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

Dr. Ye is a Multidisciplinary Researcher and Educator, with the expertise on the integration of teaching and research. Being a Multidisciplinary Researcher, 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 the 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 13 diverse graduate lecture courses with zero assistance at the PBS Pinchback Hall throughout the history of the building (20+ years). 

Engineering applications of Artificial Intelligence (AI) are challenging but but offer a promising future for dedicated researchers such as Dr. Ye. Topics of numerous first author (IEEE, ASME, SAE) publications by Dr. Ye focus on engineering applications of AI, ranging across various major branches of AI. A brief summary of keywords from Dr. Ye's own existing publications is listed here, while many relevant methodologies are also involved in his classroom teaching, such as the prominent 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 Machines, Kernel Fuzzy C-Means Clustering, Fuzzy Stochastic Control, and Nonlinear Least Squares Estimation. Dr. Ye has a strong interest in teaching and research collaboration across these topics!

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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