Revanth Krishna Senthilkumaran

Robot Learning Engineering Intern at Bosch Center for Artificial Intelligence (BCAI) and Graduate Research Assistant at CMU Safe AI Lab

Robot LearningReinforcement LearningHumanoid Loco-manipulationROSPython (Data Science)UAV Path Planning

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About

I'm Revanth Krishna Senthilkumaran, currently a Robot Learning Engineering Intern at the Bosch Center for Artificial Intelligence and a Graduate Research Assistant at CMU's Safe AI Lab. My journey in robotics began at Purdue, where I led the Autonomous Robotics Club and launched the RISE conference while researching multi-robot systems and UAVs. I'm deeply passionate about humanoid loco-manipulation and tactile sensing—specifically, how we can use latent space predictions to make robot learning more effective. I've had the chance to contribute to the HTD framework and co-author several papers, and I'm always looking to collaborate with the brightest minds in the field. Whether it's discussing cross-embodiment or scaling student-led innovation, I'm eager to connect with fellow researchers and engineers who are pushing the boundaries of what robots can do.

Networking

What I can offer

›Technical expertise in robot learning and reinforcement learning
›Experience with quadrupeds, UAVs, and humanoids
›Leadership experience in large-scale robotics initiatives
›Hardware-in-the-loop (HIL) testing and prototyping skills

Looking for

›expanding my professional network
›exploring mutual opportunities in Robotics R&D
›collaborating with researchers and engineers to push boundaries in perception and interaction

Best fit for

Robotics researchersAI engineersHardware innovatorsAcademic mentors

Current Interests

Humanoid whole-body controlCross-embodiment transfer learningTactile sensing and dexterous manipulationAutonomous UAV flight systemsRobotics education and mentoring

Background

Career

Progressed from undergraduate research and teaching roles at Purdue to internships at AeroVironment and Bosch, currently pursuing an M.S. in Robotics at CMU.

Education

M.S. in Robotics, Carnegie Mellon University (2025–2027); B.S. in Computer Engineering, Purdue University (2021–2025)

Achievements

›Co-authored four research papers during undergraduate studies
›90.9% improvement in humanoid task success via HTD framework
›Launched RISE, the Midwest’s largest student-run robotics conference
›FAA Certified Remote Pilot – Part 107
›Graduated Purdue with Honors

Opinions

Predicting tactile signals in latent space is more effective and semantically meaningful for robot learning than raw signals.
Hands-on, student-led projects and hardware hackathons are essential for innovation.
Open research and sharing code are vital for the robotics community.