Teaching

teaching

I wish to empower as many students as I can to achieve their goals. At present, I pursue this by helping students figure out how to think about problems and deal with uncertainties of research life. Most of this is one-on-one interactions, but I find teaching and other means of engagement to be invaluable as well. Much of how I think today is shaped by influential teachers, advisors, colleagues and thinkers.

CSE 490R: Mobile Robots

https://courses.cs.washington.edu/courses/cse490r/19sp/

This was the first undergraduate course that I taught from scratch. My goal was to enable students to walk in with little to no knowledge of a robot and, in 11 weeks, walk out with a clear understanding of principles and challenges for any robotic system. With this in mind, we made brand new lectures that covered the principles of inference from sensor data, local control, global planning and robot learning. We designed a new set of 13 racecars, created programming assignments, tutorials aimed at guiding students through building their own fully autonomous robot. Every team successfully competed the final demo where they autonomously raced around 6th floor of CSE collecting hidden "gold". I am grateful to the superhuman TAs who were really the backbone of this class. As a first edition, the course was very well received (4.8/5.0) and the lectures much appreciated (4.9/5.0). While the next edition will be bigger and better, this quote was very encouraging:

... is an amazing lecturer who presented stimulating concepts each week and constantly challenged us to frame the material in novel ways and think like actual robotics researchers. TAs put incredible effort into making applicable assignments/labs, and though they were dense and a bit overwhelming at times, the labs vastly improved my skills and knowledge in so many ways!

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mushr

This entire effort is open-sourced. For more details visit: https://prl-mushr.github.io/.

Advising

As a postdoc, my most meaningful hours have been spent with the amazing students I interact with both in the lab and outside. This started early on in my PhD (Anirudh Vemula being the first test subject) where we had a large lab and no postdocs. The list of students I work with is ever growing — feel free to reach out to any of them for a candid account!

PhD Students
Aditya Mandalika, UW 2018 - Current
Gilwoo Lee, UW 2018 - Current
Brian Hou, UW 2018 - Current
Liyiming Ke, UW 2018 - Current
Matthew Schmittle, UW 2018 - Current
Mohak Bhardwaj, GaTech 2019 - Current
Jonathan Spencer, Princeton 2019 - Current
Brad Saund, UMich 2019 - Current
Rogerio Bonatti, CMU 2016 - Current
MS Students, Researchers
Johan Michalove, UW 2018 - Current
Ajinkya Kamat, UW 2018 - Current
Rosario Scalise, UW 2018 - Current
Vishal Dugar, CMU 2015 - 2017
Shushman Choudhury, CMU 2016 - 2017
Mohak Bhardwaj, CMU 2015 - 2017
Jit Roy Choudhury, CMU 2014 - 2015
MS Students, Researchers
A. J. Kruse, UW 2019 - Now
Max Thompson, UW 2019
Rajat Jenamani, IIT 2019
Rahul Vernwal, IIT 2018
Gleb Shevchuk, Stanford 2018

Even as an undergrad, I spent most of my time teaching friends and juniors how to fiddle with robots. My biggest accomplishment was starting the Kharagpur Robosoccer Group was at the time the most ambitious endeavor in student research. It has now gone one to win trophies in the international world cup and is a force to be reckoned with!


Workshops

Workshops are easily the most fun part of a conference! A good workshop is a long form discussion of a timely topic and is much appreciated by newcomers to a field. I have found this to be the maximally impactful activity for the robotics community and continue to seek co-organizers to explore new topics. Here are some of the workshops I have organized:

Machine Learning in Robot Motion Planning, IROS 2018

https://personalrobotics.cs.washington.edu/workshops/mlmp2018/

This was the most enjoyable workshop that I have organized. The topic, which I am quite passionate about, was indeed timely - how do we formalize priors in motion planning? Where do we get these priors from? What can we solve that is currently unsolved? The talks and papers were excellent and the discussions went well over time. The most satisfying part was that the local students from University of Madrid really appreciated the workshop and the exposure to such discussions.

Imitation Learning and its Challenges in Robotics, NeurIPS 2018

https://sites.google.com/view/nips18-ilr/

NeurIPS was a perfect platform for this workshop which had one central message - think about humans! A lot of imitation algorithms forget that humans provide the labels and these humans get tired, are often inconsistent, have trust issues and refuse to crash into things! We had a lot of good discussions that continues to influence my research today.

Complex Collaborative Systems: Closing the Loop, Learning, and Self-Confidence

http://theairlab.org/iros2017_workshop/

This was my first workshop as an organizer. It was co-organized by UTRC and we were fortunate to have a heavy industry presence. As a result, we had a good discussion on practical issues when we close the loop on complex systems that employ learning. The discussion went to interesting places like Not all data is information, Many real-world problems are satisficing, not reward maximization and Self-contained autonomy is a myth.