Aravind Sivaramakrishnan

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I am a Ph.D. candidate in Computer Science at Rutgers University. I am part of the PRACSYS lab, advised by Kostas Bekris. I am broadly interested in applying machine learning algorithms to improve the efficiency and robustness of robotic planning. I am excited about building robust, real-world robotics systems that integrate perception, planning and learning.

Prior to my Ph.D., I earned an MS in CS from Rutgers. I earned my undergraduate degree in Computer Science & Engineering from Amrita Vishwa Vidyapeetham University. In Summer 2018, I was an intern at Preferred Networks in Tokyo working with Wilson Ko and Kuniyuki Takahashi. In Summer 2022, I was a Research Intern at Bosch Austin working with Alessandro Allievi, Jarrett Holtz and Xuesu Xiao.


This page is perpetually under construction until I say otherwise. You can find me on Github and Twitter. My CV can be found here.

[Current Research] [Papers] [Teaching] [Projects] [Talks] [Courses] [Misc]

Current Research

Currently, I am working on improving the efficiency of motion planning for robots with significant dynamics using data-driven techniques.

I also collaborate with the DATA-INSPIRE TRIPODS Institute on data-informed dynamical systems theory, with an emphasis on robotic control.

I have worked with our lab's KUKA LBR iiwa and RoboMantis robots.

Conference and Journal Papers

Workshop Papers

Other Papers


In Spring 2023, I am the TA for CS590: Socially Cognizant Robotics.

I have instructed / TAed for CS440: Introduction to Artificial Intelligence (Su17, Sp18, Sp19, Su19, Fa19, Su20, Sp21, Su21, Sp22), CS520: Introduction to Artificial Intelligence (Sp17, Fa17, Fa19, Sp20, Fa20, Fa21, Fa22) and CS460/560: Introduction to Computational Robotics (Fa18).