Richard J. Roiger. Home: Cell:

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1 Richard J. Roiger Home: Cell: Degrees Ph.D., Computer Science, 1991, University of Minnesota M.S., Mathematics, 1976, Mankato State University B.S., Mathematics, 1970, Magna Cum Laude, Mankato State University Employment 2011 Present Professor, Computer Science, Minnesota State University, Mankato, Minnesota Professor, Computer and Information Sciences, Minnesota State University, Mankato, Minnesota Associate Professor, Computer and Information Sciences, Minnesota State University, Mankato, Minnesota Assistant Professor, Computer and Information Sciences, Minnesota State University, Mankato, Minnesota Instructor, Computer and Information Sciences, Minnesota State University, Mankato, Minnesota High School Mathematics Teacher, LeCenter, Minnesota. Professional Services/Consulting 2007 Present Financial Consultant and Board Member: Retired Education Association of Minnesota Present Editorial Staff: Door to Hope Ministries Data Mining Consultant & Software Engineer, Information Acumen Corporation, Maple Grove, MN. Current Memberships Association of Computing Machinery American Association of Artificial Intelligence Current Research Interests Data Mining & Knowledge Discovery, Machine Learning

2 Publications Books Roiger, R. J. and M. W. Geatz, Data Mining A Tutorial-Based Primer, Addison-Wesley Publishing, Journal Papers Hakkila, Jon, Giblin Timothy W., Young Kevin C., Fuller Stephen P., Peters Christopher D., Nolan Chris, Sonnett Sara M., Haglin David J., and Roiger Richard J., A Gamma-Ray Burst Database of BATSE Spectral Lag and Internal Luminosity Function Values, The Astrophysical Journal Supplement Series, vol. 169 no. 1, pp , Haglin, D.J. and R. J. Roiger, A Tool for Public Analysis of Scientific Data, Data Science Journal, vol. 4, pp , Hakkila, J., T. W. Giblin, K. Young, D.J. Haglin, R. J. Roiger, J. P. Norris and J. D. Bonnell, Probing GRB Jet Structure from Prompt Emission, vol. 5 suppl, pp , Hakkila, J., T. W. Giblin, R. J. Roiger, D. J. Haglin, W. S. Paciesas, and C. A. Meegan, "Sample Completeness Affects Gamma-Ray Burst Classification," Astrophysical Journal, vol. 582, pp ,2003. Hakkila, J., D. J. Haglin, G. N. Pendleton, R. S. Mallozzi, C. A. Meegan, and R. J. Roiger, Gamma-Ray Burst Class Properties, Astrophysical Journal, vol. 538, pp , Marshall, L. L. and R. J. Roiger, "Substance User MMPI-2 Profiles: Predicting Treatment Failure," International Journal of Addictions, vol. 31 (2), pp , Roiger, R.J. "EX-WEB: An Exemplar-Based Approach to Incremental Concept Formation", Heuristics: The Journal of Knowledge Engineering and Technology, vol 6 (4), Winter Roiger, R.J. "An Exemplar-Based Approach to Concept Learning", AISB Quarterly (Special Issue on AI in Medicine), Winter 1992/93, pp Conference Papers Roiger, R.J., M.L. Miller, J. Morgan, F. Hudson, Treatment Outcome for Patients with Low Back Injuries, in Proceedings of the 2007 International Conference On Data Mining, eds. R. Stahlbock, S. F. Crone, & S. Lessmann (CSREA Press), pp , June Roiger, R.J., Teaching an Introductory Course in Data Mining, in Proceedings of the 10 th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education, ACM Special Interest Group on Computer Science Education, Universidade Nova de Lisboa, June 27-29, Hakkila, J., T. W. Giblin, W. S. Paciesas, R. J. Roiger, D. J. Haglin, & C. A. Meegan, Comments on Anisotropic Distributions of Faint BATSE GRBs, in Gamma-Ray Burst and Afterglow Astronomy 2001, eds. G. R. Ricker and R. K. Vanderspek (AIP: New York), pp , Hakkila, J., T. W. Giblin, T. M. Freismuth, K. C. Young, A. J. Sprague, A. D. Stallworth, R. J. Roiger, & D. J. Haglin, The Internal Luminosity Functions of BATSE 5B GRBs, in Gamma-Ray Burst and Afterglow Astronomy 2001, eds. G. R. Ricker and R. K. Vanderspek (AIP: New York), pp , 2001.

3 Hakkila, J., R. J. Roiger, D. J. Haglin, T. W. Giblin, & W. S. Paciesas, A Comparison of Unsupervised Classifiers on BATSE Catalog Data, in Gamma-Ray Burst and Afterglow Astronomy 2001, eds. G. R. Ricker and R. K. Vanderspek (AIP: New York), pp , Hakkila, J., D. J. Haglin, R. J. Roiger, T. W. Giblin, & W. S. Paciesas, An Update on the GRB ToolSHED Project Status, in Gamma-Ray Burst and Afterglow Astronomy 2001, eds. G. R. Ricker and R. K. Vanderspek (AIP: New York), pp , Haglin D.J., R. J. Roiger, J. Hakkila, and T.W. Giblin, Data Mining from a Web Browser, in International Conference on Advances in Infrastructure for Electronic Business, Science and Education, August, Hakkila, J., T. W. Giblin, R. J. Roiger, D. J. Haglin, W. S. Paciesas & C. A. Meegan, "The Dual Timescale Peak Flux and GRB Classess," in GAIA Spectroscopy, Science and Technology, Vol XXX, Hakkila, J., R.S. Mallozzi, R.J. Roiger, D.J. Haglin, G.N. Pendleton, and C.A. Meegan, "Tools for Gamma-Ray Burst Data Mining", Gamma-Ray Bursts in the Afterglow Era: 2 nd Workshop (Springer: Berlin), eds. E. costa, F. Frontera, & J. Hjorth, pp , Hakkila, J., R. J. Roiger, D. J. Haglin, T. Giblin, & W. S. Paciesas, How Data Mining Helps Expose Gamma-Ray Burst Properties and Instrumental Biases, in World Multiconference on Systemics, Cybernetics and Informatics, July, Hakkila, J., R. J. Roiger, D. J. Haglin, R. S. Mallozzi, G. N. Pendleton, & C. A. Meegan, Mining Gamma-Ray Burst Data, in Mining the Sky, ed. A. Banday, in press. Haglin, David J., Richard J. Roiger, Jon Hakkila, Geoffrey Pendleton, and Robert Mallozzi, A GRB Tool Shed, in Gamma-Ray Bursts: 5th Huntsville Symposium, ed. R.M. Kippen, et al., pp , Hakkila J., C. A. Meegan, G. N. Pendleton, R. S. Mallozzi, D. J. Haglin, & R. J. Roiger, The Fluence Duration Bias, in Gamma-Ray Bursts: 5th Huntsville Symposium, ed. R.M. Kippen, et al., pp , Roiger, Richard J., Jon Hakkila, David J. haglin, Geoffrey N. Pendleton, and Robert S. Mallozzi, Unsupervised Induction and Gamma-Ray Burst Classification, in Gamma-Ray Bursts: 5th Huntsville Symposium, ed. R.M. Kippen, et al., pp , Hakkila, Jon, David J. Haglin, Richard J. Roiger, Robert S. Mallozzi, Geoffrey N. Pendleton, and Charles A. Meegan, Properties of Gamma-Ray Burst Classes, in Gamma-Ray Bursts: 5th Huntsville Symposium, ed. R.M. Kippen, et al., pp , Roiger, R.J., M.W. Geatz, D.J. Haglin, and J. Hakkila, ESX -- A Tool for Knowledge Discovery, in Proceedings of the Federal Data Mining Symposium & Exposition '99, ed. W.T. Price, AFCEA International, Fairfax VA., pp , March 9-10, Hakkila, Jon., David J. Haglin, Richard J. Roiger, Robert S. Mallozzi, Geoffrey N. Pendleton, and Charles A. Meegan, AI Gamma-Ray Burst Classification: Methodology/Preliminary Results, in Fourth Huntsville Gamma-Ray Burst Symposium, eds.c.a. Meegan, P. Cushman, pp , Roiger, R.J., C. Azarbod, and R. R. Sant, A Majority Rules Approach to Data Mining, in Proceedings of the IASTED International Conference on Intelligent Information Systems, IEEE Computer Society, Los Alamitos, CA., pp , Dec Roiger, R. J. and L.D. Cornell, Selecting Training Instances for Supervised Classification, in Proceedings ISAI/IFIS, IEEE-TAB Products Group, pp , Nov., 1996.

4 Sant, R., R. J. Roiger, and C.H. Lee, Using non-statistical Induction Based Techniques for Financial Forecasting, in Proceedings ISAI/IFIS, IEEE-TAB Products Group, Nov. 1996, pp Miller, S.J. and R.J. Roiger, GenRules: A Model for Generating Production Rules from Conceptual Clusters, in Proceedings of the IASTED/ISMM, IASTED/ACTA Press, pp , June, Cornell, L.D., and R.J. Roiger, "An Introduction-Based Model for Remote Sensing Applications," in Proceedings of the 25th International Symposium on Remote Sensing and Global Change, Volume II, pp 23-32, April, Cornell, L.D., R.J. Roiger, "Automated Classification of Landsat Data Using an Induction-Based Model," in ASPRS Technical Papers: Remote Sensing, Volume II, ed. Anthony J. Lewis, February, Presentations/Conferences 2007 Presented Treatment Outcome for Patients with Low Back Injuries, at Treatment Outcome for Patients with Low Back Injuries, at the 2007 International Conference On Data Mining, Las Vegas Nevada,June Tutorial Presentation Teaching an Introductory Course in Data Mining, at the 10th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education, ACM Special Interest Group on Computer Science Education, Universidade Nova de Lisboa, June 27-29, Presented "Data Mining in Industry" at ADC Telecommunications, Eden Prairie, MN Presented "An Overview of Artificial Intelligence & Knowledge Discovery" at NASA space sciences Laboratory, Huntsville, Alabama Presented " ESX A Tool For Knowledge Discovery, at the AFCEA Federal Data Mining Symposium & Exposition 99 held in McLean Virginia Presented A Majority Rules Approach to Data Mining, at the IASTED International Conference on Intelligent Information Systems held in Freeport, The Bahamas Presented Selecting Training instances for Supervised Classification, at the 9th International Conference Symposium on Artificial Intelligence held in Cancun, Mexico Presented Using Non-Statistical Induction Based Techniques for Financial Forecasting, at the 9 th International Conference Symposium on Artificial Intelligence held in Cancun, Mexico Presented GenRules: A Model for Generating Production Rules from Conceptual Clusters, at the IASTED/ISMM International Conference on Intelligent Information Management Systems held in Washington D.C Presented "The Impact of Training Set Selection on Supervised Classification" at the 7th International Conference on Image Analysis and Processing held in Bari, Italy Presented "Automated Classification of Landsat Data Using an Induction Based Model" at the Annual Convention and Exposition of the American Congress on Surveying and Mapping (ACSM/ASPRS) held in New Orleans, Louisiana. Grants Hakkila, Giblin, Haglin, and Roiger, $130,279, RUI: Guiding Gamma-Ray Burst Classification with the KDD Process, National Science Foundation, AST , from August 1, 2001 to July 31, 2005.

5 Hakkila, Haglin, Roiger, Mallozzi, and Pendleton, $222,100, An Artificial Intelligence Classification Tool and Its Application to Gamma-Ray Bursts, NASA AISR , from February 1, 1999 to January 31, Rajiv Sant, Richard Roiger, and Chan Lee: Mankato State University Research Grant Using Non-Statistical Induction Based Techniques for Financial Forecasting., 1995.