Ajinkya Jain is a Senior Software Engineer and roboticist with 12 years of experience blending AI, machine learning, and control theory to enable dexterous robot manipulation. He holds a Ph.D. from UT Austin and has published at CoRL, RSS, and IROS while open-sourcing implementations that bridge research and production. His work spans learning object interaction models from images and demonstrations, trajectory optimization under uncertainty, and practical robot systems built in Python and C++ with PyTorch/TensorFlow. At companies from Vicarious to Intrinsic and now Google, he has shipped high-precision visual servoing and planning systems that demonstrate sim-to-real robustness. Notably, his Ph.D. contributions include a POMDP-guided trajectory optimizer and a hybrid kinematics learning method that improved articulation accuracy up to 3x, reflecting a rare mix of theoretical depth and hands-on engineering.
13 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Mechanical Engineering, Doctor of Philosophy (Ph.D.), Mechanical Engineering at The University of Texas at Austin
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