PeopleofSuperintelligence

Researcher

Christian Muise

Christian Muise is an AI researcher whose work applies automated planning to decisions under uncertainty and embodied tasks. He earned computer science degrees at Carleton University and the University of Toronto, held research posts at the University of Melbourne and MIT, led dialogue-systems work at IBM, and joined Queen’s in 2020. His 2012 PRP paper received ICAPS’s 2022 Influential Paper Award, and a paper he coauthored on ALFRED planning won the CVPR Embodied AI challenge with a 36.07% unseen success rate. In 2025, he coauthored a paper on rigorous evaluation for LLM-based planning; he is an associate professor at Queen’s and directs the Mu Lab.

Badges

Timeline

  1. 2002–2014

    Degrees at Carleton and Toronto

    At Carleton University, he earns a Bachelor of Computer Science in Software and Computing with a minor in mathematics in 2007; Dr. Louis Nel advises his “Audio Panning in Ardour” thesis. At the University of Toronto, he earns a master’s degree in computer science in 2009 and a PhD in 2014, advised by Sheila A. McIlraith and J. Christopher Beck.

  2. 2013–2017

    Research fellowships in Melbourne and MIT

    At the University of Melbourne, he is a research fellow from 2013 to 2015 on “Foundations of Human-Agent Collaboration: Situation-Relevant Information Sharing.” At MIT’s CSAIL MERS group, he is a research fellow from 2016 to 2017 and studies plan synthesis under temporal uncertainty.

  3. 2017–2019

    Dialogue systems at IBM

    At IBM Research AI, he is a research staff member from October 2017 to December 2019. He studies goal-oriented planning and learning for dialogue systems and leads a team of five researchers and engineers on dialogue work.

  4. 2020

    Joining Queen’s University

    In January 2020, he joins Queen’s University as an assistant professor and heads the Mu Lab research group.

  5. 2022

    An ICAPS award for PRP

    His 2012 paper “Improved Non-deterministic Planning by Exploiting State Relevance,” coauthored with Sheila McIlraith and J. Christopher Beck, receives ICAPS’s 2022 Influential Paper Award. The paper uses state relevance to make policies more succinct and extends PRP to online planning for fully observable non-deterministic problems.

  6. 2022–2023

    An ALFRED challenge win

    In 2022, the approach in a paper he coauthors wins first place in CVPR’s ALFRED Embodied AI Challenge. The 2023 paper, “Egocentric Planning for Scalable Embodied Task Achievement,” reports a 36.07% unseen success rate in ALFRED’s simulated domestic-task benchmark.

  7. 2025

    Evaluating LLM-based planners

    In 2025, he coauthors “Make Planning Research Rigorous Again!” The paper argues that methods for rigorous design and evaluation from automated planning should guide work on large language model planners.

  8. As of October 2026

    Associate professor at Queen’s

    As of October 2026, he is an associate professor in the School of Computing at Queen’s University and directs the Mu Lab. His research interests include natural language processing, representation learning, and time-series forecasting.

Career

  1. Since 2020Queen's UniversityAssistant Professor
  2. 2017–2019IBM ResearchResearch Staff Member
  3. 2016–2017Massachusetts Institute of TechnologyResearch Fellow
  4. 2013–2015University of MelbourneResearch Fellow

Education

  1. 2014University of TorontoPhD
  2. 2009University of TorontoMaster’s degree in computer science
  3. 2007Carleton UniversityBachelor of Computer Science in Software and Computing

From the biography.

  1. 23% of people shaping AI who left a university for a company later returned to a universityIncludes Christian Muise. We estimate that 468 of the 2,011 people shaping AI who left a university for a company (23%) later returned to a university after a median of 5 years, and 163 of 829 (20%) made the reverse round trip.
  2. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Queen's University. 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.
  3. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Massachusetts Institute of Technology. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  4. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Queen's University. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.

Colleagues

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

Sources and credits

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  1. Christian Muise haz.ca. Checked 21 October 2026.
  2. Christian Muise - Vector Institute for Artificial Intelligence vectorinstitute.ai. Checked 21 October 2026.
  3. Influential Paper Award: International Conference on Automated Planning and Scheduling (ICAPS 2022) lanternfish-point-js8m.squarespace.com. Checked 21 October 2026.
  4. Improved Non-Deterministic Planning by Exploiting State Relevance | Proceedings of the International Conference on Automated Planning and Scheduling ojs.aaai.org. Checked 21 October 2026.
  5. Egocentric Planning for Scalable Embodied Task Achievement arxiv.org. Checked 21 October 2026.
  6. Make Planning Research Rigorous Again! arxiv.org. Checked 21 October 2026.
  7. Christian Muise > Queen’s School of Computing cs.queensu.ca. Checked 21 October 2026.
  8. Mu Lab > Queen’s School of Computing cs.queensu.ca. Checked 21 October 2026.