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Kaustubh Sridhar

Hi there! I’m a final-year PhD student in Electrical and Systems Engineering at the University of Pennsylvania, where I’m advised by Insup Lee and closely collaborate with Dinesh Jayaraman and Oleg Sokolsky.

I am interested in creating adaptive generalist agents that are parameter- and sample-efficient, for the digital and physical worlds. Towards this goal, I have worked on generative models and in-context learning, deep reinforcement and imitation learning (particularly from large offline datasets), and robust deep learning.

My recent work on a Retrieval-Augmented Generalist Agent directly aims for this goal.

In the past, I have interned twice at AWS AI Labs and once at Ford and VW’s self-driving unit.

Before starting my PhD, I graduated with honors from the Indian Institute of Technology Bombay.

My CV can be found here.

Industry Experience

Awards

  • Oral Presentation (top 1.8% of 11672 submissions) for REGENT at ICLR 2025
  • Best Paper Award Nomination for CODiT at ICCPS 2023
  • Top Reviewer (top 10%), NeurIPS 2022
  • Outstanding Reviewer (top 10%), ICML 2022
  • NSF Travel Grant, ICCPS, 2023
  • Student Travel Grant, American Control Conference, 2022
  • The Dean’s Fellowship, University of Pennsylvania, 2019
  • The Howard Broadwell Fellowship, University of Pennsylvania, 2019
  • SN Bose Scholarship, Gov. of India, 2018
  • KVPY Fellowship, Gov. of India, 2015
  • Dan 1 (black belt), Shotokan Karate Association, 2011

Selected Invited Talks

  • Training Adaptive and Sample-Efficient Generalist Embodied Agents
    • Apr 2025: NTU Singapore
    • Nov 2024: Google Deepmind
    • Nov 2024: Apple MLR

Media

Publications

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