Yoh-Han Pao

George S. Dively Distinguished Professor Emeritus of
Electrical Engineering and Computer Science
509 Glennan, (216)368-4040
Ph.D., Pennsylvania State University
E-mail: yxp@po.cwru.edu

 Professor Pao's research seeks to combine the pattern recognition and artificial intelligence approaches to information processing, with emphasis on the solution of significant real-world problems.

In recent years he has contributed to the development of adaptive pattern recognition, especially as practiced with the use of neural-net computing. His book on this subject, published by Addison Wesley, has proved to be helpful in the development of that methodology.

Past research contributions include the Walsh-Function Holographic Content Addressable Memory and the Functional-Link Neural-network for learning of mappings between pattern spaces and knowledge guided evolutionary search and optimization. Present activity includes research in Computational Genomics and Adaptive Nonlinear Control. Specific current research areas include building models of complex biomolecular systems, multi-objective adaptive nonlinear control, and visualization of multivariate data.

Professor Pao is on the Editorial Boards of Pattern Recognition and has served as Associate Editor of many journals including IEEE Transactions on Nueral-Networks, Neurocomputing, Pattern Recognition and Artificial Intelligence and others. Professor Pao was the founding Editor of Academic Press Series on Quantum Electronics.

Professor Pao is a Life Fellow of IEEE, served as NSF Director of Electrical, Computer and System Engineering and is currently co-director of the Center for Computational Genomics at Case Western Reserve University.

Professor Yoh-Han Pao was co-founder and President of AI WARE Inc., a Beachwood, OH computer software company specializing in intelligent systems for industry and business. AI WARE is now part of Computer Associates International, Inc. of Islandia, NY.

  Dr. Pao's Group  

 [1] Y.H. Pao, 1989. Adaptive Pattern Recognition and Neural Networks, Addison-Wesley, Reading, MA.

 [2] P.P.C. Yip and Y.H. Pao, 1994. A guided evolutionary simulated annealing approach to the quadratic assignment problem, IEEE Transations on Systems, Man and Cybernetics, Vol. 24, No. 9, PP.1383-1387.

 [3] Y.H. Pao and P.P.C. Yip, 1995. Neural net process monitoring and optimal control. Chapter in Handbook on Fuzzy Logic and Neural Networks, edited by C.H. Chen, McGraw-Hill, N.Y.

 [4] M. Nyberg and Y.H. Pao, 1995. Automatic optimal design of fuzzy systems based on universal approximation and evolutionary programming. Chapter in Fuzzy Logic and Intelligent Systems, edited by H.L. Hua and M. Gupta, Kluwer Academic Publishers, Norwell, MA.

 [5] P.P.C. Yip and Y.H. Pao, 1995. Combinatorial optimization with use of guided evolutionary simulated annealing, IEEE Transactions on Neural Networks, Vol. 6, No. 2, pp. 290-295.

 [6] Y.H. Pao and C.Y. Shen, 1997. Visualization of pattern data through learning of non-linear variance-constrained dimension-reduction Mapping, Pattern Recognition, vol. 30, No.10, pp. 1705-1717.

 [7] Y.H. Pao, 1997. Dimension reduction, feature extraction and interpretation of data with netwrok computing, in Studies in Pattern Recognition: A memorial to the late Professor King-Sun Fu, H. Freeman, Editor, World Scientific Publishing Company. Also in International Journal of Pattern Recognition and Artificical Intelligence, Vol. 10, pp. 521-535.

 [8] Y.H. Pao and B.F. Duan, 1998. Evolving a juggler: using the inverted pendulum/cart control task to investigate issues of learning in coupled systems, Proceedings of the 2nd International Conference on Neural Networks and Brain '98, October 27-30, Beijing, China.

 [9] Y.H. Pao and Z. Meng, 1998. Visualization and the understanding of multidimensional data, Engineering Applications of Artificial Intelligence, Vol. 11, pp. 659-667.

[10] B. Hoit; S. Kiatchoosakun.; J. Restivo; D. Kirkpatrick; K. Olszens; H.F. Shao; Y.H. Pao and J. Nadeau, 2002. Naturally occurring variation in cardiovascular traits among inbred mouse strains, Genomics, Vol. 79, No. 5, pp. 679-685.

[11] J. Nadeau; L. Burrage; G. Churchill; A. Hill; J. Restivo; H.F. Shao; Y.H. Pao and B. Hoit, 2002. Building hearts from computational analysis of cardiovascular traits in genetically randomized populations, Presented in the 16th International Mouse Genome Conference , San Antonio, Texas, Nov.17 - 20.

[12] Y.H. Pao and H.F. Shao, 2003, Use of Inferented machine learning for exploration and validation of models of biomolecuare networks ( in preparation).