Juan Estrada

I am a fifth-year PhD candidate in Industrial and Operations Engineering at the University of Michigan, advised by Dr. Siqian Shen. I study how optimization can support resilient and adaptive infrastructure systems, and I am currently on the job market. Before joining Michigan, I earned a Bachelor's degree in Engineering Management from the University of Monterrey in Mexico.

Research vision

My research sits at the intersection of multi-stage stochastic optimization, distributionally robust optimization, and decomposition algorithms. I formulate optimization models for the sequential decisions that plan and operate infrastructure where the uncertainty a system faces can itself depend on the decisions made along the way. I build decomposition algorithms that solve these models exactly at the scale of a real network, and turn the solutions into policies an operator can run. The goal throughout is infrastructure that is resilient and adaptive by design.

• Methods: multi-stage stochastic optimization, distributionally robust optimization, and decomposition algorithms.
• Modeling: sequential decisions with uncertainty that can depend on the actions taken over time.
• Applications: resilient and adaptive infrastructure systems, including power networks, inspection, and supply chains.

Explore research projects

My professional experience includes:

• Student Fellow, Grid Integration Group, Lawrence Berkeley National Laboratory (LBNL), Remote (June 2026 - Present)
  Developing and coding adaptive optimization models for resilient power-systems investment planning and operations.
• Applied Science Intern, Amazon, Greater Seattle Area (May 2025 - Aug 2025)
  Internship. Worked with Amazon's Surface Research Science team on routing problems.
• Solutions Developer, Softtek, Monterrey, Nuevo León, Mexico (Feb 2022 - Jun 2022)
  Full-time. Developed data-analysis and predictive-analytics software using supervised and unsupervised statistical and machine-learning methods.
• Undergraduate Researcher, Universidad de Monterrey (Jun 2021 - Dec 2021)
  Full-time. Developed predictive machine-learning models to understand modal choice among university affiliates.
• Project Researcher Specialist, Tecnológico de Monterrey, Monterrey, Nuevo León, Mexico (Sep 2020 - Dec 2020)
  Part-time. Developed traffic microsimulation models to assess smart mobility strategies in university districts.

Honors and Awards

• 2026, Student Fellowship, Grid Integration Group, Lawrence Berkeley National Laboratory (LBNL)
• 2026, Rackham Predoctoral Fellowship, University of Michigan, Ann Arbor
• 2026, SIAM Conference on Optimization Student Travel Award
• 2025, Minority Issues Forum (MIF) Poster Competition First Place in the 2025 INFORMS Annual Meeting
• 2025, Institute of Energy Solution (IES) Graduate Fellowship, University of Michigan, Ann Arbor
• 2023, Michigan Institute for Computational Discovery and Engineering (MICDE) Student Fellowship, University of Michigan, Ann Arbor
• 2023, Best Conference Paper Award Finalist in the IEEE 19th International Conference on Automation Science and Engineering (CASE 2023)
• 2023-2025, Rackham Travel Award, University of Michigan, Ann Arbor
• 2022, Best Track Modeling & Simulation Paper in the 2022 IISE Annual Conference
• 2022, Engineering Graduate Fellowship, University of Michigan, Ann Arbor
• 2017-2021, Academic Excellence Scholarship, University of Monterrey