining, machine learning, and
artificial intelligence and their applications to real-world problems.
Before joining ASU, he conducted research at Telecom Australia Research
Laboratories, and taught at School of Computing at National University of
Singapore. He has published books and technical papers on data
preprocessing techniques on feature selection, extraction, and
construction, and instance selection for data mining applications. He
actively collaborates with researchers and practitioners in different
disciplines and in industry in the areas of data mining, machine learning,
data reduction, customer relation management, bioinformatics, and
intelligent systems. Professor Liu served on the program committee of
numerous conferences and is on the editorial board of professional
journals. He received his M.S. and Ph.D degrees from University of
Southern California. He is a member of ACM, AAAI, and a senior member of
IEEE.
David Madigan, Ph.D. (Investigator) is Professor of Statistics and
Director of the Institute of Biostatistics at Rutgers University. He
previously worked for SkillSoft, KPMG, Soliloquy, and the University of
Washington. He received a Ph.D. in Statistics from Trinity College
Dublin. Professor Madigan's research interests include Bayesian text
mining, large-scale Bayesian data analysis, and probabilistic graphical
models. He has published more than 70 technical papers. He is currently
an Action Editor for the Journal of Machine Learning Research and is the
2005 Program Chair for the Institute of Mathematical Statistics. He is a
Fellow of the American Statistical Association.
Edward C. Malthouse is an associate professor of Integrated Marketing
Communications at the Medill School of Journalism. He is an expert in data
mining and market research. He presented at M2001 and M2002. His primary
research is in the area of database marketing. He develop statistical
models and applies them to large data sets of consumer information to help
managers make marketing decisions. The primary application areas of his
models include market segmentation and targeting, and direct marketing. He
has also served as a consultant for leading companies including the
Advanta, Discover, Sachs Group, Marketing Solutions, Bell Laboratories,
Digital Equipment Corporation. He received his Ph.D. in statistics from
Northwestern University, an M.Sc. in operational research from Southampton
University, and a B.A. in mathematics from Augustana College.
Manya Mayes, as product manager for SAS Text Miner, is responsible for
strategy and direction of the SAS Text Mining product. In addition, Manya
has 5 years experience of text and data mining consulting for
manufacturing, financial, marketing and retail companies and has been using
SAS Text Miner since its inception in 1998. Manya has a graduate degree
from the University of Waikato, NZ and 14 years SAS experience in NZ,
England and the US.
Manya has been working for SAS for over 9 years. During this time she has been employed by: SAS UK, Technical Support Division providing first line support for SAS statistical products, second line support for all other SAS products and taught public course materials; SAS NZ as a Systems Engineer where she provided support for sales staff as well as support for consulting, public training and technical support; and SAS Cary Headquarters as an Analytical Consultant for 5 years and Text Miner Product Manager for 2 years.
Sreelatha Meleth, MA, MS, MS, Ph.D. is a Research Assistant Professor and
Biostatistician in the Comprehensive Cancer Center (CCC) at UAB. Besides
her doctoral degree in Applied Statistics from the University of Alabama
(Tuscaloosa), she has two MS degrees, one in Epidemiology and
Biostatistics, another in Applied Statistics. She also has a master's
degree in English Literature.
Her research interests include longitudinal data analysis, time series analysis, microarray data analysis regression techniques, missing data issues, and proteomic data analysis (2D gel and SELDI chip). In proteomics, her research interests include the effect of pre-processing on subsequent analyses, feature selection and pattern discovery.
She is currently involved as a statistician in a number of NIH funded projects at UAB. She has also worked as a consultant statistician since 1995.
Brendan Murphy is a Lecturer in Statistics at the Department of
Statistics in Trinity College Dublin, Ireland. He has held this position
since completing his Ph.D. in Statistics at Yale University in 1999.
His research interests include mixture models, classification, cluster analysis, and Bayesian statistics. His current research includes the development of statistical models for ranking (or preference) data. These methods are being applied to the analysis of Irish college applications and Irish election data.
He has served as a consultant on many projects in medicine, engineering, science and the social sciences.
Jerry Oglesby is the Director of SAS' Higher Education Consulting
group at the company. Located within the Education Division at SAS, Higher
Education Consulting works with universities and community colleges from
around the country to incorporate SAS technology into their curriculums. As
a former university professor and statistician at the University of West
Florida, Jerry Oglesby has extensive knowledge of the use of SAS in
institutions of higher learning. Prior to his appointment as director of
Higher Education Consulting, Oglesby held positions as the director of
analytical consulting and statistical training at SAS. He received his
Ph.D. in statistics from Texas A&M.
Will Potts has 15 years experience as a statistical consultant in
science and industry. Currently, he is the Chief Statistician at Data
Miners, Inc. where he collaborates on data analysis projects for clients
from many industries. Will Potts is the developer of several popular
training courses including Survival Data Mining, Neural Network Modeling,
and Predictive Modeling using Logistic Regression. Prior to Data Miners,
Will was the Co-Director of the Biometrical Consulting Service at the
Beltsville Agricultural Research Center, a Senior Biostatistician at the
Cleveland Clinic Foundation, and a Statistical Services Specialist at SAS
Institute.
David Press is Principal Consultant of Greenbrier & Russell's Advisory
Services practice. During his eighteen years he has performed various roles
leading company strategic business transformation efforts while performing
traditional leadership roles in IT Management, Product Management,
Marketing, and Solutions Delivery. David has worked for Fortune 500
companies, Software and Technology Services companies, and Professional
Services firms with an emphasis on technology solution strategy,
architecture, and delivery. During his tenure with Bank One, David led
certain application upgrades for its banking platform outsourcing division.
He also performed more strategic roles as implementation manager for
Systematics' Facilities Management Outsourcing division which concentrated
on delivering hosted applications to financial services institutions
worldwide.
Through the 1990's David moved from designing, delivering, and supporting banking and billing applications to the re-engineering of customer sales and service models(specifically inbound/outbound contact centers) and then to roles where the focus became internet enablement, retailization, customer intelligence and marketing automation.
David has led business strategy initiatives for Systematics and ALLTEL Corp. where the objectives were to transform their products and services offerings based on market shifts and technology innovations. These initiatives exposed David to Business and Technology strategy planning efforts for ALLTEL and its technology services clients. As Chief Solutions Strategist, David led ALLTEL's e-Business solutions strategy and development efforts which served the Financial Services, Communications, and Emerging Technologies verticals. During this time his teams' accomplishments ranged from establishing new technical architectures and methodologies to the delivery of emerging technology solutions ranging from payment exchanges to wireless-web applications.
Until his recent arrival at Greenbrier and Russel he most recently led the delivery of micro-marketing process and technology infrastructure delivery in multiple industries(manufacturing, retail, communications, and eCommerce). These types of engagements ranged from mass to micro marketing culture shift to campaign management system deployment. In those engagements he managed marketers and marketing analysts to deliver marketing solutions to clients. Those solutions spanned from the development of research instruments and market data products to custom analytics and large-scale business intelligence infrastructures. He also has been responsible for market, marketing, and product strategy for both a software delivery firm and a marketing services consulting firm.
He has worked with such companies as Siebel, SAS, Rational, IBM, Sybase, NCR/Teradata, Oracle, Vitria, BEA, Convergys, Fidelity National Financial, Acxiom, Experian, IMR/Market Facts, Checkfree, Portal Billing Software, Narus, Metasolv, IRI, Unica, Nielson, Plumtree, Teracore, SmartFocus, Sigma, Metavante, Intellidata, Syntellect, Nortel, Avaya, Edify, Quaero, Business Objects, and Hyperion. In many of those engagements, he was involved in developing some of these companies solutions strategies as well as the delivery of those solutions to end customers.
David has consulted to Financial Institutions, Retailers, Manufacturers, Software and Services Vendors, Energy Providers, Communications companies, and emerging technology start-ups. These engagements range from strategic business and technology planning to CRM, Billing, Payment, and Business Intelligence process and technology transformation. David serves as an advisor to startups in the analytics services arena and is also a regular speaker/lecturer with industry associations including The Data Warehousing Institute, The Cellular Telephone Industry Association, The International Quality and Productivity Center, Chicago Software Association, NACHA, and the United States Telecom Association.
Bruce Ratner, Ph.D. is a recognized authority in analysis and modeling in the DM-space (direct/database marketing {DDBM}, customer relationship management {CRM}, and (knowledge discovery/data mining {KDD}). He has a doctorate in statistics, with a concentration in multivariate statistics and response model simulation. He is active in the direct marketing industry, both as a frequent lecturer at Direct Marketing Association (DMA) conferences and as an instructor of the Advanced Statistics course sponsored by the DMA.
Dr. Ratner's latest book Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data has experienced the fastest climb up the Amazon Sales Rank within its content domain. Bruce is also the co-author of The New Direct Marketing, a text widely studied by direct marketing practitioners, and the author of the DM STAT-1 Newsletter, the only online information exchange about quantitative methods in the DM-space.
Dr. Ratner is President and Founder of DM STAT-1 CONSULTING, the leading firm for analysis and modeling in the DM community, specializing in statistical methods and knowledge discovery and data mining tools. Since 1986, Bruce has applied his expertise in the areas of banking, insurance, finance, retail, telecommunications, health care, pharmaceutical, publication & circulation, mass & direct advertising, catalog marketing, e-commerce, web-mining, B2B, and CRM-business. Bruce holds a patent for the unique application in solving the two-group classification problem with genetic programming.
Brett Russ has worked at Blue Cross and Blue Shield of North
Carolina for the past six years, most recently as a Decision Support
Consultant in the Product and Market Intelligence department. The mission
of Market Intelligence is to provide all of Sales & Marketing with
ACTIONABLE Marketing Intelligence about existing and potential employee
groups and members. In his previous positions within the company, Brett
served as a Lead Developer and as a Manager in the IT department, and as a
Decision Support Consultant in the Corporate Data Warehouse. He has fifteen
years of IT experience and holds a Bachelor's degree in Information Systems
and Finance from Appalachian State University.
Vineet Singh is the world-wide global practice principal for
Business Intelligence solutions in HP Services' Consulting & Integration
organization. He has 25 years of experience in services and
software/systems R&D with 14 years in industrial research labs (HP Labs,
IBM Research, MCC, Hitachi America, and Schlumberger). He has done
extensive research and software system development in analytical CRM,
marketing, e-commerce, data mining, optimization, statistics, high
performance computing, parallel processing, object-oriented languages,
artificial intelligence, distributed systems, and computer networking. He
has been awarded 6 patents and has 4 patents pending in data mining,
e-commerce, and collaboration systems. He has written more than 30 research
publications with many in leading refereed journals. He holds a PhD from
Stanford University, an MS from MIT, and a BS from IIT Kanpur.
Robert A. Stine is
Professor of Statistics at the Wharton School of the University of
Pennsylvania.
Professor Stine's research in statistics spans a variety of areas with practical applications. Some of his work has focused on the development of tools for building and assessing forecasts from models of time series data. This research ranges from derivations of abstract, theoretical properties of these methods to their application in various marketing, financial, and clinical problems. His most recent research considers methods for selecting statistical models, with particular relevance to the selection of important predictive features from large datasets. These methods are particularly important in the development of predictive models for credit behavior. His research has appeared in numerous academic journals, including the Journal of the American Statistical Association and the Annals of Statistics.
Steve Tanner is currently a Senior Research Scientist with the
Information Technology and Systems Center at The University of Alabama in
Huntsville. In that role, he is supporting a number of projects including
a National Science Foundation funded project entitled Linked Environments
for Atmospheric Discovery (LEAD), an Air Force project for the use of data
mining and artificial intelligence in military war games, and a sensor
network effort for on-board data mining for the Defense Intelligence Agency
(MASINT). He has worked on numerous advanced computing research and
development efforts for commercial, space and military projects including
the Teledesic Satellite program, the Air Force's Joint Strike Fighter
program, and several of NASA's Earth Science efforts. He has directed
several computer research groups for Boeing, Intergraph, General Research
Corporation, and UAH. He has also been involved in many data base
development and assessment projects. He earned a BA in Mathematics from
the University of Colorado in Boulder, a Masters in Computer Science from
the University of Alabama in Huntsville, and is currently pursuing a Ph.D.
in Sensor Networks.
Dr. Marietta Tretter is currently a Professor and Assistant
Department Head of the Department of Information and Operations Management
in the Mays Business School at Texas A&M University. She has developed
Data Mining and Data Warehousing courses at Texas A&M University. In
summer, for the past 12 years, she has lead National Sierra club Service
Trips that work with the Bureau of Land Management in recording rock art
sites in Utah and Arizona. She is also involved in the Texas Rock Art
Database project.
Her publications have appeared in Annals of Statistics, Management Science, Siam Journal on Scientific Computing, Operations Research, Academy of Management Journal and others. She has a lot of diverse interests that seem to have found a home in Data Mining.
Phil Corrin |
His consulting experience has included working for clients in the automotive, ISP, grocery, wireless, retail, PC/server and consumer software industries. He has successfully managed application development teams, created system architecture, developed new analytical methodologies and estimated complex models. He has leveraged techniques including text mining, response modeling, segmentation and survival data mining. He holds an MBA in Decision Science from the George Washington University.
Andreas Weigend has a unique career bridging between the disciplines
of computer science, statistics and business in the areas of data mining,
machine learning, and time series prediction. His recent work focuses on
behavioral modeling of online customers and of financial traders.
As Amazon.com's Chief Scientist, he directed research in data mining, statistical learning, and computational marketing. In 1999, he co-founded Moodlogic and built the prototype for the system that was voted "best music organizer" by C|NET in 2003. He also was the Chief Scientist of ShockMarket Corporation, funded by D.E. Shaw and Deutsche Bank, to create information products and trading models based on real-time data from online brokerages, leveraging principles of behavioral finance.
He has published more than one hundred scientific papers and co-authored six books, including Time Series Prediction (1993) and Computational Finance (1999). He teaches Data Mining and Electronic Business at Stanford University, as well as executive courses on e-commerce and quantitative methods. Previously, he was full-time faculty at New York University's Stern School of Business and at the University of Colorado at Boulder.
He serves on the advisory boards of several startups and hedge funds, and has consulted for Acxiom, Bank of America, Bertelsmann Venture Capital, Goldman Sachs, J.P. Morgan, Morgan Stanley, Nikko Securities, PlanetOut, Siemens, UBS, Yahoo, and others. Details are at www.weigend.com.
Andreas Weigend studied electrical engineering, physics, and philosophy at Karlsruhe, Cambridge (Trinity College), and Bonn University. He received his Ph.D. from Stanford University in physics, and was a researcher at Xerox PARC (Palo Alto Research Center) and at the Santa Fe Institute.
Cary White is the Data Warehouse Development Team Project Manager
for the University of North Carolina at Chapel Hill. He has over 20 years
of experience as an IT developer and project manager. For the last four
years, Cary has worked on the development of an enterprise-wide data
warehouse for UNC-CH. Prior to that, he designed, developed, implemented
and supported HR, Payroll and Accounting applications. In a previous
career, he was an instructor at a small college. Cary holds an MA in
Sociology from Duke University and a BA from Davidson College.
What participants say about the M-series:
"The educational content, exchange of ideas, and intellectual environment I found at the conference exceeded my expectations and confirmed SAS' place as the premier data mining conference in the world."
Thad Perry, Ph.D.
Senior Director of Infomatics
"SAS is doing a tremendous service for the data mining community. The conference provides an excellent forum for exchanging ideas and best practices in business and a stage for sharing the latest and best academic research in the field."
Jaideep Srivastava
Professor of Computer Science and Engineering
University of Minnesota
"This was a superb environment - one of the smartest conference venues I have experienced (and I have experienced a lot). The talks went into greater depth than the talks at many such meetings. Many of the talks were particularly valuable in shedding light on different application areas of data mining."
David Hand
Professor and Head of Statistics
Imperial College, London
"This conference is definitely a must. Not only for the information, but for the opportunity it provides to exchange ideas and learn from your colleagues."
Daryl Berry
T-Mobile US
"The information I got from the presentations was great, and it was nice to talk to and exchange experiences with professionals who are pretty much doing the same thing."
Victor Alonso
Zurich Insurance Co
"What really impressed me was the sense of community that normally isn't present at conferences of this size."
Brij Masand
Data Miners
"The conference has opened a whole new world for me."
Rachel Alt-Simmons
Hartford Life Insurance
