Divya Garikapati is a Staff Robotics System Safety Engineer at Google DeepMind, where she works on state-of-the-art Research on robot learning and focuses on AI Safety and alignment. Her past experience includes her role as a Lead Systems and Safety Engineer with Woven by Toyota North America (formerly Toyota Research Institute - TRI), where her work centered on the Research and Development (R&D) of Autonomous Vehicles (AVs), with a keen interest in Systems and Safety Engineering for AVs. Prior to this, Divya gained experience as an Embedded Controls Engineer with Cummins and Daimler.

She holds a Masters degree in Electrical Engineering: Systems from the University of Michigan, Ann Arbor, with a concentration in Embedded Controls.
Divya has been an active contributor to Standards Development activities within IEEE, SAE, and ISO committees, driven by her commitment to ensuring safety and compliance for AV-related technologies. She currently chairs the working group for the "IEEE P3472 - Standard for Developing Parallel Autonomy Systems in Passenger Vehicles" and is a member of the SAE Ground Vehicle AI standards committee, as well as various other standards discussion groups such as IEEE P2851.1, SAE J3237, and IEEE P3332.

Further demonstrating her contributions to the research community, Divya has reviewed over 70 research papers for various journals and conferences. She also contributes to industry reports on AV-related topics to The Autonomous, SAE, and Automotive IQ, and has published multiple papers and patents related to ongoing research at Toyota.

Her research interests span Autonomous Robots, Autonomous Vehicles, Controls Engineering, Machine Learning, Artificial Intelligence, Verification and Validation, Simulation, Generative AI, Systems and Safety Engineering, and Human-Machine Interaction.