Jaina P. Bhoiwala

Papers

Total Citations

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About

Jaina P. Bhoiwala is a researcher at the intersection of robotics and nuclear fusion, whose work focuses on deploying artificial intelligence to solve critical challenges in hazardous environments. Her primary research areas include deep reinforcement learning, autonomous navigation, and robotic manipulation for industrial inspection. Bhoiwala’s most notable contribution is her pioneering application of Deep Q-Learning to guide a robotic arm for the inspection of tokamak reactors—the complex, high-temperature devices used in fusion energy research. This work, published in 2018, demonstrated how AI-driven robotics can safely navigate the extreme conditions inside a fusion chamber, reducing human risk and enabling more efficient maintenance. Although her highly specialized paper has garnered 3 citations to date, its impact lies in laying foundational groundwork for autonomous systems in nuclear fusion, a field where safety and precision are paramount. Bhoiwala’s research bridges the gap between cutting-edge machine learning and practical engineering, offering a glimpse into a future where robots can operate in the most inaccessible and dangerous environments on Earth. Her contributions are particularly inspiring for students and researchers interested in applying AI to real-world, high-stakes problems in energy and robotics.