Rahul Shome

WEBSITE(S)| Personal Website | Kavraki Lab | Rice Academy

Rahul Shome is a Postdoctoral Research Associate in the Department of Computer Science, working with Prof. Lydia E. Kavraki at Kavraki Lab. He is also a Fellow of the Rice Academy. 

He is a roboticist who received his Ph.D. and M.S. in Computer Science from Rutgers University, New Brunswick working with Prof. Kostas Bekris. His thesis focused on task and motion planning challenges intended to endow robotic systems the ability to intelligently solve complex, realistic problems. His research places a keen interest on robots capable of interacting with objects and collaborating with humans in applications ranging from automating a factory floor, to cleaning our kitchens. His aim is to help build a future with responsible robots that work with humans. 

Previously, he has been recognized for his work on multi-robot motion planning with a Best Paper award at the conference IEEE MRS 2017, Los Angeles. His work on a robotic arm capable of robust and efficient packing of products also garnered a lot of media interest, and won a nomination for the Best Paper in Automation award at one of the largest international robotics research gathering IEEE ICRA 2019, Montreal. He has served on the organizing committee, and was a session chair in IEEE MRS 2019, New Brunswick. He has also authored a book chapter in the Encyclopedia of Robotics on asymptotically optimal sampling-based planners. 

More information about his research can be found at his personal website : www.rahulsho.me

Research Areas

Robotics, AI, Algorithms


PhD in Computer Science, Rutgers University

MS in Computer Science, Rutgers University

BTech in Computer Science and Engineering, National Institute of Technology, Durgapur, India

Honors & Awards

2020: Awarded the Rice Academy Postdoctoral Fellowship, Rice University

2019: Finalist for Best Paper in Automation Award for Towards Robust Product Packing with a Minimalistic End-Eector at IEEE International Conference on Robotics and Automation (ICRA)

2017: Best Paper Award for Scalable asymptotically-optimal multi-robot motion planning at the 1st IEEE International Symposium on Multi-robot and Multi-agent Systems (MRS)

2006, 2008: Awarded for Academic Excellence by the Governor of West Bengal


Changes or additions to profiles.rice.edu will not take effect on the Rice sub-sites until after its next refresh which occurs at 10:15am, 1:15pm, 4:15pm and 7:15pm daily. (This does not affect profiles.rice.edu)