I am an Assistant Professor in the Electrical and Systems Engineering department and the GRASP Robotics Laboratory. I hold a secondary appointment in the Computer and Information Sciences department and am a member of the Applied Mathematics (AMCS) and
Penn Institute for Computational Science (PICS) graduate groups.
Previously, I held a joint position as a Senior Applied Scientist at Amazon Web Services and a post-doctoral researcher at the California Institute of Technology in the Computing and Mathematical Sciences department.
I defended my PhD thesis in the Computer Science department at University of California, Los Angeles in 2018 where I worked with Stefano Soatto in the UCLA Vision Lab. I have an Engineer's (2014) and Master's (2012) degrees in Aeronautics & Astronautics from the Massachusetts Institute of Technology where I worked with Emilio Frazzoli at the Laboratory of Information and Decision Systems (LIDS). I was in the Aerospace Engineering department at IIT Bombay for my undergraduate studies until 2010.
I have worked extensively on self-driving cars in the areas of computer vision, planning and control at nuTonomy Inc (now Aptiv).
Research Interests: I am interested in machine learning, in particular deep neural networks, robotics and computer vision. My ambition is to bring the dream of cybernetics closer to reality and enable Embodied Intelligence. The ability to perceive and control the environment, with cognition acting as the glue in between, is the hallmark of intelligent beings; the interplay between these three is the core of my research. In my group, we perform highly multi-disciplinary research. We study ideas from statistical physics, optimization, computer vision, control theory and motion-planning. The work can be theoretical, empirical and or really anything in between: everyone from hands-on roboticists, to engineers, computer scientists and mathematicians are welcome.
NeurIPS 2020 Workshop on Deep Learning through Information Geometry: We organized a workshop recently to brainstorm how ideas in information geometry and information theory inform questions of optimization and generalization in deep learning. You can find the recorded keynote talks and accepted submissions at here.
I am always looking for exciting researchers who can be a part of my research group. I would love to hear from you.
These videos give a flavor of some recent results from our group.
If you are an existing student at Penn, send me an email and we can set up a time to talk. If you are not at Penn, please use this form to contact me about open positions.
Understanding Deep Learning
Learning with few labeled data
pratikac at seas dot upenn dot edu
Levine Hall 470
Yansong Gao (AMCS)
Christopher Hsu (ESE)
Jialin Mao (AMCS)
Rahul Ramesh (CIS)
Rongguang Wang (ESE, co-advised with Christos Davatzikos)
Rubing Yang (AMCS)
Undergraduate and Master's students
Matt Elser (CIS MS)
Rahul Maganti (ESE BS, Robo MS)
Megharjun Nanda (Robo MS)
Sebastian Peralta (Physics/ESE BS, Robo MS)
Anirudh Cowlagi (2nd year undergrad)
Emily Paul (2nd year undergrad)
Xiaoyi (Sherry) Chen (EE/MNT BS, CIS MS, now at nuro.ai)
Ashish Mehta (Robo MS, now at Qualcomm)
Christopher Hsu (ESE MS, now at ARL)
Wenbo Zhang (Robotics MS, now at grayscale.ai)
See Google Scholar for the latest list of publications and citations.