Dr. Ye (IEEE, ASME, SAE), PROF & Interim CHAIR

Dr. Ye is a Multidisciplinary Researcher and Educator who has expertise on integration of teaching and research. Dr. Ye’s research interests encompass control and optimization with diverse applications of (classical, modern, intelligent) control theories on electrical, mechanical, automotive and biomedical systems, as well as signal and image processing. As the author of hundreds of publications, Dr. Ye's first & corresponding authorship covers all rank "A" leading control proceedings in three most prestigious engineering societies (IEEE, ASME, SAE), specifically, IEEE (CDC, CCA, SMC, ACC, ISIC, FUZZ, IJCNN, CEC, CASE, ICCA, SOSE, MSC Congress, WCCI Congress), ASME (IMECE Congress, ICES, JRCICE), SAE (USA Congress, EAEC Congress, PFL Congress). Dr. Ye also has the Sole Authorship in Key Top-Tier engineering journals inclusive of IEEE Transactions and SAE Transactions. Dr. Ye's research works have been broadly and officially presented & disseminated at 70 top international conferences (mostly IEEE, ASME, SAE) held in over 40 top countries apart from the southernmost continent. Being a Multidisciplinary Educator, Dr. Ye has instructed about 200 classes with zero assistance at SU and 3 other institutions, containing 50 diverse (graduate & undergraduate) engineering courses. Dr. Ye keeps the record of independently instructing a dozen of diverse graduate courses with zero assistance at the Pinchback Hall throughout its history of 20+ years. 

Engineering Applications of Artificial Intelligence (AI) are Challenging but Interesting & Promising  for the future to many Dedicated Academic People such as Dr. Ye. Topics of numerous first author (IEEE, ASME, SAE) publications of Dr. Ye focus on Engineering Applications of AI, ranging across various major branches of AI. A brief summary of keywords from my own existing publications is listed here, while many relevant methodologies are also involved in classroom teaching of Dr. Ye, such as the Fuzzy Logic Systems, Artificial Neural Networks, Hybrid Fuzzy Neural Networks, Evolutionary Computation, Genetic Algorithms, Particle Swarm Optimization, Ant Colony Optimization, Markov Chain Monte Carlo, Principal Component Analysis, Nonlinear Component Analysis, Independent Component Analysis, Support Vector Machine, Fuzzy C-Means Clustering, Fuzzy Stochastic Control, Nonlinear Least Squares Estimation, and K-Nearest Neighbors Rule.

Dr. Ye's teaching and research interest are in the areas of system control, engineering optimization, electrical & mechanical power systems, signal & image processing, as well as artificial intelligence.

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