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) organized 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 instructing 13 diverse graduate lecture courses independently with zero assistance at the PBS Pinchback Hall throughout the history of the building (25 years). 

Engineering applications of Artificial Intelligence are challenging but offer a promising future for dedicated researchers and educators such as Dr. Ye. Topics of numerous first and corresponding author (IEEE, ASME, SAE) publications by Dr. Ye focus on engineering applications in nearly all major branches of AI. It is straightforward to confirm the details of Dr. Ye's existing publications on the IEEE Xplore platform. All of these major AI schemes have been successfully implemented in his academic research and classroom teaching, such as Fuzzy Logic Systems (FLC), Artificial Neural Networks (ANN), Hybrid Fuzzy Neural Networks, Evolutionary Computation (EC), Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Markov Chain Monte Carlo (MCMC), Principal Component Analysis (PCA), Nonlinear Component Analysis (NCA), Independent Component Analysis (ICA), Support Vector Machines (SVM), Kernel Fuzzy C-Means Clustering (KFCM), Fuzzy Stochastic Control (FSC), as well as Nonlinear Least Squares Regression Machine Learning. Dr. Ye has a great passion in (teaching and research) academic 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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