PeopleofSuperintelligence

Researcher

Rick Valenzano

Also known as Richard Valenzano

Rick Valenzano is a computer scientist who studies sequential decision making, the methods behind automated planning, heuristic search, reinforcement learning and game-playing systems. At the University of Alberta, where he earned a PhD in 2014, he helped build the ArvandHerd planner, which won the multi-core track of the International Planning Competition in 2011 and 2014. After a postdoctoral position at the University of Toronto and three years as an Applied Research Scientist at Element AI, he joined the computer science department at Toronto Metropolitan University in 2021. His work on reward machines with Sheila McIlraith and colleagues won the 2023 IJCAI-JAIR Best Paper Prize. He is an Assistant Professor at Toronto Metropolitan University and a Faculty Affiliate at the Vector Institute.

Badges

Timeline

  1. 2007–2009

    Degrees at Toronto and Alberta

    He earns a BSc in computer science and mathematics at the University of Toronto in 2007. At the University of Alberta, he completes an MSc in computing science in 2009, with a thesis on searching with multiple algorithm settings at once as an alternative to parameter tuning, supervised by Nathan Sturtevant.

  2. 2011–2014

    The ArvandHerd planner

    He develops ArvandHerd, a parallel planner built on Arvand, which was built on LAMA 2008. ArvandHerd wins the multi-core track of the International Planning Competition in 2011, and a new version wins the track again in 2014.

  3. 2014

    A PhD on heuristic search

    He completes a PhD in computing science at the University of Alberta in 2014. His thesis, Design Decisions on Suboptimal Heuristic Search-Based Systems, bounds how design decisions affect solution quality, shows the value of random exploration, and builds a multi-core portfolio of planners.

  4. 2018–2020

    Reward machines for reinforcement learning

    With Rodrigo Toro Icarte, Toryn Klassen and Sheila McIlraith, he coauthors an ICML paper in 2018 that uses a finite state automaton to expose the structure of a reinforcement learning reward function. The article Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning appears on arXiv in October 2020 and describes reward shaping, task decomposition and counterfactual reasoning with off-policy learning built on that structure.

  5. By 2021

    Applied scientist at Element AI

    By 2021, he has worked for three years as an Applied Research Scientist at Element AI, after a postdoctoral position at the University of Toronto. There he uses sequential decision making and forecasting methods on financial applications, as part of a team that develops a product that helps large institutional investors rebalance their portfolios.

  6. January 2021

    Assistant professor at TMU

    In January 2021, the Department of Computer Science at Toronto Metropolitan University welcomes him as an assistant professor. He aims to build up the university's background in artificial intelligence and to combine ideas from automated planning, reinforcement learning and game theory for sequential decision making.

  7. 2023

    A prize and a Vector affiliation

    In June 2023, he is named a Faculty Affiliate at the Vector Institute. The reward machines article he coauthored with Rodrigo Toro Icarte, Toryn Q. Klassen and Sheila A. McIlraith wins the 2023 IJCAI-JAIR Best Paper Prize for work that bridges AI planning, reinforcement learning and formal methods.

  8. As of October 2026

    Leading the Valenzano Lab

    He is an Assistant Professor in the Department of Computer Science at Toronto Metropolitan University and a Faculty Affiliate at the Vector Institute, where he leads the Valenzano Lab. In 2026, he coauthors Thread-Ordered Parallel Greedy Best First Search, which appears at SoCS 2026, and a study of breadth-first search and restarting random walks that appears at AAAI 2026.

Career

  1. Since 2023Vector InstituteFaculty Affiliate
  2. Since 2021Toronto Metropolitan UniversityAssistant Professor
  3. Until 2021Element AIApplied Research Scientist
  4. University of TorontoPostdoctoral Researcher

Education

  1. 2014University of AlbertaPhD
  2. 2009University of AlbertaMSc
  3. 2007University of TorontoBSc

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Rick Valenzano. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes Vector Institute. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.
  3. Nonprofit roles are 2.3 times as common in AI safetyIncludes Vector Institute. We estimate where people focused on safety, alignment and evaluation work. Nonprofit roles appear for 25.1% of safety people with known affiliations, compared with 11.0% in other areas.
  4. Universities (31%) and startups and other companies (25%) employ the largest shares of 2020–2026 entrantsIncludes Vector Institute. Among 819 people whose first recorded role started in 2020–2026 and who have a known current organization, 60% work in commercial sectors (25% at startups and other companies, 23% at frontier labs and 13% at big tech, with 9 in two), and 31% work at universities, compared with 66% for earlier entrants.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Rick Valenzano yet. Send us a free-licensed photo.

  1. Rick Valenzano - Department of Computer Science - Toronto Metropolitan University (TMU) torontomu.ca. Checked 22 October 2026.
  2. Nathan Sturtevant, University of Denver cs.du.edu. Checked 22 October 2026.
  3. Professor Rick Valenzano - Publications sites.google.com. Checked 22 October 2026.
  4. Professor Rick Valenzano - Software sites.google.com. Checked 22 October 2026.
  5. Rick Valenzano - Vector Institute for Artificial Intelligence vectorinstitute.ai. Checked 22 October 2026.
  6. [2010.03950] Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning arxiv.org. Checked 22 October 2026.
  7. New Faculty Profile: Rick Valenzano - Department of Computer Science - Toronto Metropolitan University (TMU) torontomu.ca. Checked 22 October 2026.
  8. IJCAI-JAIR Awards | Journal of Artificial Intelligence Research jair.org. Checked 22 October 2026.
  9. Professor Rick Valenzano sites.google.com. Checked 22 October 2026.
  10. Professor Rick Valenzano - Research Group sites.google.com. Checked 22 October 2026.