James R. Wright

Assistant Professor, Department of Computing Science
Fellow & Canada CIFAR AI Chair, Amii
University of Alberta
Edmonton, Alberta
james.wright@ualberta.ca

Academic Employment

2018–present
Assistant Professor
Department of Computing Science
University of Alberta, Edmonton, Alberta.
2016–2018
Postdoctoral Researcher
Microsoft Research, New York, NY.
2015
Visiting Graduate Student
Simons Institute for the Theory of Computing
University of California, Berkeley, CA.

Education

2010–2016
Doctor of Philosophy (Computer Science)
Dissertation: Modeling Human Behavior in Strategic Settings.
ACM SIGecom Doctoral Dissertation Award (Honorable Mention)
University of British Columbia, Canada
2007–2010
Master of Science (Computer Science)
Thesis: Beyond Equilibrium: Predicting Human Behaviour in Normal Form Games
University of British Columbia, Canada
1995–2000
Bachelor of Science (Computing Science)
Simon Fraser University, Canada

Publications

Journals

  1. Exploiting Action Impact Regularity and Exogenous State Variables for Offline Reinforcement Learning. 
    Vincent Liu, James R. Wright, Martha White.
    Journal of Artificial Intelligence Research, Volume 77, pages 71–101, May 2023.
  2. Why Do Software Developers Use Static Analysis Tools? A User-Centered Study of Developer Needs and Motivations. 
    Lisa Nguyen Quang Do, James R. Wright, and Karim Ali.
    IEEE Transactions on Software Engineering, 2020.
  3. How can machine learning aid behavioral marketing research? 
    Linda Hagen, Kosuke Uetake, Nathan Yang, Bryan Bollinger, Allison J. B. Chaney, Daria Dzyabura, Jordan Etkin, Avi Goldfarb, Liu Liu, K. Sudhir, Yanwen Wang, James R. Wright, and Ying Zhu.
    Marketing Letters, 2020.
  4. Incentivizing Evaluation with Peer Prediction and Limited Access to Ground Truth. 
    Xi Alice Gao, James R. Wright, and Kevin Leyton-Brown.
    Artificial Intelligence 275, 2019.
    (supersedes Gao, Wright, and Leyton-Brown [2016])
  5. Learning When to Stop Searching. 
    Daniel G. Goldstein, R. Preston McAfee, Siddarth Suri, and James R. Wright.
    Management Science 66:3, pages 1375–1394, March 2020.
    (Full version of Goldstein et al. [2017])
  6. Level-0 Models for Predicting Human Behavior in Games. 
    James R. Wright and Kevin Leyton-Brown.
    Journal of Artificial Intelligence Research, Volume 64, pages 357–383, February 2019.
    (supersedes Wright & Leyton-Brown [2014])
  7. Predicting Human Behavior in Unrepeated, Simultaneous-Move Games. 
    James R. Wright and Kevin Leyton-Brown.
    Games and Economic Behavior, Volume 106, pages 16–37, November 2017.
    (supersedes Wright & Leyton-Brown [2010, 2012])

Peer-Reviewed Conferences

  1. How to Evaluate Behavioral Models. 
    Greg d'Eon, Sophie Greenwood, Kevin Leyton-Brown, and James R. Wright.
    AAAI 2024: AAAI Conference on Artificial Intelligence, to appear.
    Oral presentation.
  2. Guarantees for Self-Play in Multiplayer Games via Polymatrix Decomposability. 
    Revan MacQueen and James R. Wright.
    NeurIPS 2023: Thirty-seventh Conference on Neural Information Processing Systems, to appear.
  3. Finding an Optimal Set of Static Analyzers To Detect Software Vulnerabilities. 
    Jiaqi He, Revan MacQueen, Natalie Bombardieri, Karim Ali, James R. Wright, and Cristina Cifuentes.
    ICSME 2023: IEEE International Conference on Software Maintenance and Evolution (Industry Track), 2023.
  4. Non-strategic Econometrics (for Initial Play). 
    Daniel Chui, Jason Hartline, and James R. Wright.
    AAMAS 2023: International Conference on Autonomous Agents and Multiagent Systems, pages 634–642, 2023.
  5. The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Models. 
    Greg d'Eon, Jason d'Eon, James R. Wright, and Kevin Leyton-Brown.
    ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT), 2022.
  6. Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games. 
    Dustin Morrill, Ryan D'Orazio, Marc Lanctot, James R. Wright, Michael Bowling, and Amy Greenwald.
    ICML 2021: International Conference on Machine Learning, 2021.
  7. The Role of Accuracy in Algorithmic Process Fairness Across Multiple Domains. 
    Michele Albach and James R. Wright.
    EC-21: ACM Conference on Economics and Computation, 2021.
  8. Hindsight and Sequential Rationality of Correlated Play. 
    Dustin Morrill, Ryan D'Orazio, Reca Sarfati, Marc Lanctot, James R. Wright, Amy Greenwald, and Michael Bowling.
    AAAI 2021: AAAI Conference on Artificial Intelligence, 2021.
  9. Incentivizing Evaluation with Peer Prediction and Limited Access to Ground Truth (Extended Abstract). 
    Xi Alice Gao, James R. Wright, and Kevin Leyton-Brown.
    IJCAI-PRICAI 2020 Journal Track, 2020.
  10. A Formal Separation Between Strategic and Nonstrategic Behavior. 
    James R. Wright and Kevin Leyton-Brown.
    EC-20: ACM Conference on Economics and Computation, 2020.
  11. Alternative Function Approximation Parameterizations for Solving Games: An Analysis of f-Regression Counterfactual Regret Minimization. 
    Ryan D'Orazio, Dustin Morrill, James R. Wright, and Michael Bowling.
    AAMAS 2020: International Conference on Autonomous Agents and Multiagent Systems, 2020.
  12. Learning in the Repeated Secretary Problem. 
    Daniel G. Goldstein, R. Preston McAfee, Siddarth Suri, and James R. Wright.
    EC-17: ACM Conference on Economics and Computation, 2017.
    (Abstract)
  13. Deep Learning for Predicting Human Strategic Behavior. 
    Jason Hartford, James R. Wright, and Kevin Leyton-Brown.
    NIPS 2016: Annual Conference on Neural Information Processing Systems, 2016.
    Oral presentation.
  14. Mechanical TA: Partially Automated High-Stakes Peer Grading. 
    James R. Wright, Chris Thornton, and Kevin Leyton-Brown.
    SIGCSE-15: ACM Technical Symposium on Computer Science Education,
    pages 96–101, 2015.
  15. Level-0 Meta-Models for Predicting Human Behavior in Games. 
    James R. Wright and Kevin Leyton-Brown.
    EC-14: ACM Conference on Economics and Computation, pages 857–874, 2014.
  16. Behavioral Game-Theoretic Models: A Bayesian Framework For Parameter Analysis. 
    James R. Wright and Kevin Leyton-Brown.
    AAMAS-2012: International Conference on Autonomous Agents and Multiagent Systems, pages 921–928, 2012.
    Best student paper (runner up).
  17. Beyond Equilibrium: Predicting Human Behavior in Normal Form Games. 
    James R. Wright and Kevin Leyton-Brown.
    AAAI-10: AAAI Conference on Artificial Intelligence, pages 901–907, 2010.

Other Venues

  1. Disinformation, Stochastic Harm, and Costly Effort: A Principal-Agent Analysis of Regulating Social Media Platforms. 
    Shehroze Khan and James R. Wright.
    Cooperative AI Workshop at NeurIPS, 2021.
  2. Bounds for Approximate Regret-Matching Algorithms. 
    Ryan D'Orazio, Dustin Morrill, James R. Wright.
    Bridging Game Theory and Deep Learning Workshop at NeurIPS, 2019.
  3. A Formal Separation Between Strategic and Nonstrategic Behavior. 
    James R. Wright and Kevin Leyton-Brown.
    Workshop on Behavioral EC at ACM Conference on Economics and Computation, 2019.
  4. Incentivizing Evaluation via Limited Access to Ground Truth:
    Peer-Prediction Makes Things Worse.
     
    Xi Alice Gao, James R. Wright, and Kevin Leyton-Brown.
    Workshop on Algorithmic Game Theory and Data Science at ACM Conference on Economics and Computation, 2016.
  5. Linear Solvers for Nonlinear Games: Using Pivoting Algorithms to Find Nash Equilibria in n-Player Games. 
    James R. Wright, Albert Xin Jiang, and Kevin Leyton-Brown.
    SIGecom Exchanges, volume 10, number 1, pages 9–12, 2011.

Invited Talks

PKU
A Formal Separation Between Strategic and Nonstrategic Behavior.
Peking University.
Beijing, China (virtual talk). 2020.
DLRLSS-2019
Multiagent Systems.
At Deep Learning & Reinforcement Learning Summer School.
Edmonton, Alberta. 2019.
Choice-2019
Algorithmic Behavioral Modeling.
At 11th Triennial Invitational Choice Symposium.
Chesapeake Bay, Maryland. 2019.
PGT-2018
Predicting Human Strategic Behavior: From Behavioral Economics to Deep Learning.
At Workshop on Predictive Game Theory,
Evanston, Illinois. 2018.
YoungEC'17
Algorithmic Modeling of Human Behavior.
At Young Researcher Workshop on Economics and Computation,
Tel Aviv, Israel. 2017.
INFORMS-2017
Deep Learning for Human Strategic Modeling.
At INFORMS Annual Meeting,
Houston, Texas. 2017.
IFORS-2017
Deep Learning for Human Strategic Modeling.
At 21st Conference of the International Federation of Operations Research Societies,
Québec City, Québec. 2017.
ISMP-2015
Level-0 Meta-Models for Predicting Human Behavior in Games. At 22nd International Symposium on Mathematical Programming,
Pittsburgh, Pennsylvania. 2015.
SFI
Evaluating Set-Valued Predictions.
At Combining Information Theory and Game Theory,
Santa Fe Institute, New Mexico. 2012.
LANL
Beyond Equilibrium: Predicting Human Behavior in Normal Form Games.
At Design and Control of Systems of Goal-Directed Agents; From Game Theory to Game Engineering,
Los Alamos National Laboratory, New Mexico. 2010.
BQGT
Beyond Equilibrium: Predicting Human Behavior in Normal Form Games.
At Behavioral and Quantitative Game Theory Conference on Future Directions,
Newport Beach, California. 2010.

Funding

2019–2025
NSERC Discovery Grant
Natural Sciences and Engineering Research Council of Canada
(Total value: $195,000)
2019–2020
NSERC Discovery Launch Supplement
Natural Sciences and Engineering Research Council of Canada
(Total value: $12,500)
2019–2020
Amii Resource Allocation Panel
Alberta Machine Intelligence Institute
(Total value: $78,860)
2018–2023
Canada CIFAR AI Chair
Canadian Institute for Advanced Research
(Total value: $500,000)
2018
NVIDIA GPU Grant
NVIDIA Corporation (Donation value in CAD: $1,512)

Awards

2017
Honorable Mention: ACM SIGecom Doctoral Dissertation Award
ACM Special Interest Group on E-commerce
2010–2013
UGF: University Graduate Fellowship
University of British Columbia, Canada
Declined in 2010–2012 to hold NSERC
(Total value: $80,000)
2010–2012
NSERC Canada Graduate Scholarship (Ph.D.)
Natural Sciences and Engineering Research Council of Canada
(Total value: $105,000)
2008–2009
NSERC Canada Graduate Scholarship (M.Sc.)
Natural Sciences and Engineering Research Council of Canada
(Total value: $17,500)

Graduate Students Supervised

2019–
Greg d'Eon (UBC PhD, co-supervised with Kevin Leyton-Brown)
2023–
Csongor Szepesvari (MSc)
2023–
Bahar Boroomand (MSc)
2023–
Alireza Masoumian (MSc)
2022–
Mohammad Mahdi Maghouli (MSc)
2021–
Rohini Das (MSc, co-supervised with Neil Burch)
2020–2023
Amirmohsen Sattarifard (MSc, co-supervised with Matt Taylor)
2021–2023
Revan MacQueen (MSc)
2020–DNC
Niko Yasui (PhD)
2020–2022
Shehroze Khan (MSc)
2019–2021
Michele Albach (MSc)
2019–2022
Daniel Chui (MSc)
2019–2020
Ryan D'Orazio (MSc, co-supervised with Matt Taylor, now at MILA)

Supervisory / Examination Committees

2023
Nathan Wispinski (PhD)
2023
Li-Hao Kuan (MSc)
2022
Saidur Rahman (MSc)
2021–
Kristen Yu (PhD)
2021–2023
Vincent Liu (PhD)
2021
Housam Babiker (PhD)
2020
Varun Bhatt (MSc)
2020
Sam Sokota (MSc)
2020
Niko Yasui (MSc)
2019
Trevor Davis (PhD)
2019
Adam Parker (PhD)
2019–2022
Negar Hassanpour (PhD)
2019
Wesley Chung (MSc)
2019
Md Solimul Chowdhury (PhD)
2018–2020
Craig Sherstan (PhD)
2018
Marius Stanescu (PhD)

External Examiner

2023
David Milec (PhD, Czech Technical University)
2022
Atrisha Sarkar (PhD, Waterloo University)
2022
David Milec (PhD proposal, Czech Technical University)
2018
Moshe Mash (PhD, Ben-Gurion University)

Service

2020–2023
Amii Resource Allocation Panel (co-chair starting 2022)
2022
Graduate Admissions Strategy Committee
2020–2023
Graduate Admissions Committee
2020
Program Co-chair: Graduate Student Symposium (at 33rd Canadian Conference on Artificial Intelligence)
2019
Program Committee: Deep Learning & Reinforcement Learning Summer School
2017
Co-organizer: 2017 New York Computer Science and Economics Day (NYCE Day)
2015–2017
Member: NSF PI Forum on Peer Assessment
2014–2015
Student representative: Faculty Recruiting Committee

Senior Program Committees / Area Chair

2022, 2023
International Conference on Learning Representations.
2022
AAAI Conference on Artificial Intelligence.
2019, 2020, 2022, 2023
ACM Conference on Economics and Computation.

Program Committees

2023
European Conference on Artificial Intelligence.
2021, 2022
Equity and Access in Algorithms, Mechanisms, and Optimization.
2017, 2020
International Conference on Autonomous Agents and Multi-Agent Systems.
2019–2023
Conference on Neural Information Processing Systems.
2019, 2023
International Conference on Machine Learning.
2019–2020, 2023
AAAI Conference on Human Computation and Crowdsourcing.
2018–2020
AAAI Workshop on Reinforcement Learning in Games.
2017–2021
The Web Conference (formerly International World Wide Web Conference).
2017, 2018, 2021
ACM Conference on Economics and Computation.
2016–2021
AAAI Conference on Artificial Intelligence.

Journal Reviews

I have reviewed for various journals without serving on an editorial board. These include American Economic Review, Artificial Intelligence Journal, Journal of Artificial Intelligence Research, Journal of Autonomous Agents and Multi-Agent Systems, Econometrica, Journal of Economic Behavior and Organization, Journal of Economic Theory, Journal of the European Economic Association, Games and Economic Behavior, IEEE Transactions on Games, Progress in Artificial Intelligence, Journal of Machine Learning Research, Nature Machine Intelligence, and ACM Transactions on Economics and Computation.

Conference Reviews

I have reviewed for various conferences without serving on a program committee. These include SODA, WINE, IJCAI.

Teaching

Taught at University of Alberta

2024
CMPUT 654: Modelling Human Strategic Behaviour (graduate)
2024
CMPUT 261: Introduction to Artificial Intelligence
2023 (twice)
CMPUT 261: Introduction to Artificial Intelligence
2022
CMPUT 261: Introduction to Artificial Intelligence
2022
CMPUT 654: Modelling Human Strategic Behaviour (graduate)
2022
CMPUT 366: Intelligent Systems
2021 (twice)
CMPUT 455: Search, Knowledge, and Simulations
2021
CMPUT 366: Intelligent Systems
2020
CMPUT 296: Basics of Machine Learning
2020 (twice)
CMPUT 366: Intelligent Systems
2020
CMPUT 654: Modelling Human Strategic Behaviour (graduate)
2019
CMPUT 654: Modelling Human Strategic Behaviour (graduate)
2019
CMPUT 366: Intelligent Systems

Other Courses (during graduate studies)

My duties as an instructional assistant for the various massively open online courses listed below included constructing new content (problem sets and exams), cross-checking new video content for slide typos and misstatements, and monitoring and responding to student questions in online forums.

As an instructional assistant for Computers and Society, I led the design and implementation effort of the Mechanical TA peer grading system. I also constructed exams, and assisted with curriculum development.

As a teaching assistant for Multiagent Systems, I constructed quizzes, exams, and assignments, and assisted in the day-to-day operation of the class.

2014
Game Theory II (Massively Open Online Course)
Instructional Assistant, Coursera/University of British Columbia
2014
Game Theory (Massively Open Online Course)
Instructional Assistant, Coursera/University of British Columbia
2014
CPSC 532L: Multiagent Systems (graduate)
Teaching Assistant, University of British Columbia
2014
CPSC 430: Computers and Society
Instructional Assistant, University of British Columbia
2013
Game Theory II (Massively Open Online Course)
Instructional Assistant, University of British Columbia
2013 (twice)
Game Theory (Massively Open Online Course)
Instructional Assistant, Coursera/University of British Columbia
2013
CPSC 532L: Multiagent Systems (graduates)
Teaching Assistant, University of British Columbia
2013
CPSC 430: Computers and Society
Instructional Assistant, University of British Columbia
2009
CPSC 532L: Multiagent Systems (graduates)
Teaching Assistant, University of British Columbia
2008
CPSC 430: Computers and Society
Teaching Assistant, University of British Columbia
2007
CPSC 410: Advanced Software Engineering
Teaching Assistant, University of British Columbia

Last update: Jan 24/2024