Amir-Hossein Karimi

Amir-Hossein Karimi is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, and a Vector Institute Faculty Affiliate. Prior to joining Waterloo, he gained extensive industry experience at Meta, Google Brain, and DeepMind, and provided AI-consulting services to numerous startups and incubators.

Professor Karimi’s research focuses on advancing the state of the art in artificial intelligence and charting the path for trustworthy human-AI symbiosis. His research interests include: the development of systems that can recover from or amend poor experiences caused by AI decisions, evaluation of the safety, factuality, and ethics of AI systems to foster trust in AI, and effectively combining human and machine abilities. His research explores the intersection of causal inference, explainable AI, and program synthesis.

Professor Karimi’s work has been showcased at esteemed AI and ML-related platforms such as NeurIPS, ICML, AAAI, AISTATS, ACM-FAccT, and ACM-AIES. His contributions to the field of algorithmic recourse have been acknowledged by these platforms through spotlight and oral presentations, as well as through a book chapter and a highly regarded survey paper in the ACM Computing Surveys.

• Artificial intelligence
• Machine learning
• Explainable AI
• Causal inference
• Algorithmic Recourse
• Counterfactual Explanations
• Program Synthesis
• Human-Machine Teaming
• Human-Machine Collaboration

• 2023, Doctor of Philosophy, Computer Science, ETH Zurich, Switzerland
• 2018, Masters of Mathematics, Computer Science, University of Waterloo, Canada
• 2015, Bachelor's Degree, Engineering Science, University of Toronto, Canada

• Google PhD fellowship (2021)
• NSERC Canada Graduate Scholarship (2018)
• Alumni Gold Medal Award (2018), University of Waterloo
• Spirit of Engineering Science Award (2015), University of Toronto

• ECE 457B - Fundamentals of Computational Intelligence
  • Taught in 2024
• ECE 657 - Tools of Intelligent Systems Design
  • Taught in 2024

* Only courses taught in the past 5 years are displayed.

• Moraffah, Raha, Amir-Hossein Karimi, Adrienne Raglin, and Huan Liu. "Socially Responsible Machine Learning: A Causal Perspective." In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 5819-5820. 2023.
• Karimi, Amir-Hossein, Gilles Barthe, Bernhard Schölkopf, and Isabel Valera. "A survey of algorithmic recourse: contrastive explanations and consequential recommendations." ACM Computing Surveys 55, no. 5 (2022): 1-29.
• Karimi, Amir-Hossein, Krikamol Muandet, Simon Kornblith, Bernhard Schölkopf, and Been Kim. "On the Relationship Between Explanation and Prediction: A Causal View." arXiv preprint arXiv:2212.06925 (2022).
• Karimi, Amir-Hossein, Bernhard Schölkopf, and Isabel Valera. "Algorithmic recourse: from counterfactual explanations to interventions." In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency, pp. 353-362. 2021.
• Morita P.P., Rocha A.S., Shaker G., Lee D., Wei J., Fong B., Thatte A., Karimi A., Xu L., Ma A., Wong A., and Boger J., Comparative Analysis of Gait Speed Estimation Using Wideband and Narrowband Radars, Thermal Camera, and Motion Tracking Suit Tec, Journal of Healthcare Informatics Research, Volume 4, 215-237, Canada, 2020.
• Karimi, Amir-Hossein, Gilles Barthe, Borja Balle, and Isabel Valera. "Model-agnostic counterfactual explanations for consequential decisions." In International Conference on Artificial Intelligence and Statistics, pp. 895-905. PMLR, 2020.
• Karimi A.-H., Chung A.G., Shafiee M.J., Khalvati F., Haider M.A., Ghodsi A., and Wong A., Discovery radiomics via a mixture of deep ConvNet sequencers for multi-parametric MRI prostate cancer classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 127, 45-53, Canada, 2017.
• Karimi A.H., Shafiee M.J., Scharfenberger C., Bendaya I., Haider S., Talukdar N., Clausi D.A., and Wong A., Spatio-temporal saliency detection using abstracted fully-connected graphical models, Proceedings - International Conference on Image Processing, ICIP, Volume 127, 694-698, Canada, 2016.
• Miller, Alexander, Adam Fisch, Jesse Dodge, Amir-Hossein Karimi, Antoine Bordes, and Jason Weston. "Key-value memory networks for directly reading documents." arXiv preprint arXiv:1606.03126 (2016).
• Karimi A.-H., Wong A., and Bizheva K., Automated detection and cell density assessment of keratocytes in the human corneal stroma from ultrahigh resolution optical coh, Biomedical Optics Express, Volume 2, 2905-2916, Canada, 2011.