Yaru Niu

Hi! I am a first-year PhD student at CMU Safe AI Lab, advised by Prof. Ding Zhao. Previously, I received an M.S. in Electrical and Computer Engineering at Georgia Tech, working with Prof. Matthew Gombolay. Before that, I received a B.E. in Intelligence Science and Technology at South China University of Technology. I also spent wonderful time as a research intern at Baidu Research with Dr. Liangjun Zhang, and at Berkeley with Prof. Masayoshi Tomizuka.
My research goal is to build methodologies for collaborative, interpretable, and reliable intelligent robotic systems that can interact with complex environments (including humans) around them. Thus, my research interest lies at the intersection of robotics and machine learning, and their applications in multi-agent coordination, autonomous driving, and human-robot interaction.
My Chinese name is 牛雅儒 (Niu-Ya-Ru), where my first name (雅儒) can be interpreted as a scholar in elegant taste by ancient Chinese.
CV / Google Scholar / Twitter / Github / Linkedin
News
Jan, 2023 | Our work on group distributionally robust reinforcement learning is accepted to AISTATS 2023. |
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Nov, 2022 | We are organizing the RoboDepth (Robust Out-of-distribution Depth prediction) Challenge at ICRA 2023. |
Jun, 2022 | Our work on interactive motion prediction for autonomous driving is accepted to IROS 2022. |
May, 2022 | I graduate from Georgia Tech. Thank you, GT. Check out my MS Thesis. |
Apr, 2022 | I will join Safe AI Lab at CMU as a PhD student starting from Fall 2022. |
Apr, 2022 | Our work Interpretable Continuous Control Tree (ICCT) is accepted to RSS 2022! |
Jan, 2022 | I start my research internship at Baidu Research in Sunnyvale. |
Oct, 2021 | Our work Multi-Agent Graph-Attention Communication (MAGIC) receives the Best Paper Award at ICCV 2021 Mair2 Workshop! |
Jan, 2021 | I will serve as a TA for CS 4641 Machine Learning (Spring 2021). |
Dec, 2020 | Our paper on multi-agent reinforcement learning (MAGIC) is accepted to AAMAS 2021 for oral presentation! |
Selected Publications
Notation * indicates equal contributions.
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Multi-Agent Graph-Attention Communication and TeamingIn International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2021 (Oral)
Best Paper Award at ICCV 2021 Mair2 Workshop [PDF] [Spotlight Talk]