Shing Chang

Dr. Chang's expertise focuses on quality engineering research. Research topics include applications of decision theory (multiple objective optimization), big data analytics, statistical methods (response surface), fuzzy sets, machine learning, and AI models (neural networks and generative AI such as transformers). Research projects include: (1) Large multi-modal model (LMM) for elderly fraud prevention, (2) Generative AI for Controlled Environment Agriculture (CEA) operations, (3) Big Data Analytics applications in Quality Engineering (e.g. Massive Data Analysis under Uncertainty with Applications to GPS Geometric Modeling), (4) Health Systems Engineering (e.g., predictive Health such elderly fall detection and assessing hospital data driveness), (5) Multivariate Process Monitoring and Profile Analysis, (5) Fuzzy Neural Applications in Experimental Design and Process Control (disease detection and suicide warning), and (6) Computer Image Inspection and Statistical Process Control Using Wavelet Transform.