top of page
About Me

Maryam Daryalal

Canada Research Chair in Sequential Decision-Making Under Uncertainty

IVADO Researcher

Assistant Professor of Operations Research

Department of Decision Sciences

HEC Montréal, University of Montréal

Email icon

maryam [dot] daryalal [at] hec [dot] ca

Office icon

Department of Decision Sciences
HEC Montréal | University of Montréal
3000 Côte-Sainte-Catherine Road

Montréal, QC H3T 2A7 

Maryam Daryalal copy.jpg

Education

  • Ph.D., Industrial Engineering, University of Toronto (2022)

  • M.S., Computer Science, Concordia University (2016)

  • M.S., Industrial Engineering, Amirkabir University of Technology (2013)

  • B.S., Industrial Engineering & Systems Analysis, Amirkabir University of Technology (2011)

Research Interests

Methodology

Application Areas

  • Stochastic optimization

  • Robust optimization

  • Mixed-integer optimization

  • Large-scale optimization

  • Learning for optimization

  • Decision-focused learning

  • Generative modelling

  • Machine learning

  • Sequential decision-making under uncertainty

  • Telecommunications

  • Healthcare & pharmaceutical decision modelling

  • Supply chain planning & mobility systems

  • Energy systems

  • Scheduling

  • Semantic web

​

a4a58852928c1eb6f86d12ca33020309.gif
72-727038_transparent-background-feather
a4a58852928c1eb6f86d12ca33020309.gif

Preprints

  • P. Peiroasfia, M. Daryalal, V. Roshanaei. Beyond Isolated Operating Rooms: Risk-Aware Surgical Episode Scheduling in Single-Entry Networks. [pdf]

  • A. Khademi, M. Daryalal. Robust Optimization Under Sparse Uncertainty. [pdf]

  • M. Daryalal, A. Ahmadi-Javid. Risk-Aware Logic-Based Benders Decomposition for a Location-Allocation-Pricing Problem with Stochastic Price-Sensitive Demands. [pdf]

  • M. Daryalal, A. N. Arslan, M. Bodur. Two-Stage and Lagrangian Dual Decision Rules for Multistage Adaptive Robust Optimization. [pdf]

Publications

  • O. Demers, M. Daryalal, M. Denault. Learning Risk-averse Policies with Two-stage Deep Decision Rules. Accepted at NeurIPS MLxOR Workshop, 2026. [pdf]

  • M. Hemmati, M. Daryalal. Generative Decision-focused Learning for Multistage Stochastic Convex Programming. Accepted at NeurIPS MLxOR Workshop, 2026. [pdf]

  • M. Daryalal, M. Bodur, J. Luedtke. Lagrangian Dual Decision Rules for Multistage Stochastic Mixed-integer Programming. Operations Research, volume 72, issue 2, pp. 717–737, 2024. [pdf]

  • M. Daryalal, H. Pouya, M.-A. DeSantis. Network Migration Problem: A Hybrid Logic-based Benders Decomposition Approach. INFORMS Journal on Computing, volume 35, issue 3, pp. 593–613, 2023. [pdf]

  • M. Daryalal, M. Bodur. Stochastic RWA and Lightpath Rerouting in WDM Networks. INFORMS Journal on Computing, volume 34, issue 5, pp. 2700–2719, 2022. [pdf]

  • B. Jaumard, M. Daryalal. Efficient Spectrum Utilization in Large-scale RWA Problems. IEEE/ACM Transactions on Networking, volume 25, issue 2, pp. 1263–1278, 2017. [pdf]

  • B. Jaumard, M. Daryalal. Optimizing Spectrum Utilization in Dynamic RWA. IEEE International Conference on Optical Network Design and Modeling (ONDM), pp. 1–6, 2016. [pdf]

  • B. Jaumard, M. Daryalal. Scalable Elastic Optical Path Networking Models. IEEE International Conference on Transparent Optical Networks (ICTON), pp. 1–4, 2016. [pdf]

  • J. Vlasenko, M. Daryalal, V. Haarslev, B. Jaumard. A Saturation-based Algebraic Reasoner for ELQ. Practical Aspects of Automated Reasoning, 8th International Joint Conference on Automated Reasoning (IJCAR), pp. 110–124, 2016. [pdf]

  • B. Jaumard, M. Daryalal. Solving Very Large RWA Data Instances. IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), pp. 1–6, 2016. [pdf]

  • M. Daryalal. Sequential Decision-making Under Uncertainty: Novel Methodologies and Applications. PhD Dissertation, 2022. [pdf]

Awards & Honors

  • Rising Star Award – runner-up, Canadian Operational Research Society (2026)

  • Chairholder, Canada Research Chair in Sequential Decision-Making Under Uncertainty (2025)

  • Best Paper Award, INFORMS Telecommunications & Network Analytics, INFORMS Annual Meeting (2023)

  • Judith Liebman Award, INFORMS (2021)

  • MIE Teaching Assistant Award, University of Toronto (2021)

  • Best Student Paper Finalist, Canadian Operational Research Society (2021)

  • Seth Bonder Foundation Student Grant, INFORMS (2020)

  • Best Operations Research Poster, MIE Graduate Research Symposium (2018)

  • Connaught International Scholarship Award, University of Toronto (2017)

  • Concordia Merit Award, Concordia University (2014)

Funding

Principal Investigator

  • Mitacs Accelerate Umbrella (July 2026–February 2027)

    • Partner: Groupe Sorintellis Inc.

    • Title: Dynamic risk-adjusted valuation of early-stage pharmaceutical assets using AI-driven PTRS decomposition and sequential decision modelling

    • Amount: $30,000

  • Mitacs Business Strategy (May–September 2026)

    • Partner: NURA Medical Inc.

    • Title: Scaling medication safety and enriching data interoperability across McGill University Health Centre

    • Amount: $15,000

  • Digital Research Alliance of Canada (April 2026–April 2027)

    • Title: Machine Learning and Optimization Methods for Supply Chains and Mobility Systems

    • In-kind HPC allocation valued at $74,642

    • Co-PIs: Yossiri Adulyasak, Jean-François Cordeau, Erick Delage, and Emma Frejinger

  • Canada Research Chairs Program (June 2025–June 2030)

    • Funding source: NSERC

    • Title: Sequential Decision-Making Under Uncertainty

    • Amount: $600,000

  • John R. Evans Leaders Fund (June 2025–June 2030)

    • Funding source: Canada Foundation for Innovation and Ministère de l’Économie, de l’Innovation et de l’Énergie

    • Title: Sequential Decision-Making Under Uncertainty

    • Amount: $308,150 from agencies and $227,828 from external partners

  • IVADO Grant R3AI Regroupment 9 (April 2025–September 2026)

    • Funding source: IVADO

    • Title: Learning-based sequential decision-making under uncertainty

    • Amount: $40,000

  • Mitacs Accelerate Program (June–December 2024)

    • Funding source: Mitacs

    • Title: Sequential relational synthetic data generation

    • Amount: $15,000

  • Discovery Grant (April 2024–March 2029)

    • Funding source: NSERC

    • Title: Multistage stochastic programming and robust optimization: Novel methodologies and applications

    • Amount: $170,000 plus a $12,500 Discovery Launch Supplement

​​

Co-PI

  • IVADO Exploratory Projects Program (November 2024–October 2025)

    • Funding source: IVADO

    • Title: Large-scale power grids: Transition to net zero

    • Amount: $100,000

    • Co-PIs: Michel Denault and Pierre-Olivier Pineau

Teaching

  • MATH20604 – Modèles d’optimisation, BAA (Fall 2026)

  • MATH60623A – Stochastic Optimization and Reinforcement Learning, MSc (Fall 2025/2026)

  • MATH60623A – Sequential Decision Making under Uncertainty, MSc (Fall 2023/2024)

  • MATH60623 – Optimisation stochastique et apprentissage par renforcement, MSc (Fall 2025)

  • MATH60623 – Prise de décisions séquentielles sous incertitude, MSc (Winter 2024)

  • MATH20604A – Linear Optimization Models, BAA (Fall 2022/2023/2024/2025/2026)

  • MATH60612 – Modèles d’application de l’analytique d’affaires, MSc (Winter 2025)

  • MATH60612A – Application Models in Business Analytics, MSc (Winter 2025)

  • MATH10620A – Statistics, BAA (Winter 2023)

Students

Current

Postdoctoral Fellows

  • Abbas Khademi - IVADO Postdoctoral Fellow

  • Mahya Hemmati - Mitacs/IVADO Postdoctoral Researcher

PhD

  • Mahsa Hajamini (co-advised with Louis-Martin Rousseau and Hossein Hashemi Doulabi)

  • Pedram Peiroasfia (co-advised with Erick Delage)

MSc​

  • Adrien Darbes (co-advised with Michel Denault)

  • Olivier Demers (co-advised with Michel Denault)

​​

Past

  • Georges Lemuel Balogog Mandack, MSc (2025–2026)

  • Nada El Mdari, MSc (2025–2026)

  • Kamel Yousri Amrouche, MSc (2024–2025)

  • Pedram Peiroasfia, MSc; fast-tracked to PhD (2024–2025)

  • Adrien Darbes, Research Assistant (2024–2025)

  • Philippe Béliveau, Mitacs Accelerate Intern (Fall 2024)

  • Zixuan Yang, Mitacs Globalink Intern (Summer 2024)

  • Yubo Cai, Mitacs Globalink Intern (Summer 2023)

Data and Online Supplements

Publications
a4a58852928c1eb6f86d12ca33020309.gif
vectorstock_23809517.png
a4a58852928c1eb6f86d12ca33020309.gif

Conferences & Talks

  • Risk-Aware Surgical Episode Scheduling in Single-Entry Networks, ORAHS Conference, Belfast (July 2026).

  • Robust Optimization Under Sparse Uncertainty, CORS Annual Conference, Kingston (June 2026).

  • Robust Optimization Under Sparse Uncertainty, Optimization Days, Montreal (May 2026).

  • Sequential Decision-Making Under Uncertainty: Models, Methods, and Insights, Erasmus+ International, University of Murcia, Murcia (2026, invited speaker).

  • Risk-Aware Logic-Based Benders Decomposition for a Location-Allocation-Pricing Problem with Stochastic Price-Sensitive Demands, CORS Annual Conference, Edmonton (June 2025, invited).

  • A Risk-Aware Location-Allocation-Pricing Problem with Stochastic Price-Sensitive Demands, International Symposium on Mathematical Programming, Montreal (2024).

  • Large-Scale Optimization Methods for Logical Reasoning: A Novel Perspective, Mixed-Integer Programming Workshop, Lexington (2024, invited speaker).

  • Large-Scale Optimization Methods for Logical Reasoning: A Novel Perspective, GERAD Research Seminars, Montreal (May 2024).

  • A Risk-Aware Location-Allocation-Pricing Problem with Stochastic Price-Sensitive Demands, Optimization Days, Montreal (May 2024).

  • Two-Stage Decision Rules for Multistage Adaptive Robust Optimization, INFORMS Annual Meeting, Phoenix (2023, invited).

  • Network Migration Problem: A Hybrid Logic-Based Benders Decomposition Approach, INFORMS Annual Meeting Award Presentations, Phoenix (2023).

  • A Hybrid Logic-Based Benders Decomposition Approach for the Network Migration Problem, Discrete Optimization Talks, online (2023, invited).

  • Novel Decision Rules in Sequential Decision-Making Under Uncertainty, International Conference on Stochastic Programming, Davis (2023, invited).

  • Logic-Based Benders Decomposition for the Network Migration Problem, International Network Optimization Conference (2022).

  • Novel Bounding Techniques for Multistage Adaptive Robust Optimization, CORS/INFORMS International Conference, Vancouver (2022).

  • On Primal and Dual Bounding Techniques for Multistage Adaptive Robust Optimization, Optimization Days, Montreal (2022, invited).

  • Logic-Based Benders Decomposition and Hybrid Column Generation for the Network Migration Problem, Optimization Days, Montreal (2022).

  • Stochastic Routing and Wavelength Assignment Problem in WDM Networks, INFORMS Annual Meeting (2021).

  • Integrated Staffing and Scheduling for Service Systems via Multistage Stochastic Mixed-Integer Programming, CORS Annual Conference (2021).

  • Stochastic Routing and Wavelength Assignment Problem in WDM Networks, CIRRELT (2021, invited).

  • Lagrangian Dual Decision Rules for Integrated Staffing and Scheduling in Service Systems, INFORMS Annual Meeting (2020, invited).

  • Stochastic Routing and Wavelength Assignment Problem in Network Defragmentation, INFORMS Telecommunications and Network Analytics Conference (2020).

  • Integrated Staffing and Scheduling for Service Systems via Multistage Stochastic Integer Programming, International Conference on Stochastic Programming, Trondheim (2019).

  • Lagrangian Dual Decision Rules for Multistage Stochastic Integer Programming, Optimization Days, Montreal (2019).

  • Integrated Pricing and Routing Decisions, INFORMS Revenue Management & Pricing, Toronto (2018, invited).

  • Facility Location Problem with General Objective Functions, MIE Graduate Research Symposium, Toronto (2018, poster).

Professional Service

  • Councils and committees

    • Council member, INFORMS Telecommunications & Network Analytics Section (2025–2028)

    • Committee member, INFORMS Chapters and Fora (2022–2024)

  • Award evaluations

    • Chair, Best Paper Award, INFORMS Telecommunications & Network Analytics Section (2025)

    • Committee member, Best Undergraduate Paper Award, Canadian Operational Research Society (2025)

  • Conference and research-community leadership

    • Chair, FRQNT–Stratégia “Modelling Emerging Challenges,” GERAD (2026)

    • Chair, GERAD 3-Minute Thesis (2025)

    • INFORMS Computing Society Conference, Sponsorship Chair (2025)

    • CORS Annual Conference, Cluster Chair (2024, 2027)

    • Conference session chair/organizer: ISMP, Montreal (2024); Optimization Days, Montreal (2022, 2024); CORS/INFORMS International Conference (2022); INFORMS Annual Meeting (2020, 2021); INFORMS Telecommunications & Network Analytics Conference (2020)

  • Student-chapter leadership

    • President, INFORMS/CORS Student Chapter at the University of Toronto (2019–2022)

      • INFORMS Student Chapter Award — Magna cum laude (2021)

      • INFORMS Student Chapter Award — Honorable mention (2020)

  • Ad hoc reviewer/referee

    • Transportation Science; Mathematical Programming; Operations Research; INFORMS Journal on Computing; Health Care Management Science; European Journal of Operational Research; Networks; IEEE/ACM Transactions on Networking; Operations Research Letters; Omega; Annals of Operations Research; Information Systems and Operational Research; IEEE Communications Letters; CPAIOR.

In the Community

© 2022–2026 by Maryam Daryalal

  • Google Scholar
  • ResearchGate
  • Twitter
bottom of page