Arjun Krishna
I am a CS PhD student at the University of Pennsylvania advised by Prof. Dinesh Jayaraman. My research interests broadly lie in area of robot learning, with specific interests in understanding the nature of information flow in perception-action loops and developing resource-efficient agents.

I previously obtained my Master’s in Computer Science from Georgia Tech, where I had the privileged of being advised by Prof. Matthew Gombolay. I received my Bachelor’s in Computer Science at IIT Madras, and was introduced to reinforcement learning research there by Prof. Balaraman Ravindran. Before returning to academia, I spent a few years as a Software Engineer at Indeed Japan, working on recommendation systems and advertisement bidding.

Publications

The Value of Sensory Information to a Robot
The Value of Sensory Information to a Robot
Arjun Krishna, Edward S Hu, Dinesh Jayaraman
ICLR 2025
[reviews] [project-website]
Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model
Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model
Long Le, Jason Xie, William Liang, Hung-Ju Wang, Yue Yang, Jason Ma, Kyle Vedder, Arjun Krishna, Dinesh Jayaraman, Eric Eaton
ICLR 2025
[arxiv] [project-website]
Illustrated Landmark Graphs for Long-horizon Policy Learning
Illustrated Landmark Graphs for Long-horizon Policy Learning
Christopher Watson, Arjun Krishna, Rajeev Alur, Dinesh Jayaraman
TMLR 2025, CoRL 2024 Workshop on Learning Effective Abstractions for Planning
[reviews]
Enhancing Safety in Learning from Demonstration Algorithms via Control Barrier Function Shielding
Enhancing Safety in Learning from Demonstration Algorithms via Control Barrier Function Shielding
Yue Yang*, Letian Chen*, Zulfiqar Zaidi*, Sanne van Waveren, Arjun Krishna, Matthew Gombolay
HRI '24: Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction
[paper]
The Effect of Robot Skill Level and Communication in Rapid, Proximate Human-Robot Collaboration
The Effect of Robot Skill Level and Communication in Rapid, Proximate Human-Robot Collaboration
Kin Man Lee*, Arjun Krishna*, Zulfiqar Zaidi, Rohan Paleja, Letian Chen, Erin Hedlund-Botti, Mariah Schrum, Matthew Gombolay
HRI '23: Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction
[paper]
Athletic Mobile Manipulator System for Robotic Wheelchair Tennis
Athletic Mobile Manipulator System for Robotic Wheelchair Tennis
Zulfiqar Zaidi*, Daniel Martin*, Nathaniel Belles, Viacheslav Zakharov, Arjun Krishna, Kin Man Lee, Peter Wagstaff, Sumedh Naik, Matthew Sklar, Sugju Choi, Yoshiki Kakehi, Ruturaj Patil, Divya Mallemadugula, Florian Pesce, Peter Wilson, Wendell Hom, Matan Diamond, Bryan Zhao, Nina Moorman, Rohan Paleja, Letian Chen, Esmaeil Seraj, Matthew Gombolay
IEEE Robotics and Automation Letters (presented at IROS'23)
[arxiv] [overview-video] [promotional-video]
AsymQ: Asymmetric Q-Loss to mitigate overestimation bias in off-policy reinforcement learning
AsymQ: Asymmetric Q-Loss to mitigate overestimation bias in off-policy reinforcement learning
Qinsheng Zhang*, Arjun Krishna*, Sehoon Ha, Yongxin Chen
NeurIPS-W 2022 (DeepRL workshop)
[paper]
Utilizing Human Feedback for Primitive Optimization in Wheelchair Tennis
Utilizing Human Feedback for Primitive Optimization in Wheelchair Tennis
Arjun Krishna, Zulfiqar Zaidi, Letian Chen, Rohan Paleja, Esmaeil Seraj, Matthew Gombolay
CoRL-W 2022 (Learning for Agile Robots workshop)
[arxiv] [poster] [project-video]
No matching items