I am a Lead Robotics Engineer at GrayMatter Robotics, where I develop advanced AI-driven solutions for the perception and planning stacks that power our robotic platforms to operate autonomously and reliably in high-variability, unstructured environments.
Previously, I earned my Ph.D. in Robotics from the University of Southern California, where I was part of the Realization of Robotics Systems Lab (RRoS), advised by Dr. Satyandra K. Gupta. My research focused on integrating physics-informed learning methods into robotic manipulation, with an emphasis on generalization, intuitive physics-based reasoning, and data efficiency in handling complex deformable objects ( Link to Dissertation ).
Before my Ph.D., I led multiple industry-funded projects at USC as a Master’s student and worked as a Robotics Engineer at Rolls-Royce in Singapore 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
- June 2025 Attended the Robotics Science and Systems Conference at USC in LA, where I co-authored a paper at the Space Robotics Workshop Link
- June 2025 Started working at GrayMatter Robotics as a Lead Robotics Engineer
- May 2025 I defended my Ph.D. thesis titled Physics-Informed AI Methods for Deformable Object Manipulation
- Apr 2025: Our paper on real-to-sim parameter learning for thin-shell deformable objects is accepted at ASME IDETC-CIE 2025 Conference Link
- Oct 2024: I am selected as one of the finalist for the Amazon Robotics Fall Research Symposium. I will be presenting my work on physics-informed learning for deformable object manipulation, in-person at their Boston office Link
Experience
Lead Robotics Engineer
Ph.D. Research Intern
Worked with the mobile manipulation team on Visual Place Recognition for grocery picking robot
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
Research
Featured Publications
Publications
Search for a specific publication filtering publications.
(2024).
Simulation-Assisted Learning for Efficient Bin-Packing of Deformable Packages in a Bimanual Robotic Cell.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
(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)