Hsi-Yung Feng

Hsi-Yung Feng is a Professor and Department Head in the Department of Mechanical Engineering at the University of British Columbia's Faculty of Applied Science. His academic leadership spans both research and administration within one of Canada's premier engineering institutions.

His educational background includes a B.S. from National Taiwan, and M.S. and Ph.D. degrees from Ohio State University. He is a Professional Engineer (P.Eng.) and a Fellow of the American Society of Mechanical Engineers (FASME).

Dr. Feng's research focuses on CAD/CAM/CAI (Computer-Aided Design, Manufacturing, and Inspection) systems, with particular emphasis on highly flexible and direct CAD modeling techniques, multi-axis CNC machining processes, and computational tools for 3D printing and laser scanning applications. His work bridges theoretical computational geometry with practical manufacturing solutions.

His recent publications demonstrate a consistent focus on advancing geometric modeling, machining simulation, and quality inspection methodologies. The research shows progression from fundamental geometric algorithms toward increasingly sophisticated applications in manufacturing automation, with strong emphasis on practical implementation challenges in CNC machining and additive manufacturing.

Among his professional recognitions, Dr. Feng received the prestigious Killam Teaching Award from the University of British Columbia in 2014, highlighting his excellence in engineering education.

• Killam Teaching Award, University of British Columbia, 2014

As Department Head, Dr. Feng oversees academic programs, faculty development, and strategic planning for mechanical engineering education and research. His leadership extends to directing the CAD/CAM/CAI Laboratory, which serves as a hub for advanced manufacturing research, focusing on developing innovative computational methods for modern manufacturing challenges.

The CAD/CAM/CAI Laboratory, under Dr. Feng's direction, focuses on developing innovative computational methods for manufacturing challenges, particularly in multi-axis machining, 3D printing optimization, and quality inspection systems. Current research includes multi-axis CNC machining simulation, generic postprocessor development, and optimal printing paths with adaptive infill structures for 3D printing.