I am a Ph.D. candidate in Operations Management at UCLA Anderson School of Management. I received my B.Sc. in Industrial Engineering from Sharif University of Technology in 2021. I am on the 2026–2027 academic job market.

My research interests are in sustainable operations. I study consequential and complex real-world problems where better decision-making can create value in practice while reducing the risks and burdens communities face. My primary research domain is wildfire management, with energy management as a secondary application stream.

In wildfire management, my work spans utility grid inspection and maintenance as well as broader questions involving prevention, suppression, and mitigation. I place substantial value on domain expertise and actively engage with utility professionals, firefighters, and other practitioners to ensure that the problems I study and the models I develop are grounded in real decision settings.

Methodologically, I use optimization, stochastic modeling, and data-driven methods, with particular interests in large-scale optimization and decision-focused sequential learning. I also increasingly use recent advances in AI, including agentic systems, to accelerate data-intensive and computational aspects of my research, allowing me to devote more attention to problem definition, formulation, and deriving meaningful managerial insights.

Curriculum Vitae

• Aug 18, 2026 Scheduled to present at the INFORMS PhD Job Market Showcase at the 2026 INFORMS Annual Meeting in San Francisco.
• July 30, 2026 Our paper Preventing Catastrophic Wildfires: Annual Grid Inspection and Maintenance Plan was selected as a finalist for the 2026 INFORMS Service Science Best Student Paper Award.
• July 23, 2026 Our paper Preventing Catastrophic Wildfires: Annual Grid Inspection and Maintenance Plan was accepted for presentation at the Humanitarian Operations (HOPE) Research Workshop at the University of Notre Dame.
• May 9, 2026 Our paper Preventing Catastrophic Wildfires: Annual Grid Inspection and Maintenance Plan won the 2026 POMS College of Supply Chain Management Best Student Paper Award.
• Mar 27, 2026 Selected to participate in the Rising Stars Workshop at the University of Michigan (29 selected out of 132 applicants).

• Preventing Catastrophic Wildfires: Annual Grid Inspection and Maintenance Plan
  Major Revision at Operations Research [SSRN]

  with A. Fattahi, S. Dasu, R. Ahmadi

  We design an optimal inspection and maintenance plan for large power grids under uncertainty, capturing correlated wildfire risk and operational capacity constraints. Using data from one of California's largest utility companies, we show how principled planning can substantially reduce the damage from catastrophic wildfires.

  • Media coverage: UCLA Anderson Review, POMS SCM Research Bites
  • Winner, POMS College of SCM Best Student Paper Award 2026
  • Finalist, INFORMS Service Science Best Student Paper Award 2026
  • Best Flash Talk Award, Early-Career Sustainable Operations Workshop 2026
  • Accepted for Humanitarian Operations (HOPE) Workshop 2026
• Fair and Flexible Scheduling for Dynamic Energy Load Control under Stochastic Demand
  Under review at Management Science [SSRN]

  with A. Fattahi, S. Dasu, R. Ahmadi

  We formulate a stochastic dynamic program for direct load control that jointly models fairness over time and operational flexibility in admissible call lengths. We develop a scalable aggregation–disaggregation method with provable guarantees and quantify the efficiency impacts of fairness and flexibility using high-resolution CAISO demand data.

• Decision-Focused Assessment Allocation for Dynamic Interventions
  Planned for submission to Operations Research

  with S. Dasu, R. Ahmadi

  We study dynamic systems that jointly allocate interventions and scarce information-acquisition opportunities. We develop Decision-Focused Assessment Allocation (DFAA), which targets observations that are both informative and consequential for downstream decisions, and establish performance guarantees.

• Balancing Prevention, Suppression, and Mitigation in Wildfire Risk Management
  Work in progress

  with R. Ahmadi, S. Dasu

  This project examines wildfire risk reduction as a portfolio problem spanning prevention, suppression, and mitigation — three intervention classes that act at different stages of the wildfire process. Our goal is to understand how these three levers should be combined under realistic budget and risk conditions.

The best way to reach me is by email.