DM-HI 2010 - 5th INFORMS Workshop on Data Mining and Health Informatics (INFORMS DM-HI 2010)

The Data Mining (DM), Artificial Intelligence (AI) and Health Applications (HA) subdivisions of INFORMS are jointly organizing the workshop in conjunction with the 2010 INFORMS Annual Meeting. The previous four workshops were well received in terms of number of presentations as well as attendances. The attendees showed strong interest in future workshops following a similar format. The objectives of this workshop are to:

? Present state-of-the-art research and practice of health care applications
? Encourage research collaboration among DM, AI and HA members.
? Publicize the existence of the DM, AI and HA subdivisions at INFORMS and attract new members within and beyond INFORMS.

Thanks to our Sponsors

The workshop will consist of two parallel tracks, a health care applications track and a data mining research track. Each track will consist of at least two morning sessions and two afternoon sessions, and each session will consist of three or four presentations. A plenary speaker will be scheduled over lunch.

Call for Papers
The theme of the workshop centers around health informatics, and topics of interest include, but are not limited to:

Foundations of Data Mining and Artificial Intelligence
AI/DM in Operations Research and Operations Management
Machine Learning and Statistical Learning Algorithms
Bioinformatics
Pattern Recognition
Natural Language Processing
Intelligent Information Retrieval
Visualization
Healthcare DM and Knowledge Discovery
Healthcare Logistics
Healthcare Simulations
Patient Flow Modeling
Medical Imaging
Medical Decision Making
Biosurveillance, Healthcare and Public Health Surveillance
Disease Modeling and Prevention
Disease Spread and Transmission Simulations
Multi-Agent Systems
Risk Management
Global Health
Case Studies

On behalf of the INFORMS-DM-HI 2010 Organizing Committee, we would like to invite you to submit an abstract, not exceeding 200 words, for review. Two members of the Organizing Committee will review the abstracts. Authors of accepted abstracts will be expected to give a presentation at the workshop and submit a short paper, not exceeding six (6) pages, for the workshop proceedings, to be published on a CD. Authors are encouraged to submit a longer, high quality version of their workshop papers to the international journal Annals of Operations Research, special issue on "Data Mining and Informatics." Please see the Call for Papers on the journal website: www.springer.com/journal/10479.

Click here to submit your abstract

Time line:
May 15 200-word abstracts due
June 15 Acceptance decisions sent out
Sept. 30 Proceedings papers due
Nov. 6 Workshop

For questions about the workshop, contact Program Co-Chairs Durai Sundaramoorthi, dsundaramoorthi-AT-missouriwestern.edu, Mariel S. Lavieri, lavieri-AT-umich.edu or Huimin (Min) Zhao, hzhao-AT-uwm.edu.

Workshop Committee
The Program Co-Chairs will lead the organization of the workshop with feedback from the entire committee. The Workshop Co-Chairs will coordinate logistics with INFORMS, including registration, program, facilities and catering. The Proceedings Chair will organize the structure of the workshop proceedings, facilitate distribution of the proceedings, and coordinate the special journal issue. Finally, the Review Committee Chairs will coordinate the review of abstracts submitted for the Workshop.

Program Co-Chair Durai Sundaramoorthi, PhD is an Assistant Professor in Steven L. Craig School of Business at Missouri Western State University (MWSU). He teaches courses in Management Science and Statistics. Prior to this position, he was a faculty in the Engineering management department at Missouri University of Science & Technology (formerly University of Missouri-Rolla). He received his PhD in Industrial Engineering from the University of Texas at Arlington in 2007. He performed his doctoral research in the Center on Stochastic Modeling, Optimization, and Statistics (COSMOS). He also has a M.S. in Industrial Engineering from the University of Texas at Arlington and a B.S. in Mechanical Engineering from Bharathiar University, India. His research interests include Data Mining, Optimization, Simulation, and Simulation-based Optimization applied to diverse applications. He developed SIMNA, a simulation of nurse activity, for the purpose of evaluating assignments from different nurse-patient assignment policies. He has worked on process improvement projects at Heartland Regional Medical Center, FedEx, GE, and Thomas & Betts that utilized data mining, simulation, and optimization. He is a member of Institute for Operations Research and the Management Sciences (INFORMS), Decision Sciences Institute (DSI), and Institute for Industrial Engineering (IIE).

Program Co-Chair Mariel S. Lavieri, PhD is an Assistant Professor in the Industrial and Operations Engineering Department at the University of Michigan. She has a B.Sc. in Industrial and Systems Engineering and a B.A. in Statistics from the University of Florida. She received her MSc and PhD in Management Science from the University of British Columbia. Her most recent research focuses on medical decision-making, in particular on determining optimal treatment protocols by explicitly modeling stochastic disease progression. She has also developed models for health workforce planning, which take into account training requirements, workforce attrition, capacity planning, promotion rules and learning. Dr. Lavieri is the recipient of both the Bonder Scholarship as well as the Pierskalla Award from the Health Applications Section. She is a member of the Institute for Operations Research and the Management Sciences (INFORMS) and the Institute for Industrial Engineering (IIE).

Program Co-Chair Huimin (Min) Zhao, PhD is an Associate Professor of Management Information Systems at the Sheldon B. Lubar School of Business, University of Wisconsin-Milwaukee. He earned his PhD in Management Information Systems from The University of Arizona. His current research interests are in the areas of data mining, data integration, and medical informatics. His research has been published in several journals, including Communications of the ACM, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Systems, Man, and Cybernetics, Information Systems, Data and Knowledge Engineering, Journal of Management Information Systems, and Decision Support Systems. He serves on the editorial review board of the Journal of Database Management. He served as a co-chair of the 19th Workshop on Information Technologies and Systems (WITS) in 2009. He is a member of the Institute for Operations Research and the Management Sciences Information Systems Society (INFORMS ISS), Association for Information Systems (AIS), Information Resources Management Association (IRMA), and Institute of Electrical and Electronics Engineers, Inc. (IEEE).

Management Committee Member Kwok-Leung Tsui, PhD is a professor in the School of Industrial and Systems Engineering at Georgia Institute of Technology. He has a B.Sc. in Chemistry and an M.Ph. in Mathematics both from the Chinese University of Hong Kong, and a Ph.D. in Statistics from the University of Wisconsin at Madison. He had worked in the Quality Assurance Center of AT&T Bell Laboratories before joining Georgia Tech in 1990. Dr. Tsui is a (elected) fellow of American Statistical Association and was a recipient of the 1992 NSF Young Investigator Award. He was the (elected) President and Vice President of the American Statistical Association Atlanta Chapter in 1992-1993, the chair of the INFORMS Section in the Quality, Statistics, and Reliability (QSR) in 2000, and the founding chair of the INFORMS Section in Data Mining (DM), in 2004. Dr. Tsui is also a US representative in the ISO Technical Committee on Statistical Methods (TC 69). He is currently the departmental editor of the IIE Transactions and on the editorial board of Journal of Quality Technology and International Journal of Reliability, Quality, and Safety Engineering.

Management Committee Member Victoria Chen, PhD an Associate Professor in the Department of Industrial and Manufacturing Systems Engineering at the University of Texas at Arlington. She received her Bachelors degree in Mathematical Sciences from the Johns Hopkins University, and she received her Masters and Doctoral degrees from the School of Operations Research and Industrial Engineering at Cornell University. She has been an active member of INFORMS (formerly ORSA) since 1987, serving terms as President of the student sections at both her undergraduate and graduate institutions, and co-founding the Informs DM Section in 2003. She served as DM Secretary-Treasurer in its founding year, DM Vice-Chair in 2004-05, and she is currently DM Chair. Her research is a cross-disciplinary mix of statistics, optimization, logistics, engineering, and sustainability, and has been funded by the U.S. Environmental Protection Agency, the National Science Foundation, and several companies.

Management Committee Member George C. Runger, PhD is a Professor in the department of Industrial Engineering at Arizona State University. His research is on real-time monitoring and control, data mining, and other data-analysis methods with a focus on large, complex, multivariate data streams. His work is funded by grants from the National Science Foundation and corporations. In addition to academic work, he was a senior engineer at IBM. He holds degrees in industrial engineering and statistics.

Management Committee Member S. Tom Au, PhD is an Executive Director of Research in AT&T Labs, Information and Software System Research. He manages a department of statisticians, economists and computer scientists on large-scale data mining research and applications related to telecommunications. Current applied data mining research includes spatial and temporal event detection, churn/appetency/up-selling predictive modeling, technology migration modeling, forecasting and seasonal decomposition via data mining, and wallet estimation. He has a BS in mathematics from the Chinese University of Hong Kong, and a MS and PhD in statistics from Yale University. He joined the Business Analysis Center of AT&T Bell Laboratories in 1984, and was promoted to Distinguished Member of Technical Staff and then Technology Leader. He led a team winning the Large AUC task during the 2009 Australia Data Mining Analytical Challenge competition. He was the chair of the INFORMS Section in Data Mining in 2005, and a committee member of the INFORMS Data Mining competition in 2008. He was also a committee member for the INFORMS Data Mining Workshop in 2009 and 2010.

Management Committee
Kwok-Leung Tsui, Georgia Institute of Technology
Tory Chen, University of Texas at Arlington
George Runger, Arizona State University
Tom Au, AT&T Labs

Review Committee
Margret Bjarnadottir, Stanford University
Nick Street, University of Iowa
Nan Liu, Columbia University
Elizabeth Cudney, Missouri University of Science & Technology
Benjamin Armbruster, Northwestern University
Bin Zhu, Boston University
Raj Sharman, University of Buffalo
Alan Wang, Virginia Tech
Kalyan Pasupathy, University of Missouri