• Associate Professor, Mechanical Engineering
  • Gulf Oil/Thomas A. Dietz Career Development Professor
Bruce Tai

Educational Background

  • Ph.D., Mechanical Engineering, University of Michigan, Ann Arbor – 2011
  • M.S., Applied Mechanics, National Taiwan University – 2006
  • B.S., Civil Engineering, National Taiwan University – 2004

Research Interests

    • Non-traditional machining processes
    • Numerical modeling of manufacturing processes
    • AI in manufacturing
    • Additive and hybrid manufacturing 
    • Surgical simulation and data analytics

Awards & Honors

  • ASME Fellow - 2022
  • TEES Engineering Genesis Award - 2019
  • TEES Young Faculty Fellow Award, Texas A&M University - 2018
  • Outstanding Young Manufacturing Engineer Award, Society of Manufacturing Engineers (SME) - 2017
  • Blackall Machine Tool and Gage Award, American Society of Mechanical Engineers (ASME) - 2017

Selected Publications

  • CC. Shih and B. Tai, 2025, “Dynamic Cutting Force Estimation via Fourier Neural Operator With Inferred Machine Tool Dynamics: A Proof of Concept,” Journal of Manufacturing Science and Engineering, 147(8), 081003.
  • M. Heydari and B. Tai, 2025, “A Machine Learning Approach for Rapid Solution of Three-Dimensional Moving Heat Source Problems in Manufacturing,” Journal of Manufacturing Science and Engineering. 147(6), 061006.
  • Nigam, A., and Tai, B. L., 2024, "Effects of in-process surface finishing on part strength in polymer material extrusion additive manufacturing," Additive Manufacturing, 80, p. 103960.
  • Randolph, O., Zvanut, R., and Tai, B. L., 2024, "Microstructure analysis and machinability of additively manufactured A205 aluminum with heat treatments," Journal of Manufacturing Processes, 127, pp. 51-61.
  • Nigam, A., Kellam, J. F., Ambrose, C. G., and Tai, B. L., 2024, "A Data-Driven Methodology to Comprehensively Assess Bone Drilling Using Radar Plots," JBJS Open Access, 9(1).