Charvi is an aspiring AI researcher with a strong foundation in machine learning, control systems, and robotics. She is passionate about developing adaptive and interpretable models for complex, real-world environments.

Her research interests lie at the intersection of graph-based learning and reinforcement learning for dynamic decision-making. Charvi focused on explainability (xAI) and deep geometric learning for semantic scene graph localisation as part of the Mobile Robotics Group at the Oxford Robotics Institute. She also worked on adversarial robustness of Graph Neural Networks at the Max Planck Institute for Intelligent Systems.

She recently completed her MEng in Engineering Science at the University of Oxford, where she built a broad interdisciplinary background through a range of hands-on projects including designing controllers, satellite design and routing algorithms for 3D circuits as part of the selective EUROP scheme.

Charvi enjoys gardening, yoga, exploring new places, and outdoor activities that allow her to unwind and recharge.