Michael Steinbach,  Research Associate

Department of Computer Science and Engineering
University of Minnesota
4-192 EE/CS Building, 200 Union Street SE
Minneapolis, MN 55416

Office: EE/CS 5-225E
Phone: (612) 626-7503  Fax: (612) 625-0572
E-mail: steinbac (at) cs (dot) umn (dot) edu

Links:   teaching     research     publications     software    professional services     resume

Michael Steinbach earned his B.S. degree in Mathematics, a M.S. degree in Statistics, and M.S. and Ph.D. degrees in Computer Science from the University of Minnesota. He is currently a research associate in the Department of Computer Science and Engineering at the University of Minnesota, Twin Cities. Previously, he held a variety of software engineering, analysis, and design positions in industry at Silicon Biology, Racotek, and NCR. His research interests are in the area of data mining,  bioinformatics, and statistics.  He has authored over 20 research articles, and is a co-author of the data mining textbook, Introduction to Data Mining, published by Addison-Wesley. He is a member of the IEEE Computer Society and the ACM.



I am part of the data mining group of Professor Vipin Kumar.  We perform data mining research in a variety of areas. Two areas of focus are data mining for Earth science data and biological / biomedical data.


Click here for more information on support envelopes, including MATLAB code and a technical report.


Click here for a  list of my publications.

Introduction to Data Mining Introduction to Data Mining
Pang-Ning Tan, Michael Steinbach, Vipin Kumar
Addison-Wesley, 2005.

ISBN : 0321321367.

Professional Services

Program Committees


Journals:  Transactions on Knowledge Discovery from Data (TKDD), Transactions on Knowledge and Data Engineering, Transactions on Parallel and Distributed Systems, Journal of American Society of Information Science,  Transactions on Geoscience and Remote Sensing, IEEE Transactions on SMCB, VLDB Journal, Data and Knowledge Engineering

Conferences:  ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, SIAM International Conference on Data Mining, IEEE International Conference on Data Mining, Pacific-Asia Conference on Knowledge Discovery and Data Mining, ACM SIGMOD International Conference on Management of Data, International Conference on Machine Learning, International Conference on Data Engineering, Supercomputing