Gautham Narayan Narasimhan

Hello! I am currently a Research Assistant at the Robotics Institute (RI) at Carnegie Mellon University. Previously I completed my masters thesis with Prof. David Held at CMU.

I study machine learning algorithms that enable robots to perceive and manipulate general purpose objects. Currently I'm working on model based reinforcement learning for robotic pouring tasks.

Contact: gauthamn (at) andrew.cmu.edu

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Research and Publications
clean-usnob Learning Material Properties using a Differentiable Simulator for Liquid/Granular manipulation
Gautham Narayan, Xingyu Lin, David Held
In progress

Currently training a Material Point Method based differentiable simulator to learn material properties. Cross Entropy Method has shown good performance for trajectory optimization once the material properties have been learnt. More details coming soon ...

clean-usnob ROLL: Visual Self-Supervised Reinforcement Learning with Object Reasoning
Yufei Wang*, Gautham Narayan*, Xingyu Lin, Brian Okorn, David Held
* denotes equal contribution
Conference on Robot Learning, CoRL 2020

Unknown object segmentation to learn a visual representation that can reason about occlusions. Our method achieves state of the art on object manipulation benchmarking tasks.

[Paper] [Website]
clean-usnob Segmentation for learning image based goal conditioned policies
Gautham Narayan, David Held
Master's Thesis - Carnegie Mellon University, 2020
clean-usnob Experimental Droplet Spatter Analysis Using Least Squares Approximation
Gautham Narayan, Bill Eddy
Internal Report - NIST Center of Excellence in Forensic Science, 2020
clean-usnob Effect of winglets induced tip vortex structure on the performance of subsonic wings
Gautham Narayan, Bibin John
Elsevier - Aerospace Science and Technology, 2016

Design optimization for subsonic winglets using computational fluid dynamics.

[Paper]

Source