Team

Faculty

Francisco Pereira
Professor
  • Machine Learning
  • Intel. Transport Systems
  • Simulation Modelling
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Carlos Lima Azevedo
Associate Professor
  • Transport Simulation
  • Demand Management
  • Behaviour Modelling
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Filipe Rodrigues
Associate Professor
  • Machine Learning
  • Urban Mobility
  • Econometrics
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Rico Krueger
Associate Professor
  • Choice Modelling
  • Machine Learning
  • Bayesian Methods
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Postdocs

Miguel Costa
  • Intelligent Transportation Systems
  • Cycling Safety
  • Machine Learning
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Serio Agriesti
  • Simulations
  • Transport Modeling
  • Impact Assessment
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Lui Albæk Thomsen
  • Human-Computer Interaction
  • Virtual Reality
  • Multimodality
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PhD Students

Xiaoyi Wu
  • Machine Learning
  • Transp. Optimization
  • Simulation
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Danya Li
  • Machine Learning
  • Traffic Forecasting
  • Transportation
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Dang Viet Anh Nguyen (Andrew)
  • Learning-based Control
  • Reinforcement Learning
  • Intelligent Systems
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Julia Guggenberger
  • Tradable Credits Schemes
  • Behavioral Economics
  • Individual Mobility
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Francisco Madaleno
  • Active Learning
  • Metamodeling
  • Causal Discovery
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João Böger
  • Inductive Biases
  • Simulation Metamodels
  • Neural Networks Architecture
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Oskar Bohn Lassen
  • Causal Graph Neural Networks
  • Simulation metamodels
  • Neural architecture search
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Daniel Guerrero-Domínguez
  • Quantum Computing
  • Quantum Algorithms
  • Quantum Optimization
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Johane Hvidberg Conradsen
  • Bayesian Machine Learning
  • Choice Modelling
  • Mathematical Psychology
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Isabela Maranca
  • Choice Modelling
  • Public Transport
  • Infrastructure Design
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Lanlan Yan
  • Choice Modelling
  • Machine Learning
  • Behavioral Neuroscience
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Miriam Pasternak Jørgensen
  • Agent-Based Modelling
  • Information Systems
  • Machine Learning & AI
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Junbo Xia
  • Mobility Cultures
  • Geospatial Analytics
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Ongoing Collaborations

Fatemeh Siar (DTU)
Co-supervision with Prof. Felix Wilhelm Siebert
  • Computer Vision
  • Video Understanding
  • Road Safety
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Alfredo Jose Ojeda Diaz (DTU)
Co-supervision with Prof. Sonja Haustein
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Marta A. Conceição
co-supervised with Prof. Bruno Miranda (FMUL)
Loïs Mitteke Jackson (DTU)
Co-supervision with Prof. Felix Wilhelm Siebert
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Maria Lucchetta (DTU)
Co-supervision with Prof. Sonja Haustein
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Ollie Wiesner (University of Washington)
 

Research Assistants

Nora Grace Clage
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Past Members

Faculty / Researchers
Samitha SamaranayakeVisiting from Cornell
Ricardo DazianoVisiting from Cornell
Postdocs
PhD students
Lorena Torres Lahoz 2025. Thesis title: Choices, Experiences and Scenario Discovery in Emotions and Travel
Carolin Schmidt 2025. Thesis title: Prediction and Learning-based Control for Autonomous Mobility
Atefeh H. Golsefidi 2024. Thesis title: Adaptive and Flexible Charging Network Expansion with Reinforcement Learning, Optimization and Simulation
Frederik Boe Hüttel 2024. Thesis title: Deep Bayesian Modelling for Uncertainty Estimation in Transportation Systems
Mathias Niemann Tygesen 2024. Thesis title: Spatio-temporal Machine Learning for Future Mobility: Precision, Resilience, and Adaptability
– Ioanna Arkoudi 2024. Thesis title: Embedding Representations for Discrete Choice and Travel Demand Models
– Christoffer Riis 2024. Thesis title: Bayesian Machine Learning for Simulation Metamodeling
– Antoine Dubois 2021 – 2023
– Sergio Garrido 2019 – 2022
Visiting PhD students / External Collaborations
Rubina Singh (University of Washington) 2025
Ekin Uguel (University of Washington) 2025
Manuel Merolla (Sapienza University of Rome) 2025
Cheng Lyu (Technical University of Munich) 2025
Hao Wu (Technical University of Munich) 2025
– Noam Katzir (Technion)
– Silke Kaiser
– Cloe Cortes Balcells (EPFL)
– Keren-Or Rosenbaum (Technion)
Lampros Yfantis (UCL)
Mohamed Eldafrawi (Sapienza University of Rome)
Santa Maiti (TUM), Visiting postdoc
Mana Meskar (SUT)
Bianca Pascariu (Université Gustave Eiffel), Visiting postdoc
Anna Martins (IST), Co-supervision with Prof. Filipe Moura
Gabriel Valença (IST), Supervised by Filipe Moura and Ana Morais de Sá
Zhongcan Li (Southwest Jiaotong University), Co-supervision with Profs. Liping Fu and Chao Wen
Xu Yan (Southwest Jiaotong University), Co-supervision with Prof. Evelen van der Hunk
– Yunhai Gong (Dalian University of Technology) 2022, Co-supervision with Prof. Shaopeng Zhong
– Mingzhuang Hua (Southeast University) 2022, Co-supervision with Prof. Xuewu Chen
Vishnu Baburajan 2021, Thesis title: Automated Text Analysis on Open Ended Response Surveys: Measuring Attitudes Regarding Autonomous Vehicles
Nassim Motamedi (TUM) 2019, Thesis title: “Data­driven modeling of lane changing on freeways”
MSc students
– Mathias Sofus Hovmark 2024, MSc Business Analytics, Thesis: Using Context-Aware Bayesian Mixed Multinomial Logit Models for Predicting Travel Behaviour with Rejsekort Data
– Dimitrios Agyros 2023, MSc Transport & Logistics, Thesis: Simulation and Assessment of Congestion Pricing Control through Machine-Learning
– Anders Lassen 2023, MSc Mathematical Modelling and Computation, Thesis: Reinforcement Learning for Adaptive Congestion Pricing
– Þórður Örn Stefánsson 2023, MSc Human-Centred AI, Thesis: Investigating the effects of activity patterns and urban context on individuals’ emotional state
– Hildur Lára Jónsdóttir, Gudrun Gudnadottir 2023, MSc Industrial Engineering, Thesis: Data Exploration, Reliability and Simulation of Travel in the Public Transportation Network: A Case Study of Greater Copenhagen
– Frederik Sandström Ommundsen 2023, MSc Business Analytics, Thesis: Spatial analysis of mental health, mobility and urban context data using machine-learning techniques
– Alexandre Bernard-Michinov 2023, MSc Transport & Logistics, Thesis: Exploring Bayesian Optimisation for Scenario Discovery in Complex Mobility Simulation
– Dimitrios Zerzis 2023, MSc Transport & Logistics, Thesis: Calibration of Activity-based models using Bayesian Optimisation
– Jesper Hauch 2023, MSc Mathematical Modelling and Computation, Thesis: Learning and Generalizing Polynomials in Simulation Metamodeling
– Carl Johan Astrup, Julian Simon Róin Skovhus 2023, MSc Mathematical Modelling and Computation, Thesis: Uncovering Censorship: Poisson Regression for Estimating Latent Demand in EV chargers
– Lukas Ralf Schinzel 2022, MSc Mathematical Modelling and Computation, Thesis: Exploring advanced visualization for microscopic mobility insights
– Pernille Sand 2022, MSc Mathematical Modelling and Computation, Thesis: Causality, Invariance, Hierarchical Bayes
– Lawrence Egyir 2022, MSc Mathematical Modelling and Computation, Thesis: SAS cargo predictions
– Mark Tselikov 2022, MSc Business Analytics, Thesis: Causal Metamodels for Simulators
– Theis Hjortkjær 2022, MSc Math. Modelling and Comp., Thesis: Zero-Shot learning of shared mobility demand using meta learning and graph neural networks
– Toke Bøgelund-Andersen 2022, MSc Business Analytics, Thesis: Predicting Car Pick-Up Times in Shared Mobility with Deep Graph Neural Networks
– Peter Groth 2022, MSc Math. Modelling and Comp., Thesis: Trajectory Forecasting with Graph Neural Networks
– Lorena Torres Lahoz 2022, MSc Math. Modelling and Comp., Thesis: Latent Class Choice Models using Machine Learning: Application to Individual Decisions in Sustainable Mobility
– Aikaterini Antonoudi & Andreas Arampatzis 2021, MSc Transport & Logistics, Thesis: Estimating Spatio-Temporal Demand for Electric Vehicle Charging
– Gauthier Belpaire 2021, MSc Business Analytics, Thesis: EV charging demand prediction from GPS traces
– Jacques Michel 2021, MSc Business Analytics, Thesis: Machine Learning applied to shipbuilding market analysis
– Mattia Andreotti 2021, MSc Industrial Engineering, Thesis: Predictive Maintenance at Haldor Topsoe
– Andreas Kaae 2021, MSc Transport & Logistics, Thesis: Survival Analysis Modeling of Electric Vehicle Charging
– Aijie Shu 2021, MSc Transport & Logistics, Thesis: Multi-task classification of trip mode and purpose: Leveraging transfer-learning and artificial neural networks on noisy and class-imbalanced GPS trajectories”
– Joan Omella 2021, MSc Transport & Logistics, Thesis: Metamodel optimization for traffic simulation calibration
– Kleio Milia & Magnus Hedengran 2021, MSc Transport & Logistics, Thesis: Smart parking: Forecasting cruising time using big data”
– Michael Wamberg 2021, MSc Math. Modelling and Comp., Thesis: Bayesian inference for probabilistic skill assessment: Ranking and rating of football clubs and players
– Simone Vestergaard & Rebecca Sommer 2021, MSc Business Analytics, Thesis: Automization of the supplier selection for SimpleFeast to ensure maximization of value
– Christian Glissov & Tobias Konradsen 2021, MSc Math. Modelling and Comp., Thesis: Recurrent Flows for Video Generation
– Francisco Jose Perez Dominguez 2020, MSc Transport & Logistics, Thesis: Applying a multi-layer network model for multi-modal trip planning in Maas
– Antonios Koutounidis 2020, MSc Transport & Logistics, Thesis: A travel and energy behaviour sensitive optimisation for charging of private EV fleet in the Danish context
– David Zhuravlev 2020, MSc Industrial Engineering, Thesis: Developing a reinforcement learning approach to trading strategy in energy balancing markets
– Nikolaos Nakis 2020, MSc Math. Modelling and Comp., Thesis: Task-free Variational Continual Learning
– Kasper Rolsted 2020, MSc Math. Modelling and Comp., Thesis: Generalized Heteroscedastic Multi-output Censored Gaussian Processes for Demand Prediction
– Mathias Tygesen 2020, MSc Math. Modelling and Comp., Thesis: Density estimation with Normalizing Flows
– Johannes Benjamin Eckert 2019, MSc Industrial Engineering, Thesis: Exploring blockchain in user-centric emission trading systems for multi-modal mobility
– Kris Walther 2019, MSc Math. Modelling and Comp., Thesis: Spatio-temporal modelling and forecasting of road traffic using Gaussian processes and deep neural nets
– Anders Parslov 2019, MSc Math. Modelling and Comp., Thesis: Uncertainty Estimation and Quantile Regression in Neural Networks for Bus Arrival Time Prediction
– Mathilde Loft 2019, MSc Math. Modelling and Comp., Thesis: Deep Survival Analysis for Shared Mobility
– Sebastian Balle 2019, MSc Math. Modelling and Comp., Thesis: Spatio-temporal analysis of bicycle incidents in the urban area of Copenhagen
Research assistants
– Antonios Koutounidis 2020-2022
– Nina Friser Holst
– Louise Amanda Bünger Sørensen