Mauro Salazar

Mauro Salazar is an Assistant Professor in the Control Systems Technology section of the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e), with co-affiliations at the Eindhoven AI Systems Institute (EAISI) in both Health and Mobility domains. He leads his own research group focused on optimization models and methods for systems and control.

His educational background includes:

• B.Sc. and M.Sc. in Mechanical Engineering from ETH Zürich (2012, 2015)
• Master thesis conducted at EPFL's Automatic Control Lab
• Ph.D. in Mechanical Engineering from ETH Zürich (2019) in collaboration with Ferrari Formula 1
• Postdoctoral Scholar at Stanford University's Autonomous Systems Lab (2019-2020)

Salazar's research centers on optimization models for multi-scale cyber-socio-technical systems with applications spanning mobility systems, pandemic response, and material design. His work bridges theoretical optimization with practical implementation, particularly in sustainable mobility solutions where he develops methods for optimal design and operation of transportation systems from single vehicles to entire networks. He investigates mesoscopic user behavior modeling and designs incentive schemes to align individual and system-level objectives in transportation networks.

His recent publications (2025) demonstrate a strong focus on sustainable mobility systems, with recurring themes in electric vehicle fleet management, battery degradation modeling, ride-pooling algorithms, and energy management for transportation electrification. His work spans multiple disciplines including automotive engineering, control systems, energy management, and public health, characterized by rigorous mathematical optimization approaches applied to real-world challenges.

His scientific recognitions include:

• Two ETH Medals (for Master's and PhD theses)
• Best Student Paper awards at ITS 2018 and ECC 2022
• Best Teacher Award (2021)
• Nomination for TU/e Young Researcher Award (2022)

Salazar actively advises research projects and secured funding through the Dutch Research Council's NEON project (Crossover research program, Grant 17628). His teaching portfolio includes Optimal Control and Reinforcement Learning, Engineering Optimization, and Advanced Full-Electric and Hybrid Powertrain Design. He leads the 'Group Salazar' within the Control Systems Technology section and contributes to EAISI Health and Mobility initiatives.