Margarita Paz Castro

margarita.castro [at] uc.cl

old emails:
mpcastr3 [at] uc.cl
margarita.castro [at] ing.puc.cl

I'm an Assistant Professor in the Department of Industrial Engineering at Pontificia Universidad Católica de Chile. Send me an email if you have any questions about my work or if you are interested in working together.

I was previously a Post Doctoral Fellow at the Mechanical and Industrial Engineering department at the University of Toronto working with Prof. Merve Bodur. I obtained my Ph.D. from the Mechanical and Industrial Engineering department at the University of Toronto under the supervision of Prof. Chris Beck and Prof. Andre Cire.

My research focuses on discrete optimization problems and using Decision Diagrams to solve them. I am also interested in Integer Programming, Stochastic Programming, Constraint Programming, AI applications (e.g., AI planning and neural networks), and OR applications (e.g., scheduling and vehicle routing).

[CV] [Publications]

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[GitHub]

News 2025:

New role as Associate Editor (Data & Software Specialists) for INFORMS Journal on Computing.
New manuscript with Nicolás Casassus (master student) and Gustavo Angulo.
- A Decision Diagram Approach for the Parallel Machine Scheduling Problem with Chance Constraints [arXiv] [OO]

News 2024:

On maternity leave from February to September.
Paper accepted in "Applied Energy":
- Optimal cleaning scheduling for large photovoltaic portfolios
New manuscript with Merve Bodur and Amer Shalaby :
- Incorporating Service Reliability in Multi-depot Vehicle Scheduling. [arXiv]

News 2023:

I won the research grant "FONDECYT de Iniciación 2022" for three years to keep working on Decision Diagrams for discrete optimization.
Paper accepted in "Applied Energy" :
- Optimization-based expansion planning for power and hydrogen systems with feedback from a unit commitment model
I presented my project with Merve Bodur and Yongjia Song at MIP Workshop 2023 on multi-stage stochastic programming [pre-print]
I presented my work with Merve Bodur and Amer Shalabi at IFORS 2023 and ICSP 2023 on a chance constraint model for the vehicle schedule problem.
Paper accepted in "Artificial Intelligence":
- Learning Reward Machines: A Study in Partially Observable Reinforcement Learning

News 2022:

New manuscript with Merve Bodur and Yongjia Song :
- Markov Chain-based Policies for Multi-stage Stochastic Integer Linear Programming with an Application to Disaster Relief Logistics. [OO][arXiv]
Paper accepted INFORMS Journal on Computing:
- Decision Diagrams for Discrete Optimization: A Survey of Recent Advances [arXiv]

News 2021:

I received the ACP Doctoral Research Award:
- Thesis: Optimization Methods Based on Decision Diagrams for Constraint Programming, AI Planning, and Mathematical Programming [post-print]
- CP 2021 talk
INFORMS 2021 talks:
- Multi-stage Stochastic Programming Approaches To Contingency Modality Activation With An Application In Disaster Relief Logistics (speaker: me)
- Incorporating Service Reliability In Multi-depot Vehicle Scheduling: A Chance-constrained Approach (speaker: Merve Bodur)
Published paper at Mathematical Programming:
- A Combinatorial Cut-and-Lift Procedure with an Application to 0-1 Second-Order Conic Programming
I joined the DIIS department at PUC as an Assistant Professor.
Talk at TSL Workshop 2021: Incorporating Service Reliability in Multi-depot Vehicle Scheduling: A Chance-Constrained Approach.
Talk at CORS 2021: Training binarized neural networks using MIP and CP (paper).
I joined the COOL lab at UofT as a Post Doctoral Fellow.

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