Victor Verdugo

I am an Assistant Professor at the Institute of Engineering Sciences, Universidad de O'Higgins in Chile. Until recently, I was an LSE Fellow in the Department of Mathematics at the London School of Economics and Political Science. Before joining LSE and during my PhD, I was part of the Theory of Algorithms and Optimization group at École normale supérieure in Paris and the Algorithms and Optimization group at Universidad de Chile, in Santiago.

These days I'm mainly working on combinatorial optimization and market design problems, including algorithmic aspects of electoral representation and voting systems, fairness and diversity in resource allocation, and dynamic interaction in networks and markets. I also work on the design of approximation algorithms for combinatorial optimization problems and online optimization algorithms for optimal stopping, revenue management, and resource allocation. Application areas of my research include Computational Social Choice, Revenue Management, Efficient and Fair Resource Allocation, Market Design.

I'm currently leading the following projects:

Basic Research - Fondecyt Research Initiation Grant, Algorithmic Aspects of Representation: Allocation and Fairness, 2020-2022.

Applied Research - ESR Mineduc, Strategic Development of Tourism in the O'Higgins Region based on Mathematical and Data Modeling, 2020-2021.

Recent Articles

A 2-Approximation for the Bounded Treewidth Sparsest Cut Problem in FPT Time (V. Cohen-Addad, T. Mömke and V. Verdugo), 2021.

Apportionment with Parity Constraints (C. Mathieu and V. Verdugo), 2021.

Convergence Rates of Blockchain Mining Games: A Markovian Approach (A. Jofré, A. Pardo, D. Salas, V. Verdugo and J. Verschae), 2021.

Proportional Apportionment: A Case Study From the Chilean Constitutional Convention (J. Cembrano, J. Correa, G. Diaz and V. Verdugo), EAAMO 2021.

Preserving Diversity when Partitioning: A Geometric Approach (S. Pérez-Salazar, A. Torrico and V. Verdugo), EAAMO 2021.

Optimal Revenue Guarantees for Pricing in Large Markets (J. Correa, D. Pizarro and V. Verdugo), SAGT 2021.

Multidimensional Apportionment through Discrepancy Theory (J. Cembrano, J. Correa and V. Verdugo), EC 2021.

Strong Algorithms for the Ordinal Matroid Secretary Problem (J. Soto, A. Turkieltaub and V. Verdugo), Mathematics of Operations Research, 2021.

Research

These days I'm mainly working on combinatorial optimization and market design problems, including the use of advanced algorithmic and optimization techniques for designing electoral and civic representation systems, improving fairness and diversity in resource allocation, and understanding the consequences of the dynamic interaction of agents in networks and markets. I also work on the design of approximation algorithms and online algorithms for optimal stopping, revenue management and matching markets.

Education

• Doctor of Philosophy - PhD Ecole normale supérieure (2014 — 2018)
• Doctor of Philosophy - PhD Universidad de Chile (2014 — 2018)
• Master's degree Universidad de Chile (2013 — 2013)
• Engineer's degree Universidad de Chile (2007 — 2013)

Companies

• Assistant Professor Universidad de O'Higgins (2018)
• LSE Fellow The London School of Economics and Political Science (LSE) (2019 — 2020)

Projects

My basic research is funded by a Fondecyt Research Grant: Algorithmic Aspects of Representation: Allocation and Fairness, 2020-2022.

I'm also involved, by leading or participating, in the following projects of applied research:

Strategic Development of Tourism in the O'Higgins Region based on Mathematical and Data Modeling, 2020-2021. I'm currently leading this project where the goal is create, in collaboration with actors directly involved and relevant to the O'Higgins region i) a replicable model based on territorial data intelligence, and ii) a set of tools based on visualization and data analytics to aid in making investment decisions in regional tourism. The project is funded by ESR Mineduc.

Transfer and Adoption of Technologies for Risk Management in the Production of Cherries: Towards an Agriculture of Precision in the O'Higgins Region, 2021-2023. Together with Rodrigo Verschae (UOH) and Cristobal Quiñinao (UOH), we got an O'Higgins Regional Innovation Funding (FIC-O'Higgins) for a project on risk management for cherries fields in the O'Higgins region based on machine learning and computer vision techniques.