I am an Applied Research Scientist at Element AI. Previously I was a postdoctoral fellow at the University of Toronto after having completed my PhD in Computing Science at the University of Alberta. I am interested in artificial intelligence, particularly in the areas of
automated planning, heuristic search, knowledge representation, reinforcement learning, and game-playing agents. See the links to the left
for a list of publications.
Contact
me at x@cs.toronto.edu where x=rvalenzano (ie. replace "x" with "rvalenzano"
without the quotation marks). Try and grab that email address, you
meddling spambots.
You can also find me on LinkedIn.
NewsAugust 28, 2018 - Presenting paper on Reward Machines at the Montreal AI Symposium.
May 11, 2018 - Paper accepted at ICML 2018 on using finite state automata to specify reward functions in RL.
February 14, 2018 - Paper accepted at Canadian AI 2018 on using temporal logic to provide advice to an RL agent.
January 24, 2018 - Paper accepted at AAMAS 2018 on using temporal logic for specifying multiple tasks for an RL agent.
January 8, 2018 - Started working as an Applied Research Scientist at Element AI.
September 28, 2017 - Paper on k-polygon graphs accepted in the journal Discrete Applied Mathematics. Erdős number down to 3!
August 18, 2017 - Attending ML Ensemble
June 25, 2017 - Headed to Montreal for the Deep Learning Summer School
June 11, 2017 - Headed to Ann Arbor and Pittsburgh for RLDM and SoCS.
May 17, 2017 - Paper on understanding and solving the pancake sorting problem to appear at SoCS 2017.
February 8, 2017 - I have been given an award for being an Outstanding Program Committee Member at AAAI 2017.
February 6, 2017 - ArvandHerd 2014 is now on GitHub. See the Software page for more detail.
September 1, 2016 - I am co-teaching a graduate course on heuristic search and reinforcement learning with Professor Sheila McIlraith.
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