Udaya Ghai
Papers
1
Total Citations
5
H-Index
1
About
Udaya Ghai is a researcher whose work sits at the intersection of control theory, differentiable programming, and robotics. His most notable contribution is the development of **Deluca**, a pioneering open-source differentiable control library that provides natively differentiable physics and robotics environments. This work, which has garnered 5 citations, enables researchers to auto-differentiate through simulation dynamics, dramatically accelerating the training of gradient-based control methods. By creating a benchmarking suite alongside these environments, Ghai has provided the community with a standardized platform for comparing and advancing control algorithms. His research addresses a critical bottleneck in robotics: the need for fast, efficient training of controllers in complex physical systems. Through Deluca, Ghai has made differentiable simulation accessible, allowing for rapid prototyping and optimization of control policies. This contribution is particularly impactful for students and researchers working in reinforcement learning, optimal control, and robotic manipulation, as it bridges the gap between traditional model-based control and modern data-driven approaches.
Research Focus
Key Achievements
Top Papers
- 1