Jesse Zhang
jessez at usc dot edu
Hi! I am a 5th-year PhD candidate at USC, advised by Professors Jesse Thomason and Erdem Biyik at USC
and Joseph J. Lim at KAIST on
deep reinforcement learning for robotics. I completed my undergrad at UC Berkeley,
where I worked with Professors Sergey Levine and Dinesh Jayaraman.
I have interned at NVIDIA in the
Seattle Robotics Lab,
AWS Lablets in Rasool Fakoor's team, NAVER AI Labs and Horizon
Robotics.
I am interested in improving generalization and sample-efficiency of reinforcement learning algorithms by
injecting inductive biases (e.g., programs), incorporating large offline datasets (e.g., through offline RL),
and guiding agents with external knowledge (e.g., large language models).
CV  / 
GitHub  / 
Twitter  / 
Google Scholar
News
02/25 Gave a talk as part of the Google Deepmind Tech Talk Series!
01/25 HAMSTER is accepted to ICLR 2025!
01/25 Gave a talk at at the RLLAB at Yonsei University!
12/24 Gave a talk at at the NTU Robot Learning Lab!
09/24 EXTRACT is accepted to CoRL 2024!
05/24 RL-VLM-F is accepted to ICML 2024!
03/24 Excited to be joining NVIDIA's Seattle Robotics Lab this summer as an intern!
02/24 Gave a talk at the PAL lab at UPenn
02/24 Selected as Finalist for the Qualcomm Innovation Fellowship
Research
(Highlighted /
All)
(* indicates equal contribution,
† indicates equal advising)
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Service
Serving as a PhD mentor for the Google x USC AI Community Project, focused
on assisting undergraduates from underrepresented backgrounds in teaching AI to students from local Los Angeles middle and high schools.
Serving/Served as a reviewer for RA-L, CHI 2024, ICML 2024, ICLR 2024, NeurIPS 2023, ICML 2023, ICLR 2023, CoRL 2022, ICML 2022, ICLR 2022 (highlighted
reviewer
award, top 8%), NeurIPS 2021 (outstanding reviewer award, top 8%), CoRL 2021, ICLR
2021, ICLR
SSL-RL
Workshop 2021, IEEE ITSC 2019
Teaching
TA at University of Southern California
08/2024: CSCI 566: Deep Learning (Master's Level)
01/2023: CSCI 566: Deep Learning (Master's Level)
01/2022: CSCI 360: Intro to AI (Undergrad Level)
08/2020: CSCI 566: Deep Learning (Master's Level)
UC Berkeley
08/2019: TA CS188: Intro to AI (rating: 4.75/5.00, 0.42 above dept avg)
01/2019: Course Reader CS170: Efficient Algs and Intractable Problems
Others
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