Sahit Chintalapudi
Student at Learning-and-Intelligent-Systems
Cambridge, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolSahit Chintalapudi is a PhD student at MIT specializing in motion planning, control, and reinforcement learning for robotic manipulation, supervised by Leslie Kaelbling and Tomas Lozano-Perez. With 11 years of hands-on experience spanning research roles at DeepMind, Georgia Tech, Carnegie Mellon, and University of Washington, he blends theory with systems work—implementing factor-graph Gaussian Process planners, MPC interfaces for AutoRally, and RL-based manipulation pipelines. He has contributed to published motion- and footstep-planning research and built infrastructure for learning from demonstration and curriculum generation in real-world robotics. Comfortable across C++, MATLAB, ROS, and modern ML toolchains, Sahit also has product-facing experience from internships and student leadership roles that highlight his ability to move ideas from simulation to hardware. An underappreciated thread in his background is repeated emphasis on simulation-to-hardware transfer, from Gazebo parade-float sims to AutoRally and industrial assembly policies.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Massachusetts Institute of TechnologyBachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Georgia Institute of TechnologyGPA: 4.0, GPA: 4.0 at County College of MorrisHigh School, GPA: 4.0, High School, GPA: 4.0 at Mount Olive High School
Github Skills (60)
robotics10
gazebosim10
python10
machine-learning10
verification10
deep-learning10
tensorflow10
racing9
data-science9
toolbox9
ml9
opencv9
deep-neural-networks9
drake9
neural-network9
Programming languages (6)
Github contributions (5)
belindal/alfred-exploration
Nov 2021 - Dec 2021
Contributions:53 commits, 1 push in 12 days
AJLiu/rll-site
Jun 2017 - Mar 2019
Contributions:8 PRs, 28 pushes, 7 branches in 1 year 9 months
robot-learninglabrobotlearning-lab
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