Jesse Zhang

jessez at usc dot edu

Hi! I am a fourth-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 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).

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  • 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
  • 02/24 SPRINT is accepted to ICRA 2024, and TAIL is accepted to ICLR 2024
  • 10/23 BOSS is accepted as an oral at CoRL 2023
  • 05/23 Started an internship at AWS research this summer

  • 11/22 SPRINT is accepted as a spotlight talk at CoRL 2022 LangRob Workshop
  • Research (Highlighted / All)
    (* indicates equal contribution, indicates equal advising)
  • 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
  • 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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