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California State University, Long Beach

Mechanical & Aerospace Engineering (MAE)

picture of Hsin-Piao Chen

Dr. Hsin-Piao Chen

MSAE Advisor

Fall 2017 Schedule

Schedule Sem/Lab Time Days Room
MAE 422-01 SEM 3:50-6:45PM MW ECS-210
MAE 465-01 SEM 2:00-3:15PM MW ECS-202
MAE 522-01 SEM 5:30-6:45PM MW ECS-210
MAE 563-01 SEM 7:00-9:45PM T ECS-210

Schedule updated: SEPTEMBER 12, 2017

View the complete Schedule of Classes


Dr. Hsin-Piao Chen is currently a professor in the Department of Mechanical and Aerospace Engineering at California State University, Long Beach. He was Associate Professor in the Institute of Aeronautics and Astronautics at the Cheng Kung University, Taiwan from 1984 to 1985. He has also served as a consultant to Douglas Aircraft Company.

Dr. Chen received his B.S. degree in Engineering Science from Cheng-Kung University, M.S. degree in Power Mechanical Engineering from Tsing-Hua University and Ph.D. in Aerospace Engineering from Georgia Institute of Technology. He is a member of the Phi-Tau-Phi Scholastic Honor Society, an AIAA senior member, and an active member of ICCE and ASME.

Dr. Chen's area of specialty is in structures and materials, with a special emphasis on the analysis and design of composite structures, finite element analysis, structural design optimization, and aerospace structures. He has been involved in the NASA ICAPS (Innovative Composite Aircraft Primary Structures) and HSR (High Speed Research) programs since inception and conducted both experimental and computational work. He has been funded by the Boeing Company to develop the technique of nonlinear structural analysis and shape optimization for hole-drilling in manufacturing process. He was a member of the technical team of the Long Beach Public Safety Structural Seismic Upgrade Project which is funded via the FEMA Hazard Mitigation Grant Program. He was the principal investigator of the research project "Characterization and Detection of Delamination in Smart Composite Structures" funded by US Army Research Office to develop a delamination detection methodology using a combined finite element methods, genetic algorithms and neural network techniques.

Research and Publications

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