Faculty
Postdocs
PhD Students
Visiting PhD Students / Ongoing Collaborations
Gabriel Valença (IST)
Visiting Student (Supervised by Filipe Moura and Ana Morais de Sá)
Miguel Costa (IST)
Co-supervision with Prof. Filipe Moura and Manuel Marques
Mohamed Eldafrawi (Sapienza University of Rome)
Co-supervision with Prof. Guido Gentile
Keren-Or Rosenbaum (Technion - Israel Institute of Technology)
Co-supervision with Prof. Yoram Shiftan
Zhongcan Li (Southwest Jiaotong University)
Co-supervision with Profs. Liping Fu and Chao Wen
Yunhai Gong (Dalian University of Technology)
Co-supervision with Prof. Shaopeng Zhong
Xu Yan (Southwest Jiaotong University)
Co-supervision with Prof. Evelien van der Hurk
Ana Martins (IST)
Co-supervision with Prof. Filipe Moura
Mingzhuang Hua (Southeast University)
Co-supervision with Prof. Xuewu Chen
Cloe Cortes Balcells (EPFL)
Co-supervision with Prof. Michel Bierlaire
Past Members
Faculty / Researchers
Postdocs
PhD students
– Sergio Garrido 2019 – 2022, Thesis title:
– Valentino Servizi;2022, Thesis title: Mining User Transport Behavior from Smartphones
– David Durán-Rodas 2021, Thesis title: Efficiency and/or equity? Understanding and planning bike-sharing based on spatial fairness
– Niklas Petersen 2021, Thesis title: Multi-model bus arrival prediction with intelligent handling of uncertainties
– Inon Peled 2021, Thesis title: Machine Learning Methods for Transportation under Uncertainty
– Ioulia Markou 2019, Thesis title: Detection, analysis and prediction of traffic anomalies due to special events
– Aliasghar Mehdizadeh Dastjerdi 2019, Thesis title: ATIS and Commuters Behavior: Factors Affecting Behavioral Intentions Toward the Use of Travel Information Technology
Visiting PhD students / External Collaborations
– Giovanni Tuveri (University of Cagliari), Co-supervision with Prof. Italo Meloni
– Santhanakrishnan Narayanan (TUM), Co-supervision with Prof. Constantinos Antoniou
– Lampros Yfantis (UCL), Co-supervision with Prof. Maria Kamargianni
– Francisco Antunes 2021, Thesis title: Active Learning Metamodels for Transport Simulation Problems
– Vishnu Baburajan 2021, Thesis title: Automated Text Analysis on Open Ended Response Surveys: Measuring Attitudes Regarding Autonomous Vehicles
– Georges Sfeir 2021, Thesis title: Integration of Machine Learning and Discrete Choice Models to Better Predict and Describe Decision Makers’ Choices with Applications to Travel Decisions
– Yafei Han (MIT) 2019, Thesis title: Neural-embedded discrete choice models
– Nassim Motamedi (TUM) 2019, Thesis title: “Datadriven modeling of lane changing on freeways”
– Haizheng Zhang (MIT) 2018, Thesis title: Online calibration for simulation-based dynamic traffic assignment: towards large-scale and real-time performance
MSc students
– 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