Ruohan is a Ph.D. student in the Personal Robotics Lab since October 2016, fully sponsored by the National Science Scholarship (Singapore).
He received First Class Honors in Computer Science from the National University of Singapore. Ruohan's main research interest is user-centric machine learning. In particular, he works on imitation learning and meta-learning such that intelligent agents could learn from human behaviors and quickly adapt to individual people.
His personal webpage can be found here.
- Random expert distillation: Imitation learning via expert policy support estimation, R Wang, C Ciliberto, P Amadori, Y Demiris, ICML 2019
- Support-guided Adversarial Imitation Learning, R Wang, C Ciliberto, P Amadori, Y Demiris, Neurips 2019 LIRE Workshop
- Real-time workload classification during driving using hypernetworks, R Wang, PV Amadori, Y Demiris, IROS 2018
- Multi-modal robot apprenticeship: Imitation learning using linearly decayed dmp+ in a human-robot dialogue system, Y Wu, R Wang, LF D’Haro, RE Banchs, KP Tee, IROS 2018
- Dynamic movement primitives plus: For enhanced reproduction quality and efficient trajectory modification using truncated kernels and local biases, R Wang, Y Wu, WL Chan, KP Tee, IROS 2016
- Human-robot partnership: A study on collaborative storytelling, CJ Wong, YL Tay, R Wang, Y Wu, HRI 2016