Curriculum Vitae of Chien-Chung Chan

 

Office Address

Department of Computer Science

University of Akron

Akron, OH 44325-4003

Office: CAS 228

Phone: (330) 972-8014

e-mail: chan@cs.uakron.edu

      www.cs.uakron.edu/~chan

Education

Taipei Institute of Technology, Electrical Engineering, Diploma, 1978

University of Kansas, Master of Computer Science, 1984

University of Kansas, Ph.D. of Computer Science, 1989

 

Research Interests

Knowledge Discovery and Data Mining

Distributed Decision Support Systems

Expert systems and uncertainty management

Rough sets, fuzzy sets, Dempster-Shafer theory, and Bayesian belief networks.

 

Teaching Interests

Multi-Tier Web-based programming

Artificial Intelligence, Expert Systems

Machine Learning, Soft Computing,

Database Systems, KDD, Data Mining

 

Professional Experience

   Aug., 2001 – Present:  Professor of Computer Science

   January, 2000 – August 2001: System architecture consultant, ZyxBio Company, Cleveland, Ohio.

   Aug., 1994 – Aug., 2001:  Associate Professor of Computer Science

   June, 1998 – Aug., 1999: Chief System architect and developer, Art-Van company, Taipei, Taiwan.

   Aug., 1989 – Aug., 1994:  Assistant Professor of Mathematical Sciences

   June, 1980 – June, 1982: Electrical Engineer, China Steel Corporation, Taiwan.

 

Publications

·       Khasawneh, N. and C.-C. Chan, “Active user-based and ontology-based web log data preprocessing for web usage mining,” Proceedings of IEEE/WIC/ACM WI-2006, December 18-22, Hong Kong, 2006.

·       Chan, C.-C. and Sivaraj Selvaraj, “Distributed approach to feature selection from very large data sets using BLEM2,” NAFIPS 2006, Int. Conf. of the North American Fuzzy Information Processing Society, June 3-6, Montreal, Quebec, Canada, 2006. ISBN 0-7803-9188-8 IEEE Catalog No. 05TH8815C, Library of Congress: 2006924074.

·       Shiao, Grace and C.-C. Chan, “Design of data analysis component for Microsoft SQL server 2000,” The University of Akron Conference on Undergraduate and Graduate Student Research, November 17, 2005, pp. 48.

·       Chan, C.-C. and Zhicheng Su, “From Data to Knowledge:  an Integrated Rule-Based Data Mining System,”  Proceedings of the 17th International Conference of Software Engineering and Knowledge Engineering, July 14 – 16, Taipei, 2005, pp. 508-513.

·       Khasawneh, N. and C.-C. Chan, “Web Usage Mining using Rough Sets,” NAFIPS 2005, Int. Conf. of the North American Fuzzy Information Processing Society, June 22-25, Ann Arbor, Michigan, pp. 580-585, ISBN 0-7803-9188-8 IEEE Catalog No. 05TH8815C.

·       Gundavarapu, M. and C.-C. Chan, “Learning rules from databases using SQL,” The University of Akron Conference on Undergraduate and Graduate Student Research, October 21, 2004, pp. 41.

·       Selvaraj, S. and C.-C. Chan, “Distributed approach for feature selection,” The University of Akron Conference on Undergraduate and Graduate Student Research, October 21, 2004, pp. 42.

·       Ouhammou, A. and C.-C. Chan, “Bioinformatics data retrieval components,” The University of Akron Conference on Undergraduate and Graduate Student Research, October 21, 2004, pp. 43.

·       Xu, T.H., Y.J. Lin, and C.-C. Chan, “A web-based product modelling tool – a preliminary development,” Int. J. of Advanced Manufacturing Technology, 21: 669-677, 2003.

·       Chan, C.-C. and S. Santhosh, “BLEM2: Learning Bayes’ rules from examples using rough sets,” Proc. NAFIPS 2003, 22nd Int. Conf. of the North American Fuzzy Information Processing Society, July 24 – 26, 2003, Chicago, Illinois, pp. 187-190.

·       Cheh, J.J. and C.-C. Chan, “Bankruptcy prediction by CART and LERS with quantification for data processing,” Proceedings AAA regional conference, 2003.

·       Lei, H., C.-C. Chan and J.J. Cheh, “Rule-based classifier for bankruptcy prediction,” Proc. 14th MidWest Artificial Intelligence and Cognitive Science Conference MAICS 2003, April 12 – 13, 2003, University of Cincinnati, Cincinnati, Ohio, pp. 74-81.

·       Batur, C., L. Zhou and C.-C. Chan, “Support vector machines for fault detection,” Proceedings of the 41st IEEE Control Design Conference,  ISBN# 0-7803-7516-5@2002IEEE, pp. 1355-1356, 2002.

·       Lin, Y.J., T.H. Xu and C.-C. Chan, “A web-based product modeling tool – a preliminary development,” Proc. 2002 Japan-USA Symposium on Flexible Automation, International Conference on New Technological Innovation for the 21st Century, Hiroshima, Japan, July 14 – 19, 2002, pp. 103-108.

·       Chan, C.-C., “Learning rules from very large databases: a rough multiset approach,” Proc. Ninth International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems, IPMU 2002, Annecy, France, July 1 – 5, 2002, pp. 235-242.

·       Chan, C.-C., “Distributed incremental data mining from very large databases: a rough multiset approach,” Proc. the 5th World Multi-Conference on Systemics, Cybernetics and Informatics, SCI 2001, Orlando, Florida, July 22-25, 2001, pp. 517-522.

·       Chan, C.-C., “How to set up an online store,” Proc. of Ohio Chinese American Professional Association Symposium 2001, Kent State University, Kent, Ohio, June 2 – 3, 2001, pp. 13.

·       Chan, C.-C., L.K. Verma, N. Khasawneh, and S. Rahman, “Generation of executable rule-based classifiers using Java Technology,”  Proc. 12th MidWest Artificial Intelligence and Cognitive Science Conference MAICS 2001, March 31 – April 1, 2001, Miami University, Oxford, Ohio, pp. 45-48.

·       Khasawneh, N. and C.-C. Chan, “Servlet-based implementation for rule-based classifiers,” Proc. 12th MidWest Artificial Intelligence and Cognitive Science Conference MAICS 2001, March 31 – April 1, 2001, Miami University, Oxford, Ohio, pp. 70-74.

·       Rahman, S. and C.-C. Chan, “A rule-based program generator using JESS,” Proc. 12th MidWest Artificial Intelligence and Cognitive Science Conference MAICS 2001, March 31 – April 1, 2001, Miami University, Oxford, Ohio, pp. 112-116.

·       Verma, L.K., V. Kumar, S. Kumar and C.-C. Chan, “SQL generated rule-based system,” Proc. 12th MidWest Artificial Intelligence and Cognitive Science Conference MAICS 2001, March 31 – April 1, 2001, Miami University, Oxford, Ohio, pp. 135-140.

·       Chan, C.-C., "A rough set approach to attribute generalization in data mining," Journal of Information Sciences, 107, pp. 169 - 176, 1998.

·       Chan, C.-C. and J.W. Grzymala-Busse, "On the lower boundaries in learning rules from examples," in Incomplete Information: Rough Set Analysis, edited by Ewa Orlowska, pp. 58-74, Physica-Verlag, Heidelberg, 1998.

·       Batur, C., C.-C. Chan, and A. Srinivasan, "Fuzzy model based fuzzy predictive controller," in METHODS AND APPLICATIONS OF INTELLIGENT CONTROL, edited by Spyros G. Tzafestas, pp. 173-196, Kluwer Academic Publishers, 1997.

·       Chan, C.-C., "A rough set approach to attribute generalization in data mining," Proc. of Joint Conference of Information Sciences 1997, Research Triangle Park, North Carolina, March 1 – 5, 1997, pp. 391-394.

·       Quafafou, M. and C.-C. Chan, "An Incremental Approach for Learning Fuzzy Rules from Examples," The Third European Congress on Intelligent Techniques and Soft Computing - EUFIT'95, Aachen, Germany, August 28-31, pp. 520-523, 1995.

·       Batur, C., A. Srinivasan, and C.-C. Chan, "Fuzzy model based fuzzy predictive controllers," Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, Vol. 3, No. 2, pp. 117 - 130, 1995.

·       Chan, C.-C. and J.W. Grzymala-Busse, "On the two local inductive algorithms: PRISM, and LEM2," Foundations of Computing and Decision Sciences, Vol. 19, No. 3, 185-203, 1994.

·       Srinivasan, A., C. Batur, and C.-C. Chan, "Using inductive learning to determine fuzzy rules for dynamic systems," Int. J. of Engineering Applications of Artificial Intelligence, Vol. 6, No. 3, pp. 257 - 264, 1993.

·       Batur, C., A. Srinivasan, and C.-C. Chan, "Inverse fuzzy model controllers," Proc. American Control Conference, pp. 772 - 776, 1993.

·       Batur, C., A. Srinivasan, and C.-C. Chan, "Fuzzy model based fuzzy predictive controllers," Proc. of First Int. Conference on Fuzzy Theory & Technology, pp. 176 - 180, 1992.

·       Chan, C.-C., "Incremental learning of production rules from examples under uncertainty: a rough set approach," Int. J. of Software Engineering and Knowledge Engineering, Vol. 1, No. 4, pp. 439 - 461, 1991.

·       Batur, C., A. Srinivasan, and C.-C. Chan, "Automated rule based model generation for uncertain complex dynamic systems," Int. J. of Engineering Applications of Artificial Intelligence, Vol. 4, No. 5, pp. 359 - 366, 1991.

·       Batur, C., A. Srinivasan, and C.-C. Chan, "Automated rule based model generation for uncertain complex dynamic systems," Proc. 6th IEEE Int. Symposium on Intelligent Control, pp. 275 - 279, 1991.

·       Chan, C.-C., Batur, C., and A. Srinivasan, "Determination of quantization intervals in rule-based models for dynamic systems," Proc. 1991 IEEE Int. Conf. on Systems, Man, and Cybernetics, Charlottesville, VA, Oct. 13 - 16, pp. 1719 - 1723, 1991.

·       Chan, C.-C. and J.W. Grzymala-Busse, "Rough-set boundaries as a tool for learning rules from examples," Proc. 4th Int. Symposium on Methodologies for Intelligent Systems, Charlotte, N.C., Oct. 12 - 14, pp. 281 - 288, 1989.

 

Presentations/Talks

·       C.-C. Chan, “Web Usage Mining Using BLEM2,” Institute of Information Science Academia Sinica, Taipei, Taiwan, December 27, 2006.

  • C.-C. Chan, “Application of Rough Sets to Knowledge Engineering,” The National Chiao Tung University, Hsinchu, Taiwan, December 28, 2006.

·       Chan, C.-C., “From Data to Knowledge: Data Mining using Rough Sets,” July 19, 2005, Institute of Information Science, Academia Sinica, Taipei, Taiwan.

·       Chan, C.-C., "Rough set theory and its applications," CS Seminars, Spring 2000, Department of Math and CS, University of Akron.

·       Chan, C.-C., "Knowledge discovery in databases," CS Seminars, Fall 1999, Department of Math and CS, University of Akron.

·       Chan, C.-C., "Incremental learning of certain and possible rules from examples," Workshop on rough sets and database mining, Computer Science Conference, Nashville, Tenn., March, 1995.

 

Grants and Awards

·          Chan, C.-C., Integrated Rule-Based Data Mining Expert System, Goodyear grant, US$ 22,914, August 2006 – July 2007.

·          Yi, Ping, Tom Xiao, and C.-C. Chan, Smart Sign Ordering Systems, ODOT grant, US$68,000, Oct. 2000 – Sept. 2002.

·          OSC Cluster Ohio Grant, co-PI with Kathy Liszka, Jutta Luettmer-Strathmann, etc., June 2001.

·          Chan, C.-C., Faculty Research Fellowship, The University of Akron, June – August, 2000.

·          Chan, C.-C., C. Batur, and L. Krishna, NeuralWare Research Grant Program, US$99,500, 1998 April- 1999, April.

·          Xiao, Tom, A. Abonamah and C.-C. Chan, Microsoft Instructional Lab Grant, 1996-1997.

·          C.-C. Chan, NASA-ASEE Summer Faculty Fellowship, NASA Lewis Research Center, 1997.

 

Professional Memberships

IEEE-Computer Society

Association for Computing Machinery

 

Scholarly Activities

·       Program Committee: The fourth international conference on Rough Sets and Current Trends in Computing (RSCTC'2004-2006)

·       Program Committee: The Tenth International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2005)

·       Program Committee:  Int. Conf. on Computing and Information, 1993-1995

·       Steering Committee: OCAPA (Ohio Chinese Academic and Professional Association), 1997

·       Reviewer for journals and conferences

·       Ph.D. Dissertation Committees (over 15)

·       Direct undergraduate honors projects (5)

·       Direct Master's Projects in Computer Science (over 30)

·       Inductive learning program developed: LERS3 and BLEM2

·       Ongoing projects: SQL and web-based learning programs, optimization of inference engines for multi-value classifiers

 

Courses Taught

  • Lower Level Undergraduate Courses:

Introduction to Computer Science, Data Structures and Algorithms I and II

  • Upper Level Undergraduate Courses:

Theory of Programming Languages, Artificial Intelligence, Database Management Systems

  • Graduate Courses:

Expert Systems, Expert Systems in Control and Manufacturing, Advanced Database Management, Data Mining