Some more pictures of us: 1, 2, 3, 4, 5, 6, 7

Welcome to the Perception, Action, & Learning research group at UPenn (PennPAL). We simultaneously push the limits of what can be achieved using today’s prevalent principles in robot learning (“exploit”), and ask foundational questions in robotics towards building better design principles for efficient and minimalist robots in the future (“explore”). As examples of “exploit”, we have trained quadruped robots to perform circus tricks on yoga balls and robot arms to perform household tasks in entirely unseen scenes with unseen objects. As examples of “explore”, we are studying the sensory requirements of robot learners: what sensors do they need and when during training and task execution do they need them? We are motivated in all this work by the grand goal of building general-purpose robots that can help humans in our homes, offices, hospitals, farms, and more.

Note: A more complete research statement, written in August 2024, is here.

Some recent talks that might give you more of a sense of what we have been working on over the years:

• Exploring and Exploiting Robot Learning, Michigan AI Symposium (Oct 2024)
• How to Train Your Robot, Nemertes “What’s Next” Industry Conference Talk (for a general audience) (Sep 2024)
• Polyglot Robots, MIT Embodied Intelligence Seminar (Mar 2023)
• Scaling Vision-Based Robot Learning, GRASP Faculty Research Talk (Aug 2022)
• Scaling Vision-Based RL for Robotics, MIT Computational Sensorimotor Learning Seminar (Feb 2022)
• Perception Through Action and For Action, AAAI New Faculty Highlight Talk (Feb 2021)

Our work is possible because of our funding sources.

Current PhD students in the lab

• Aurora Qian
• Edward Hu
• Jason Ma (co-advised with Osbert Bastani)
• Leon Kim (co-advised with Michael Posa)
• Pratik Kunapuli (co-advised with Vijay Kumar)
• Junyao Shi
• Arjun Krishna

Current MS and undergraduate students in the lab

• Hungju Wang (MS Student)
• Jason Yan (undergraduate)
• Will Liang (undergraduate)
• Sam Wang (undergraduate)
• Fiona Luo (undergraduate)
• Lilian Li (undergraduate)

Student Collaborators

• Kaustubh Sridhar (PhD student advised by Insup Lee and Jim Weimer)
• Chris Watson (PhD student advised by Rajeev Alur)
• Kyle Vedder (PhD student advised by Eric Eaton)
• Tianyu Li (PhD student advised by Nadia Figueroa)
• George Gao (MS student advised by Nadia Figueroa)
• Long Le (PhD student advised by Eric Eaton)

Visiting Students and Postdocs

• Chuan Wen (PhD student at Tsinghua University, advisor: Yang Gao, 2020-now)
• Weilin Wan (PhD student at University of Hong Kong, advisor: Taku Komura, 2023-2024)
• Jingxi Xu (PhD student at Columbia University, advisors: Matei Ciocarlie, Shuran Song, 2020)
• Oleh Rybkin (PhD student collaborator 2020-now, next postdoc at UC Berkeley)
• Zhiyang Duo (PhD student at University of Hong Kong, advisors: Wenping Wang and Taku Komura, 2023-2024)

Past Students

• Srinath Rajagopalan (MS 2020, next at Amazon Robotics)
• Adarsh Modh (MS 2020, next at NEC Research Labs America)
• Kun Huang (MS 2022, next at Cruise Automation), winner of the SEAS outstanding MS Research Award
• Andrew Shen (visiting undergrad 2021, next at CMU MS in ML)
• Lloyd Acquaye Thomson (visiting MS student 2021, African Masters in Machine Intelligence program)
• Kausik Sivakumar (MS 2023, next at Tutor Intelligence), winner of the GRASP MS Research Award
• Yunshuang Li (MS 2024, next at USC CS PhD Program), winner of the SEAS outstanding MS Research award
• Alan Zhao (MS 2024, next at Skild.ai)
• James Springer (MS 2024, next at Anduril Industries)
• Vaidehi Som (MS 2023, next at Zipline)
• Tasos Panagopoulos (BS+MS 2024, next at Jane Street)

Principal Investigator

• Dinesh Jayaraman