Loading...
IE-RSME Workshop Series on Applied Mathematics — Sustainable Transportation & Energy Systems: An Optimization and AI Perspective
by
Thu, Apr 23, 2026
9:30 AM – 3:30 PM (GMT+2)
Private Location (sign in to display)
1
Registered
Details
Sustainable Transportation & Energy Systems: An Optimization and AI Perspective
The IE-RSME Workshop on Applied Mathematics and Knowledge Transfer aims to foster collaboration between academia and institutions tackling real-world challenges. This edition will focus on the recent advances in mathematical optimization with applications related to sustainable and low-carbon transportation and energy infrastructure.
The design and operation of modern urban infrastructure require rigorous mathematical modeling that captures the nonlinearities and stochastic nature of the underlying systems. Our speakers will present recent advances in optimization, network design, stochastic modeling, and data analytics, with applications in infrastructure management and operations.
The workshop will feature four keynote talks (30 minutes each), a session for contributed flash talks and student poster presentations, and an open talk from a speaker selected by RSME. We encourage broad participation to explore different perspectives on sustainable systems.
Agenda
09:30 - 09:40 | Welcome and Opening Remarks
09:40 - 10:25 | Talk 1
10:25 - 11:10 | Talk 2
11:10 - 11:40 | Flash Presentations
11:40 - 12:10 | Coffee Break & Networking
12:10 - 12:55 | Talk 3
12:55 - 13:15 | Poster 3-minute-presentations
13:15 - 14:00 | Talk 4
14:00 - 15:00 | Lunch & Poster session
Call for Contributions
We welcome contributions from students, researchers, and professionals interested in the mathematical and optimization challenges posed for sustainable transportation and energy systems. Participants are invited to submit abstracts for short flash talks (3–10 minutes) and/or poster presentations related to the workshop themes, including but not limited to:
- Mathematical optimization for sustainable transportation and mobility systems
- Energy systems modeling and low-carbon infrastructure planning
- Stochastic and network-based approaches to urban mobility and logistics
- Data-driven methods for smart grids and energy demand management
- Operations research for integrated transportation–energy systems and decarbonization
To be considered, please submit a brief abstract (maximum 200 words) to bissan.ghaddar@ie.edu with subject "IE-RSME workshop abstract" by 12/04/2026.
We particularly encourage early-career researchers and graduate students to contribute.
Dress Casual (jeans ok)
Food Provided
Speakers
Salvador Pineda
Universidad de Málaga
Salvador Pineda obtained his degree in Industrial Engineering from the University of Málaga in 2006, and his PhD in Electrical Engineering from the University of Castilla-La Mancha in 2011. From 2011 to 2016, he worked as a professor at the Technical University of Denmark and the University of Copenhagen. Since 2016, he has been a professor in the Department of Electrical Engineering at the University of Málaga. His research interests focus on the operation and planning of energy systems, decision-making under uncertainty, bilevel programming, machine learning, and statistics.
Julio González Díaz
University of Santiago de Compostela
Julio González Díaz is a Professor of Operations Research and Mathematical Optimization at the University of Santiago de Compostela, affi liated with the Centre for Mathematical Research and Technology (CITMAga). His work spans mathematical optimization, decision models, game theory, and algorithmic development, with a strong focus on leveraging optimization techniques to solve complex decision problems in networked and competitive environments.
Bissan Ghaddar
IE University and Ivey Business School
Bissan Ghaddar works at the intersection of smart cities, machine learning, and mathematical optimization, developing data-driven models for sustainable and resilient infrastructure systems. She holds a Ph.D. in Operations Research–Management Science from the University of Waterloo and has experience in both academia and industry, including research at IBM on energy, telecom, water, and transportation network optimization.
Her research focuses on integrating AI and optimization to address large-scale challenges in energy and mobility systems, with publications in leading journals such as Mathematical Programming, INFORMS Journal on Computing, and SIAM Journal on Optimization.
Manuel Navarro García
Optimization Consultant, Decide4AI
Manuel Navarro-García works at the intersection of mathematical optimization and data science, developing advanced decision-support models that integrate predictive analytics with mathematical programming. He holds a Ph.D. in Mathematical Engineering from Universidad Carlos III de Madrid and has a background in Mathematics, Physics, and Statistics for Data Science. Currently, he serves as an Optimization Consultant at Decide4AI, where he designs optimization models that provide quantitative and qualitative insights to improve strategic and operational decision-making in industry.
Sponsors
