Operations Research · Transport Systems · Data Science

I help transport systems run better in the real world.

I combine optimization, data and operational knowledge to study how transport systems can make better decisions under real-world constraints.

My work spans flexible mobility, transport data and public-sector operations: from model to decision.

Flexible & demand-responsive mobility
Transport optimization & operations
Data science & decision support

Fabio Sartori

About

Hi, I'm Fabio.

“Optimizing a system is more than lowering the objective function. It is being fast, cheap and efficient!”

I am a transport engineer who fell in love with optimization early and never got over it. Show me a fleet, a timetable or a bus network and I will start asking how it could run better tomorrow morning, with the data we have today.

I have looked at that question from many seats: running a municipal transport department in Brazil, a PhD at KU Leuven on demand-responsive buses, vehicle energy data at a European research institution, and now automated electric shuttles in France. Every seat taught me the same thing: the best model is the one people actually use.

That is what I enjoy most. Sitting with the people who run a service, understanding their problem, and handing back an answer that saves time, money and energy.

Method

Every project follows the same chain: understand the decision, turn the data into a picture of the system, model or simulate it, decide, and check the result against reality. The method follows the problem: mixed-integer programming and decomposition, constraint programming, metaheuristics, simulation, statistics and machine learning.

What I bring is having sat on both sides of the table, at different moments. In Brazil I was on the side that lives with the decision: budgets, regulation, timetables, a bus concession under review. In research I built the optimization models. Bringing the two together is what I am doing now with automated electric shuttles: operating rules and energy limits go into the model from the start, and the model has to be fast enough to rerun when the day changes.

Fabio Sartori

Experience

2025 – now Postdoctoral research · France

Automated electric shuttles

Scheduling, charging and operational adaptation for an experimental electric shuttle service.
2024 – 2025 European research institution

Applied data science

Vehicle energy modelling from real-world telemetry and instrumented driving data, including the reconstruction of variables not directly reported by the vehicle.
2019 – 2024 Doctoral research · Belgium

Demand-responsive transport

Optimization of flexible public transport services under capacity and operational constraints.
2017 – 2019 Municipal administration · Brazil

Public sector

Transport planning, bus concessions, regulation and mobility policy, first leading a municipal transport department and later serving as deputy head of transport in a state capital.
2016 – 2023 Universities in Brazil and Belgium

Teaching

Operations research, programming and transport-related quantitative methods, with supervision of student research.
2026 Side project

HELMET

HELMET stands for Hierarchical Exact Learning ModEl for Transportation. Testing whether the methods of my research can become a planning tool for electric on-demand operators. So far: a product proposal, a market study and a pitch, selected for EIT Jumpstarter 2026.

Fabio Sartori

Research

Selected research by theme

Flexible and demand-responsive transport

Optimization of a semi-flexible demand-responsive feeder bus system using variable neighborhood search International Transactions in Operational Research · 2025
Optimization of a semiflexible demand-responsive feeder system in suburban areas using a memetic algorithm Journal of Advanced Transportation · 2023
A survey on demand-responsive public bus systems Transportation Research Part C · 2022
Hierarchical optimization for resilient real-time operation of automated electric shuttle services INSTR · 2026
Fleet sizing and scheduling for battery-electric automated shuttles using Benders decomposition ICTS · 2026
Optimizing a demand-responsive feeder system for low-demand areas hEART · 2022

Behaviour and safety

Drivers' speed profile at curves under distraction task Transportation Research Part F · 2017
Driving-simulator validation and eye-fixation analysis under mental workload ANPET · 2014–2017
Road safety on five continents RS5C · 2018

Vehicle energy and data

Benchmarking the real-world energy benefits of vehicle-integrated photovoltaics Transport and Pollution (TaP) Conference · 2025 · co-author
Unveiling the energy impact of vehicles' automation: a first empirical estimation TRB Annual Meeting · 2025 · contributor

Recognition Cátedra Abertis Prize for the master's dissertation in transportation engineering.

Training Delft Road Safety Course for Latin America, TU Delft · 2018
Machine Learning for Earth Systems Modelling, ECMWF three-course online series · 2026 (in training)

Fabio Sartori

I help transport systems run better in the real world.

Hi, I'm Fabio.

Experience

Automated electric shuttles

Applied data science

Demand-responsive transport

Public sector

Teaching

HELMET

Selected research by theme

Flexible and demand-responsive transport

Behaviour and safety

Vehicle energy and data

Perspective

Let's talk