Embedded Files
Here is an overview of my research interests and the research projects I am leading and/or involved in.
For the list of publications and a complete list of members in our group please visit my staff page and/or the group website.
Research Interests
Research Interests
Multi-scale adaptive transport systems
Intersection of Operations Research, Machine Learning and Behavioral Modeling
Integrated data-driven and model-based techniques
Choice-based optimization models for transportation
Integrating preferences of users (shippers, carriers, passengers) into decision making models
Prediction-based real-time optimization
Stochastic and dynamic optimization models
Intermodal freight transportation
Robustness towards uncertainty in supply, demand, and operation of the (automated) equipments, vehicles, vessels etc.
Sustainable Transportation and Logistics over Water
Research projects:
Research projects:
ADAPT-OR (ERC Grant) Adaptive Transport Systems with Holistic Representation of Supply and Demand
Project leader, ERC Starting Grant
Timeline: Jan 2024 - Dec2028
For efficient and sustainable transportation, we need to model the perspective of both the supply (e.g., services, infrastructure) and the demand side (e.g., preferences of users). Only then a holistic modelling framework can be developed where the decisions at different levels learn from one another and are adapted continuously in a robust way while accommodating the different preferences.
I propose a holistic adaptive modelling framework that considers the interaction between different levels, both on the supply and demand sides, in order to adapt the decisions towards increased efficiency and sustainability. This necessitates a paradigm change in modelling as it is challenging to maintain robustness across different time-scales at the network level. I plan to achieve this by developing model-based adaptive optimization and learning methods with my expertise on optimization and behavioural modelling.
Within ADAPT-OR we are developing new models and algorithms for transportation researchers (and beyond) with self-learning capabilities. This capability will enable service providers to adapt and maintain their business, users to receive better services and society to reach sustainable transport solutions addressing one of EU’s grand challenges.
PhDs: Karel Scheepstra and Ethan Yang
Postdocs: Javier Duran Micco and Mingye Luan
FlexMobility - Design of Mixed Flexible-Fixed Public Transport Networks
NWO Open Technology Program
I am the co-PI collaborating with Javier Alonso-Mora
Our role in the project is to develop behavioral models to support choice-driven network design models in the context of mixed fixed and flexible services
PhD: Firda Gumilar
Collaborators: Gemeente Amsterdam, AMS Institute, Gaiyo, Flying Fish, The Routing Company
Timeline: 2025-2030
PATH2Zero: PAving THe way towards Zero Emission and RObust inland shipping
NWA Zero Emission Inland Shipping
Transport work package where we address strategic, tactical and operational level decisions for transport and energy systems.
PhD: Jayvee Ramos
Multi-level decision making
Timeline: 2023-2028
TRiLOGy (NWO Blauwe Route project): Sustainable Transportation and Logistics over Water: Electrification, Automation and Optimization
Project leader
Co-PI: Javier Alonso-Mora
PhD: Cigdem Karademir (finished in 2025), Postdoc: Breno Alves Beirigo (now professor @UTwente)
Collaborators: AMS, Zoev City, Gemeente Amsterdam, DEMCON and Flying Fish
The focus of my group: Strategic and Operational Level Fleet Management Models
Timeline: Oct 2020 - Jan 2025
NOVIMOVE (H2020): Novel inland waterway transport concepts for moving freight effectively
WP2 on New port & river logistics operations with Edwin van Hassel (U Antwerp)
PhD: Adrien Nicolet (finished in 2024)
The focus of my group: Optimization models for transport operations through the Rhine-Alpine corridor with incorporation on behavioral models regarding modal split across different alternatives
Timeline: 2020-2024
Artificial Intelligence for Sustainable Real-time Transportation Systems (TU DELFT - ME Cohesion Project):
PhD: Pedro Zattoni Scroccaro (finished in 2024)
Application of imitation learning ideas in a model-based setting in transportation applications.
Timeline: 2020-2024
Crowd behavior modeling (CBM) of ultra large passenger ships (TU DELFT - ME Cohesion Project):
with Austin Kana and Javier Alonso-Mora
My focus: Route choice modeling of people on board during evacuation & agent-based simulation
Timeline: Jan 2021 - Jan 2022
COMET-PS: Complexity Methods for Synchromodality (NWO project)
Lead the project on the TU Delft side
PhD: Rie Larsen (finished in 2022)
Our role: develop predictive models for synchromodal transportation
Closely collaborating with: CWI, TNO, CTT (Combi Terminal Twente), Port of Amsterdam
Timeline: 2018-2022
Google Sites
Report abuse