Parth Potdar

I build ML and robotics systems that work in the real world.

I am a recent MEng graduate from the University of Cambridge specializing in bridging the gap between research and real-world deployment. My approach is grounded in first principles and shaped by experience across the autonomy stack, combining a foundation in Machine Learning, Computational Neuroscience, and Robotics with the engineering rigor required to make systems work reliably under uncertainty.

This perspective has guided my work, from building a safety-critical autonomy MVP in an early-stage startup, to conducting research in vision-based tactile sensing, and the end-to-end design of aerial robotics systems. Across these projects, I have focused on designing systems that not only perform well, but are robust and deployable into the noisy real-world.

I am motivated by the challenge of solving complex problems, and turning research into systems that work in the real-world. I am looking to apply my blend of research and engineering skills to solve the next generation of problems through Embodied AI and robotics.