PeopleofSuperintelligence

Researcher

Peyman Mohajerin Esfahani

Peyman Mohajerin Esfahani is a control and optimization researcher whose work on decision-making under uncertainty draws on machine learning, including reinforcement learning. He studied electrical engineering at Sharif University of Technology in Iran and worked on a PhD at ETH Zurich's Automatic Control Laboratory from 2008 to 2014. In 2015, he and Daniel Kuhn posted a paper on Wasserstein distributionally robust optimization, and in 2016 he started as an assistant professor at TU Delft. There he received an ERC Starting Grant and the INFORMS Lanchester Prize in 2020, followed by the 2022 European Control Award. Since 2025, he is an associate professor at the University of Toronto, where he is cross-appointed between Mechanical & Industrial Engineering and Electrical & Computer Engineering.

Born
1982
Works
163
Citations
4,740
h-index
25
Badges

Years link to their sources. Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2000–2008

    Electrical engineering at Sharif

    He studies electrical engineering at Sharif University of Technology in Iran, with a BSc over 2000–2005 and an MSc over 2005–2008.

  2. 2008–2014

    PhD at ETH Zurich

    His PhD at ETH Zurich's Automatic Control Laboratory runs from 2008 to 2014.

  3. 2014–2016

    Postdoc at EPFL and ETH Zurich

    Between 2014 and 2016, he holds a dual postdoctoral appointment at the Risk Analytics and Optimization Chair at EPFL and the Automatic Control Laboratory at ETH Zurich. In 2015, he is also a visiting research scholar at MIT's Laboratory for Information and Decision Systems.

  4. 2015

    Wasserstein distributionally robust optimization

    In May 2015, he and Daniel Kuhn post a paper on data-driven distributionally robust optimization with the Wasserstein metric. It shows that decision problems over a Wasserstein ball around the training data can be reformulated as finite convex programs, often tractable linear programs, and carry finite-sample performance guarantees.

  5. 2016–2025

    Assistant professor at TU Delft

    TU Delft appoints him assistant professor in systems and control, and he takes up the post at its Delft Center for Systems and Control in October 2016. He is on the faculty there until joining the University of Toronto in 2025.

  6. 2020

    ERC grant and Lanchester Prize

    In 2020, he receives an ERC Starting Grant and the INFORMS Frederick W. Lanchester Prize. The grant project proposes a control design approach built on distributionally robust optimization, a decision-making model whose solutions are optimized against all distributions consistent with given prior information.

  7. 2022

    A European Control Award

    In 2022, as an associate professor at the Delft Center for Systems and Control, he receives the European Control Award. The award, sponsored by the European Control Association, recognizes his contributions to data-driven optimization and control and distributionally robust decision-making.

  8. Since 2025

    Associate professor at Toronto

    He joins the University of Toronto in 2025 as an associate professor in industrial engineering, cross-appointed with Electrical & Computer Engineering. His research group, the Decision, Learning & Control Lab, works on control theory, optimization and machine learning, including reinforcement learning. In fall 2026, he teaches Introduction to Machine Learning and Markov Decision Processes.

Career

  1. Since 2025University of TorontoAssociate Professor
  2. 2016–2025Delft University of TechnologyAssistant Professor
  3. 2015Massachusetts Institute of TechnologyVisiting Research Scholar
  4. 2014–2016EPFLPostdoc
  5. 2014–2016ETH ZurichPostdoc

Education

  1. 2014ETH ZurichPhD
  2. 2008Sharif University of TechnologyMSc
  3. 2005Sharif University of TechnologyBSc

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. Data-Driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations2015 · 1,857 citations
  2. Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning2019 · 363 citations
  3. Distributionally Robust Logistic Regression2015 · 162 citations
  4. Symbolic Control of Stochastic Systems via Approximately Bisimilar Finite Abstractions2014 · IEEE Transactions on Automatic Control · 156 citationsWith Alessandro Abate
  5. Cyber attack in a two-area power system: Impact identification using reachability2010 · American Control Conference · 144 citations

From OpenAlex, as of 21 October 2026.

  1. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of Toronto. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  2. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes University of Toronto. 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. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorateIncludes University of Toronto. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorate. Across 2,116 people with both an undergraduate degree and a doctorate recorded, we trace which undergraduate schools feed which doctoral programs, how often students stay at the same school, and how paths differ by birth-country region.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of Toronto. 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.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. Biography - Peyman Mohajerin Esfahani mohajerinesfahani.github.io. Checked 20 October 2026.
  2. Dr. P. (Peyman) Mohajerin Esfahani tudelft.nl. Checked 20 October 2026.
  3. Data-driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations arxiv.org. Checked 20 October 2026.
  4. Professorship at TU Delft for Dr. Mohajerin Esfahani actu.epfl.ch. Checked 20 October 2026.
  5. Peyman Mohajerin Esfahani - Department of Mechanical & Industrial Engineering mie.utoronto.ca. Checked 20 October 2026.
  6. Newsletter September 2020 - DISC disc.tudelft.nl. Checked 20 October 2026.
  7. Peyman Mohajerin Esfahani has been granted the European Control Award tudelft.nl. Checked 20 October 2026.
  8. Making decisions under uncertainty: Meet MIE Professor Peyman Mohajerin Esfahani - U of T Engineering News news.engineering.utoronto.ca. Checked 20 October 2026.