Back to

Dr Tomas Lagos

Lecturer

 

Business School
Sch of Info Systems & Tech Mgt

Dr Tomas Lagos is a Lecturer in the School of Information Systems and Technology Management (SISTM) at UNSW Sydney.

His research mission is to address pressing environmental and economic challenges, leveraging advanced computational methods to contribute to a more sustainable and resilient future. Tomas’s work bridges the gap between complex algorithmic development and real-world application, aiming to solve critical issues in resource management, climate adaptation, and modern supply chains.

 

The First INFORMS TSL Data-Driven Research Challenge (2024-2025 TSL-Meituan)

Winning material: Data-Driven Optimization for Meal Delivery: A Reinforcement Learning Approach for Order-Courier Assignment and Routing at Meituan

Call: https://connect.informs.org/tsl/tslresources/datachallenge
Outcome: https://www.informs.org/Recognizing-Excellence/Community-Prizes/Transportation-Science-and-Logistics-Section/TSL-Data-Driven-Research-Challenge

Commitment to Impact

A core pillar of Tomas’s academic work is delivering measurable social, environmental, and economic impact. His research is designed to move beyond the theoretical and drive strategic policy changes.

Notable impacts include:

  • Electrical Network Resiliency: Conducted foundational research on enhancing the resilience of the electrical network in Chile. The strategic recommendations arising from these publications have been adopted and are currently being implemented.

  • Wildfire Mitigation Policies: Recently finalized advanced algorithms that provide data-driven recommendations on preventive landscape treatments to mitigate wildfire spread. These models were rigorously calibrated using real-world data from Texas and Australia. The next phase of this project involves applying these algorithms to real-life forestland data to help nations highly vulnerable to climate change craft strategic, effective landscape treatment policies.

Research Interests

Methodologies:

  • Artificial Intelligence & Machine Learning

  • Reinforcement Learning

  • Optimization (Bilevel, Robust, Combinatorial)

  • Online Scheduling

  • Network Theory

Applications:

  • Resources Policy Management

  • Sustainability and Climate Change Adaptation

  • Wildfires & Electrical Networks Resiliency

  • Supply Chain Logistics & Transportation

  • E-Commerce