I am a Ph.D. candidate in robotics at USC, affiliated with the Realization of Robotics Systems Lab (RRoS) advised by Dr. Satyandra K. Gupta. My research is centered around integrating physics-informed learning methods into robotics, focusing on enhancing robots’ capability to manipulate objects with complex physics. I’m developing practical and scalable approaches to create explainable models that exploit physics-aware inductive biases for robots to perform complex tasks.
Before starting my Ph.D., I have led multiple industry-funded projects at USC as a Master’s student. In the past, I worked for Rolls-Royce, Singapore, as a robotics engineer for two years.
Download my CV .
Interests
- Robot Learning
- Robotic Manipulation
- Deep Learning
- Motion Planning
Education
PhD in Mechanical Eng. (Robotics), 2025
University of Southern California
MSc. in Mechanical Eng., 2021
University of Southern California
Bachelor of Technology, 2016
National Institute of Technology Karnataka
News
- Apr 2024: Successfully completed my Ph.D. thesis proposal, I am a Ph.D. Candidate now!
- Mar 2024: This Summer, I will intern at Toyota Research Institute in their Mobile Manipulation Perception team in Los Altos
- Nov 2023: Aerodef 2023: Our poster on AI-Powered Smart Robotic Cells for Prepreg Composite Layup Automation received the graduate runners-up prize Link
- Oct 2023: I presented our paper on physics-informed robotic screw driving at IROS 2023 Paper Link
- Aug 2023: I interned at Amazon Robotics as an Applied Scientist II intern in their stow manipulation team in Seattle
- Mar 2023: IEEE Spectrum featured my ICRA paper video Article
Research
Experience
Applied Science Intern
Worked with the perception team in the Stow Manipulation Project
Research Assistant
Realization of Robotics Systems Lab
Team lead for industry funded projects for developing advanced robotic solutions
Robotics Technologist
Rolls-Royce Plc
Worked with research partners to mature technology beyond TRL 4
Graduate Engineer Trainee
General Motors India Pvt. Ltd.
Selected as a part of the flagship campus connect program by GM India
Publications
Search for a specific publication filtering publications.
(2023).
Physics-Informed Learning to Enable Robotic Screw-Driving Under Hole Pose Uncertainties.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
(2023).
Inverse Reinforcement Learning Framework for Transferring Task Sequencing Policies from Humans to Robots in Manufacturing Applications.
IEEE International Conference in Robotics and Automation.
(2022).
Physics Informed Synthetic Image Generation for Deep Learning based detection of wrinkles and folds.
ASME Journal of Computing and Information Science in Engineering.
(2022).
Synthetic image-assisted deep learning framework for detecting defects during composite sheet layup.
ASME IDETC-CIE Conference, 2022.
(2022).
Visual servo-based trajectory planning for fast and accurate sheet pick and place operations.
ASME Manufacturing Science and Engineering Conference.
(2021).
A Simulation-Based Grasp Planner for Enabling Robotic Grasping during Composite Sheet Layup.
IEEE International Conference in Robotics and Automation.
(2021).
A Digital Twin for Automated Layup of Prepreg Composite Sheets.
ASME Journal of Manufacturing Science and Engineering.
(2021).
A Digital Twin for Automated Layup of Prepreg Composite Sheets.
ASME Manufacturing Science and Engineering Conference.
(2021).
Toolpath Generation for Robot Filleting.
Internatoinal Conference on Advanced Surface Enhancement.
(2021).
An adaptive framework for robotic polishing based on impedance control.
The International Journal of Advanced Manufacturing Technology.
(2019).
In-process virtual verification of weld seam removal in robotic abrasive belt grinding process using deep learning.
Robotics and Computer-Integrated Manufacturing.
Projects
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Multi-Robot Cell for Automated Composite Layup on a Rotating Tool
Composite manufacturing is an industry that is growing rapidly. In this project, we collaborated with Advanced Technology Group at Lockheed Martin to design a multi-robot cell for sheet manipulation, draping and heating. No programming is required and an easy to use interface enables quick setup times with 30% reduction in touch time.
A Multi-Arm Robotic Assistant for Sheet Manipulation and Draping
Sheet manipulation for highly complex tasks such as prepreg composite layup is complex and challenging. The sheets used in such processes are large in size and difficult to manipulate using a single robot. In this project, the focus was to develop a multi-robot assistant system for aiding an operator in composite sheet layup task.
Accomplishments
Best Paper Award at IDETC-CIE 2022
Viterbi Graduate Student Fellowship
Academic Excellence Award
NSF Travel Award for ASME MSEC & IDETC-CIE Conferences (2021, 2022)