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Chia-Yuan Wu

Ph.D. Candidate at Lehigh ISE

About

I am a Ph.D. candidate in the Department of Industrial and Systems Engineering (ISE) at Lehigh University under the supervision of Prof. Daniel P. Robinson. I received my M.S. in Industrial Engineering and Management in 2017 and my B.B.A. in Management Science in 2015, both from National Chiao Tung University in Hsinchu, Taiwan.

My research focuses on fair collaborative machine learning and synthetic data generation, with an emphasis on mitigating unfairness, preserving privacy, and reducing communication costs through innovative techniques such as bilevel optimization and data distillation.

Prior to joining Lehigh University, I worked as a system design engineer at Advanced Micro Devices (AMD) and AU Optronics Corp. (AUO), both based in Hsinchu, Taiwan.

Education

  • Ph.D., Industrial and Systems Engineering, Lehigh University, Bethlehem, PA, USA, 2022–present
  • M.S., Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan, 2015–2017
  • B.B.A., Management Science, National Chiao Tung University, Hsinchu, Taiwan, 2011–2015

Experience

  • Teaching Assistant, Lehigh University, Bethlehem, PA, USA, Aug. 2025–Dec. 2025
  • Research Assistant, Lehigh University, Bethlehem, PA, USA, May 2025–Aug. 2025
  • Teaching Assistant, Lehigh University, Bethlehem, PA, USA, Aug. 2024–May 2025
  • Graduate Assistant, Lehigh University, Bethlehem, PA, USA, Jul. 2024–Aug. 2024
  • Research Assistant, Lehigh University, Bethlehem, PA, USA, Jan. 2023–Jun. 2024
  • Software System Designer, Advanced Micro Devices, Inc. (AMD), Hsinchu, Taiwan, Apr. 2021–Jul. 2022
  • Senior Software Engineer, AU Optronics Corp. (AUO), Hsinchu, Taiwan, Sept. 2017–Apr. 2021
  • Intern, Taiwan Semiconductor Manufacturing Company (TSMC), Hsinchu, Taiwan, Jul. 2016–Aug. 2016

Publications

  • Chia-Yuan Wu, Frank E. Curtis and Daniel P. Robinson (2025). "A Bilevel Optimization Approach for Computing Synthetic Data to Mitigate Unfairness in Collaborative Machine Learning." Preprint in review.
  • Sheng-I Chen, Chia-Yuan Wu (2020). "A stochastic programming model of vaccine preparation and administration for seasonal influenza interventions." Mathematical Biosciences and Engineering.
  • Sheng-I Chen, Chia-Yuan Wu, Yu-Hsuan Wu and Min-Wei Hsieh (2019). "Optimizing influenza vaccine policies for controlling 2009-like pandemics and regular outbreaks." PeerJ.

Conferences

  • MOPTA 2024, Bethlehem, PA, August 2024. (presentation)
    Enhancing Fairness in Machine Learning through Training Synthetic Datasets in Multi-Client Scenarios.
  • MOPTA 2023, Bethlehem, PA, August 2023. (attendance)