Dr WU Tsung-Lin

wu tsung-lin



 
Senior Research Fellow
Email: tsunglin.wu@ntu.edu.sg
Education

PhD (Industrial Engineering), Georgia Institute of Technology
MS (Industrial Engineering), National Tsing Hua University
BBA, National Taiwan University

 

Biography

Tsung-Lin is a senior research fellow at RRIS, with a strong passion for precision rehabilitation, particularly in ability data analytics. His work at RRIS focuses on analysing data from motion capture systems, wearable devices, and other technologies to address key clinical research questions. With a diverse background in machine learning and operations research, Tsung-Lin has led and contributed to a range of industrial and research projects, particularly in healthcare and manufacturing. These projects involved data analysis, algorithm development, and software development. His previous work spans areas such as disease prediction, radiation therapy treatment planning, medical alert management, production scheduling, robotic process automation for machine control, and itinerary planning in tourism, among others.

 

​​​​​Research Interest
  • Precision Rehabilitation
  • Machine Learning
  • Operations Research

 

​​​Project
  • Projects in RRIS precision rehabilitation​

 

Publication

Journal

  • L Zhang, A Sidarta, TL Wu, P Jatesiktat, H Wang, L Li, PWH Kwong, A Long, X Long, WT Ang (2025). Towards clinical application of enhanced timed up and go with markerless motion capture and machine learning for balance and gait assessment. IEEE Journal of Biomedical And Health Informatics
  • O Roberts, TL Wu, P Teng, JL Lau, YH Pua, RA Clark, Y Hu, BY Tan (2025). Biomechanical analysis of step-up and step-down tasks in knee osteoarthritis: Insights from leading and trailing limbs. Clinical Biomechanics, 122, 106436
  • Y Hu, P Teng, TL Wu, R Clark, YH Pua, O Roberts, JW Yong, A Alhossary, LS Lim, DYR Chong, WT Ang, BY Tan (2025). Biomechanical differences of Asian knee osteoarthritis patients during standing and walking using statistical parametric mapping: A cross-sectional study. The Knee, 52, 155-163
  • JW Pan, A Sidarta, TL Wu, WHP Kwong, PL Ong, MRJ Tay, MW Phua, WB Chong, WT Ang, KSG Chua (2024). Unraveling stroke gait deviations with movement analytics, more than meets the eye: a case control study. Frontiers in Neuroscience
  • TL Wu, AA Alhossary, TC Pataky, WT Ang, CJ Donnelly (2022). pyemgpipeline: A Python package for electromyography processing. Journal of Open Source Software, 7(72), 4156

    •