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www.haroldsoh.com

Harold SOH

Assistant Professor
Associate Director, NUS AI Lab

  • Ph.D. (Artificial Intelligence & Robotics, Imperial College London, UK, 2014)
  • M.S. (Software Engineering, University of Melbourne, Australia, 2005)
  • B.ASc. (Computer Science, Economics, University of California, Davis, 2004)

Harold Soh is an Assistant Professor in the Department of Computer Science at the National University of Singapore (NUS), where he directs the Collaborative Learning and Adaptive Robots (CLeAR) group. Harold completed his Ph.D. at Imperial College London with Yiannis Demiris on online learning for assistive robots. Harold's current research focusses on machine learning and decision-making for trustworthy collaborative robots. His work spans cognitive modeling (specifically human trust) to physical systems (perception with novel e-skins) and has been recognized with best paper award nominations at RSS, HRI, and IROS. Harold has served on the HRI committee as LBR Co-Chair (2019) and on the Technical Advances PC as a member (2020) and chair (2021). He is an Associate Editor of the ACM Transactions on Human Robot Interaction (2021). He regularly serves as PC member or reviewer for the top publication venues in AI (NeurIPS, AAAI, IJCAI) and robotics (ICRA, IROS, RSS, HRI).

RESEARCH AREAS

Artificial Intelligence
  • Decision Making & Planning
  • Machine Learning
  • Robotics
  • Trustworthy AI

RESEARCH INTERESTS

  • Human-Robot Interaction

  • Machine Learning

  • Robotics

  • Artificial Intelligence

RESEARCH PROJECTS

RESEARCH GROUPS

Collaborative, Learning, and Adaptive Robots (CLeAR)

The Collaborative, Learning, and Adaptive Robots (CLeAR) Lab at NUS investigates the science and engineering of human-AI/robot teams. For more information, check out https://clear-nus.github.io


TEACHING INNOVATIONS

SELECTED PUBLICATIONS

  • Multi-Task Trust Transfer for Human Robot Interaction. Harold Soh, Yaqi Xie, Min Chen, and David Hsu. International Journal of Robotics Research (IJRR), 2020
  • Event-Driven Visual-Tactile Sensing and Learning for Robots. Tasbolat Taunyazov, Weicong Sng, Hian Hian See, Brian Lim, Jethro Kuan, Abdul Fatir Ansari, Benjamin Tee, and Harold Soh. Robotics: Science and Systems Conference (RSS), 2020
  • Refining Deep Generative Models via Discriminator Gradient Flow. Abdul Fatir Ansari, Ming Liang Ang, and Harold Soh. International Conference on Learning Representations (ICLR), 2021.
  • Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization. Sreejith Balakrishnan, Quoc Phong Nguyen, Bryan Kian Hsiang Low, and Harold Soh. Neural Information Processing Systems (NeurIPS), 2020.
  • Robot Capability and Intention in Trust-based Decisions across Tasks. Xie Yaqi, Indu Prasad, Desmond Ong, David Hsu and Harold Soh. ACM/IEEE Conference on Human Robot Interaction (HRI), 2019
  • Harold Soh and Yiannis Demiris. Learning Assistance by Demonstration: Smart Mobility With Shared Control and Paired Haptic Controllers. J. Human-Robot Interact. 4, 76–100 2015.
  • Harold Soh, Yanyu Su, and Yiannis Demiris. Online spatio-temporal Gaussian process experts with application to tactile classification. in Intelligent Robots and Systems IROS, 2012 IEEE/RSJ International Conference on 4489–4496 2012.

AWARDS & HONOURS

  • Best of IEEE Transactions on Affective Computing (T-AFFC) 2021 Award, Applying Probabilistic Programming to Affective Computing, 2022

  • Best Paper Award, Extended Tactile Perception: Vibration Sensing through Tools and Grasped Objects, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021

  • Best Paper Award Finalist, The Transfer of Human Trust in Robot Capabilities across Tasks, Robotics Science and Systems (RSS), 2018.

  • Best Paper Award Finalist, Planning with Trust for Human Robot Collaboration, ACM/IEEE Human Robot Interaction (HRI), 2018.

  • Best Long Paper Award Runner-up, Generation Meets Recommendation: Proposing Novel Items for Groups of Users, ACM Recommender Systems (RecSys), 2018.

  • M.I.T. SMART Postdoctoral Fellowship Award, 2013

  • Best Cognitive Robotics Paper Finalist, Online Spatio-Temporal Gaussian Process Experts with Application to Tactile Classification, IEEE/RSJ Intelligent Robots and Systems (IROS), 2012.

  • UK James Dyson Award National Finalist, 2012

  • IEEE/RSJ IROS Cognitive Robotics Best Paper Finalist, 2012

  • Khazanah Global Scholarship (Postgraduate), 2009-2013.

  • Uni. of California Regents Scholarship, 2000-2004

MODULES TAUGHT

CS3264
Foundations of Machine Learning
CS5340
Uncertainty Modelling in AI

 

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