Shivin Dass

PhD Student In AI And Robotics at The University of Texas at Austin

Austin, Texas, United States
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Summary

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Senior
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Top School
Shivin Dass is a PhD student in AI and Robotics at UT Austin with nine years of experience bridging research and applied systems in imitation learning, reinforcement learning, and robot planning. He has developed robust RL representations and teleoperative imitation approaches during research roles at USC’s CLVR lab and earlier worked on multi-agent path planning at IIIT-Delhi’s CORAL lab. A hands-on builder who co-founded an edtech startup, he pairs strong full-stack backend experience (Django, SQL) with deep learning research, enabling reproducible robot learning experiments. Known for rigorous academic training—BTech with honors from IIIT-Delhi and an MS from USC—he brings both theoretical depth and practical engineering to robotic autonomy projects.
code9 years of coding experience
job4 years of employment as a software developer
bookMaster's degree, Computer Science, 4, Master's degree, Computer Science, 4 at University of Southern California
bookDoctor of Arts, Robot, Doctor of Arts, Robot at The University of Texas at Austin
bookClass XII, Science, Class XII, Science at Sardar Patel Vidyalaya
bookBachelor of Technology, Computer Science and Engineering, 9.49, Bachelor of Technology, Computer Science and Engineering, 9.49 at Indraprastha Institute of Information Technology, Delhi
languagesEnglish, Hindi
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Github Skills (16)

opengraph9
microdata9
rdfa9
json-ld8
semantic-web8
knife8
microformats8
algorithms6
html6
spoon6
css5
reinforcement-learning5
mobile5
javascript4
imitation-learning2

Programming languages (1)

Python

Github contributions (5)

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Contributions:8 commits, 7 pushes, 1 branch in 1 year 9 months
ShivinDass/inverse_rl

Dec 2019 - Jun 2022

Implementing the two pioneering IRL papers "Algorithms for Inverse Reinforcement Learning" - (Ng &Russell 2000) and "Maximum Entropy Inverse Reinforcement Learning" - (Ziebart et al. 2008)
Contributions:10 commits, 9 pushes, 1 branch in 2 years 6 months
reinforcement-learning
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