Summary
Prajwal Chidananda is an applied scientist with 10 years of experience building real-time perception and embodied intelligence systems for autonomous driving, robotics, and AR/VR. Currently at Wayve’s ML Horizons team, he focuses on end-to-end scene understanding, novel view synthesis, and dynamics using NeRFs, VLMs and LLMs to make systems accurate, robust and efficient. His prior work includes leading hand-tracking and gesture recognition at Magic Leap—shipping highly optimized on-device models and an automatic ground-truthing pipeline that slashed labeling cost—and a NeRF-based 6DoF object pose tracker at Giant.AI that achieved large speed and stability gains without labelled data. He combines deep research fluency with production engineering, frequently turning state-of-the-art literature into deployable systems that hit strict latency and resource budgets. Based in Sunnyvale, he blends a strong academic background from Carnegie Mellon with a pragmatic focus on lightweight, high-throughput models for embedded and real-world robotics applications. An under-the-radar strength is his knack for algorithmic speedups (orders-of-magnitude runtime improvements) while preserving or improving accuracy.
10 years of coding experience
7 years of employment as a software developer
B E, Electronics and Communications Engineering, 9.38, B E, Electronics and Communications Engineering, 9.38 at M.S. Ramaiah Institute Of Technology
Master of Science (M.S.), Electrical and Computer Engineering, Master of Science (M.S.), Electrical and Computer Engineering at Carnegie Mellon University
English, Kannada, Hindi