Welcome to my academic homepage. I am a Ph.D. student in
under the supervision of Computer Science at University of California, Los Angeles (UCLA) Song-Chun Zhu.
I work on representation learning for reasoning and skill learning tasks. In particular, I'm interested in building and understanding inductive biases for learning representations from multi-modal data, so as to systematically generalize in real-world physical and psychological dynamics. Some of my research keywords can be found below:
Humanlike Learning: Concept and language acqusition, Embodied agents, (Inverse) Reinforcement learning
Representation Learning: OOD generalization (domain and systematic), Energy-based generative model, Multi-modal learning
[06/2021] Will work as a research intern at .
[05/2021] One paper about hierahical skill acqusition via adversarial learning and option inference is accepted to ICML 2021.
[02/2021] New on measuring the generalization in human-like abstraction learning and reasoning!
2020.6 - 2021.5, Research Intern, Google Brain Robotics
Advisors: Dr. Pannag Sanketi and Laura Graesser.
2019.6 - 2019.9, Research Intern, ByteDance AI Lab
Advisors: Dr. Lei Li and Dr. Tao Kong.
2018.7 - 2018.11, Research Intern, University of California, Los Angeles, Center for Vision, Cognition, Learning and Autonomy
Advisors: Prof. Song-Chun Zhu, Dr. Yixin Zhu and Mark Edmonds.
2017.7 - 2017.9, Research Intern, National University of Singapore, School of Computer Science, CVRP Lab
Advisor: Prof. Gim Hee Lee.
Conference PC Member/Reviewer: ICML (top reviewer), NeurIPS, ICLR, AAAI, IJCAI (senior PC), CVPR (outstanding reviewer), ICCV, ECCV, WACV, ACCV, RSS, ICRA, IROS, CoRL
Journal Reviewer: IEEE RA-L, AAS, IEEE/CAA JAS
UCLA Center for Vision, Cognition, Learning and Autonomy
3878 Slitcher Hall
603 Charles E Young Dr E
Los Angeles, CA 90024
xm [at] cs [dot] ucla [dot] edu
[ G o o g l e Scholar]