# Sandeep Reddy Baddam > Robotics & AI @ Kodiak, CMU, Bosch • UW • NIT-W Location: Mountain View, California, United States Profile: https://flows.cv/sandeepreddybaddam Hello! I am Sandeep Reddy, a software engineer in the motion planning and controls team at Kodiak Robotics Inc., a driverless technology company in Mountain View, CA. I graduated from the University of Washington (UW), Seattle where I was part of the Robot Learning Lab, directed by Professor Byron Boots. As a Research Assistant, I’ve had the pleasure of working on the DARPA RACER program, conducting research on robot motion planning and inverse reinforcement learning for high-speed off-road level 4 autonomous vehicles. After graduation, I joined the Bosch Center for Artificial Intelligence, working on the precise navigation problem for Lunar Rover autonomous docking, which is prepared for a series of flight missions, in collaboration with NASA. Post internship, I joined as a visiting researcher at the Carnegie Mellon University Robotics Institute, working with Professor Andrea Bajcsy on safe human-robot interaction for autonomous driving. Broadly, my interests include planning algorithms, robot policy learning, safe human-robot interaction, and planning under uncertainty. Before joining UW, my undergraduate years at NIT Warangal, India, culminated in my leadership of a multifaceted SAE Baja off-road racing team, comprising 25 individuals spanning software, simulation, and hardware domains. Website: https://sandeepreddybaddam.github.io/about/ ## Work Experience ### Software Engineer @ Kodiak Jan 2024 – Present | Mountain View, California, United States @Motion planning and controls, Robot autonomy team ### Software Intern @ Kodiak Jan 2024 – Jan 2024 | Mountain View, California, United States @Motion planning and controls, Robot autonomy team • Demonstrated autonomy software features to modulate vehicle speed for rapid changes and discontinuities in off-road terrain • Built negative obstacle regression simulation set to validate planning behavior ### Visiting Researcher @ Carnegie Mellon University Robotics Institute Jan 2023 – Jan 2024 | Pittsburgh, Pennsylvania, United States • Integrated human behavior prediction models with reachability to maintain optimally conservative safety monitor (Backward Reachable Tube for active collision-avoidance) in interactive autonomous driving ### Robotics AI Software Intern @ Bosch Research Jan 2023 – Jan 2023 | Pittsburgh, Pennsylvania, United States Lunar CubeRover - NASA PFP • Formulated optimal control strategies under uncertainties for effective docking and achieved 100% success rate • Incorporated external uncertainty learning with expert demos making EKF quickly adapt to extraterrestrial environments ### Research Assistant @ Paul G. Allen School of Computer Science & Engineering Jan 2022 – Jan 2023 | Seattle, Washington, United States Level 4 autonomy @Robot Learning Lab, University of Washington • Executed Cross-entropy and Inverse RL to auto-tune the planner’s cost function saving 5 hours of manual tuning • Developed feature debugger that quantitatively compares nominal planner decisions with expert demonstrations • Implemented parallel version for cross-track error in MPC-based local planning that is 115X faster than serial computation ### Software Engineering Intern - Motion Planning @ Paul G. Allen School of Computer Science & Engineering Jan 2022 – Jan 2022 | Seattle, Washington, United States DARPA-funded RACER (Robotic Autonomy in Complex Environments with Resiliency) Program • Implemented and tested safety-critical motion planning algorithms for high-speed off-road level 4 autonomous vehicles ### Graduate Student Researcher @ University of Washington Jan 2022 – Jan 2022 | Seattle, Washington, United States @ Ultra Precision Controls Laboratory 1. Multi-robot Formation and Autonomous Navigation 2. Vision-based Autonomous Tracking and Platooning • Worked on path planning via vision for non-linear models using Feedback Linearization • Wrote obstacle avoidance algorithm to maintain multi-robot formation while navigation • Achieved making robots track each other in visually defined paths using computer vision and sensor fusion techniques • Built state-space models for different objectives and obtained stable PID along with UI development ### Research & Development Engineer [GTE] @ Bajaj Auto Ltd Jan 2021 – Jan 2021 | Pune, Maharashtra, India • Designed and validated a technique to find the precise cabin volume of any closed car with an accuracy of 98% • Wrote an optimization algorithm to find best HVAC design parameters • Experimented in real-time for different cars using data acquisition system ### Captain @ SAE Baja Off-road Racing - Team Spardhak Jan 2019 – Jan 2020 | National Institute of Technology, Warangal • Led a 25-member cross-functional off-road vehicle team including software, simulation, suspension, steering, and brakes • Developed graphical sim using IoT and Matlab’s ThingSpeak to obtain the running status of the vehicle with < 2-sec delay • Improved chassis design using grid-independent technique and achieved overall weight under 150kg maintaining min. fos of 1.8 ### Designer @ SAE Baja Off-road Racing - Team Spardhak Jan 2017 – Jan 2020 | National Institute of Technology, Warangal • Modeled and fabricated 3D printed prototypes to check the functionality and packaging of customized components • Analyzed and tested strength for various critical components of vehicle in simulations and validated through real-time testing ### IoT Internship @ SMARTBRIDGE EDUCATIONAL SERVICES PRIVATE LIMITED Jan 2017 – Jan 2017 | Hyderabad ## Education ### Master's degree in Mechanical Engineering (Robotics and Controls) University of Washington ### Bachelor's degree in Mechanical Engineering National Institute of Technology Warangal ## Contact & Social - LinkedIn: https://linkedin.com/in/sbaddam - Website: https://sandeepreddybaddam.github.io/about/ --- Source: https://flows.cv/sandeepreddybaddam JSON Resume: https://flows.cv/sandeepreddybaddam/resume.json Last updated: 2026-04-05