Ruo Yu (David) Tao

Computer Science Ph.D. Student @ Brown
Email: ruo_yu_tao "at" brown "dot" edu
Resume: here

I'm a PhD student researching reinforcement learning in the Intelligent Robot Lab at Brown University advised by George Konidaris. My current research interests and work are centered on agent-state and representation learning in partially observable environments for reinforcement learning. I also think eligibility traces are super neat.

Previous to this, I was a Computing Science M.Sc. (Thesis) student at the University of Alberta, co-advised by Adam White and Marlos C. Machado in the RLAI lab. Even further in my distant past, I was a First-class Honours and Dean's Honour List student studying Computer Science at McGill University. I was previously a research intern at both Mila and Microsoft Research.

If you're interested in collaborating on something, shoot me an email!

Publications

Novelty Search in Representational Space for Sample Efficient Exploration

Ruo Yu Tao, Vincent François-Lavet, Joelle Pineau

Oral presentation, NeurIPS 2020

Towards Solving Text-based Games by Producing Adaptive Action Spaces

Ruo Yu Tao, Marc-Alexandre Côté, Xingdi Yuan, Layla El Asri

Oral presentation, WordPlay workshop NeurIPS 2018

TextWorld: A Learning Environment for Text-based Games

Marc-Alexandre Côté, Ákos Kádár, Xingdi Yuan, Ben Kybartas, Tavian Barnes, Emery Fine, James Moore, Ruo Yu Tao, Matthew Hausknecht, Layla El Asri, Mahmoud Adada, Wendy Tay, Adam Trischler

Computer Games Workshop IJCAI 2018

Education

Brown University

Ph.D. Student, 2022 - Current

Advisor: George Konidaris

University of Alberta

M.Sc. (Thes), 2020 - 2022

Advisors: Adam White and Marlos C. Machado

McGill University

Hons. B.Sc., 2016 - 2020

Undergraduate research advisor: Joelle Pineau.
First-Class Honors, Deans List.

Experience

National University of Singapore (NUS)

Over the summer/during the pandemic lockdown I was working on a research project advised by Lee Wee Sun on neural-based memory for RL and SLAM as a research assistant.

Mila (Quebec AI Institute)

At Mila, I was working on a research project in exploration in a model-based reinforcement learning setting starting in my final year of my undergraduate degree at McGill. The project is mentored by Vincent François-Lavet and advised by Joelle Pineau. Our paper on this was accepted to NeurIPS 2020 for an oral presentation. Check out our paper above!

Microsoft Research Montreal

During my time at Microsoft Research, I worked on reinforcement learning and natural language problems. I was advised by Marc-Alexandre Côté on projects including:

  • Adaptive text action spaces: see the above paper!

  • TextWorld: a reinforcement learning framework for agents to learn text-based games. Also see above!

Articles

  • I wrote a short piece on the dangers of reshaping in tensor manipulation libraries.

  • I was previously a contributor to an RL framework developed by the lovely people at FOR.ai. Check out the Journal of Open Source Software article here and the actual codebase itself here.

Miscellaneous things about me

  • I have a cooking blog you should check out!

  • In a past life (and technically still), I was a lieutenant in the Singapore Armed Forces and a Combat Engineer by vocation. This has helped a lot when I need to come up with interesting facts about myself. My go-tos are: I'm certified to disarm IEDs and I have a tank license.

  • I spent my childhood and teenage years in Beijing - I would still call it home for me!

  • I make a really good matcha latte.

  • I love to climb!

  • I made my sister's website.

Contact

Github
Google Scholar
LinkedIn
Come see me out people on my Twitter
Need a book recommendation? Check out my Goodreads