Summary
Harold Soh is an Associate Professor and leader of the Collaborative Learning and Adaptive Robots (CLeAR) group at the National University of Singapore, with 14 years of research experience bridging machine learning, human-robot interaction, and trustworthy decision-making for collaborative robots. His work ranges from cognitive modeling of human trust to tactile perception with novel e-skins, earning a best paper at IROS’21 and multiple top-conference nominations, and he regularly shapes the field through program and editorial leadership (HRI, RA-L, IJRR, AAAI symposiums). Trained at Imperial College London and seasoned by postdoctoral stints at MIT and University of Toronto, he combines rigorous online learning foundations with applied systems development for assistive and autonomous agents. Based in Singapore, he balances an active academic portfolio with a personal life that includes two young children and an affinity for science fiction paired with a good glass of wine—an indicator of his curiosity-driven but grounded approach to research.
14 years of coding experience
9 years of employment as a software developer
Bachelor of Arts and Sciences (BAS), Computer Science, Economics, Bachelor of Arts and Sciences (BAS), Computer Science, Economics at University of California, Davis
PhD, Robotics, Machine Learning, Human-Robot-Interaction, PhD, Robotics, Machine Learning, Human-Robot-Interaction at Imperial College London
The University of Melbourne
English, Malay