How can a robot learn from its own interactions?
What abstractions are necessary to describe a task?
When does a robot even know that the task is now completed?
In a quest to find answers to the above questions, I am currently a PhD student at ETH Zurich, advised by Marco Hutter, and a Deep Learning R&D Engineer at NVIDIA Research. I also closely collaborate with Animesh Garg at the University of Toronto.
Over the past few years, I have had the opportunity to work with some amazing robotic groups. I have been a visiting student researcher at Vector Institute, a research intern at NNAISENSE, and a part-time research engineer at ETH Zurich. During my undergrad at IIT Kanpur, I was a visiting student at University of Freiburg, Germany, working closely with Abhinav Valada and Wolfram Burgard.
I am incredibly thankful to my collaborators and mentors, and enjoy exploring new domains through collaborations. If you have questions or would like to work together, feel free to reach out through email!
|Oct 7, 2021||Joined Marco Hutter’s group at ETH Zurich as a PhD student|
|Jun 28, 2021||Excited to start as a Deep Learning R&D Engineer at NVIDIA!|
|May 18, 2020||Excited to start my master thesis with Animesh Garg at PAIR Lab, University of Toronto!|
|Jan 22, 2020||Our paper on ‘Learning Camera Miscalibration Detection’ from my work at Autonomous Systems Lab, ETH Zurich is accepted to ICRA 2020|
|Sep 1, 2019||Started my internship with the Intelligent Automation team at NNAISENSE, Lugano!|
I am primarily interested in decision-making and control for the operation of robots in human environments. These days, my efforts are focused on designing perception-based systems for contact-rich manipulation tasks, such as articulated object interaction with mobile manipulators and in-hand manipulation. Other areas of interest include hierarchical reinforcement learning, optimal control, and 3D vision.
- Transferring Dexterous Manipulation from GPU Simulation to a Remote Real-World TriFinger (Under Review)
- Articulated Object Interaction in Unknown Scenes with Whole-Body Mobile Manipulation (Under Review)
- Neural Lyapunov Model Predictive Control (Under Review)
- Learning Camera Miscalibration Detection ICRA 2020
- Vision-based Autonomous UAV Navigation and Landing for Urban Search and Rescue ISRR 2019
- Vision-based Autonomous Landing in Catastrophe-Struck Environments Workshop on Vision-based Drones: What’s Next?