Since December 2021 I am an Assistant Professor in the Fluids and Flows group, Department of Applied Physics, Technische Universiteit Eindhoven.

Active flowing matter

pedestrian dynamics & automated tracking

statistical mechanics & Langevin equations, for and from big data analytics

computer vision & deep neural networks

machine learning for dynamical systems and turbulence

scientific & high performance computing, scientific data management

software design & engineering

An extensive description of my work on pedestrian crowds including pictures and videos can be found on the website of the Crowdflow research group.

In the period 2019-2021, I have been the PI of the NWO-VENI research grant:

financed by the Netherlands Organisation for Scientific Research (NWO).

Jan. 2019 - Nov. 2021 University researcher

Technische Universiteit Eindhoven. Department of Applied Physics - Group: Fluids and Flows (via personal NWO-VENI grant)
Jan. 2016 - Dec. 2018 Post-doctoral researcher

Technische Universiteit Eindhoven. Department of Applied Physics - Group: Turbulence and Vortex Dynamcs (WDY)

Jan. 2013 - Feb. 2016 Ph.D. Applied Mathematics

Technische Universiteit Eindhoven. Centre for Analysis, Scientific Computing and Applications (CASA)

Jan. 2012 - Jun. 2016 Ph.D. Structural Engineering

Polytechnic university of Turin. Department of Structural Engineering, Construction and Soil Mechanics

Jan. 2014 Consultant

Crowd dynamics at Milano Expo2015, NH Pavillion

Mar. 2011 - Dec. 2012 Visiting student

Los Alamos National Laboratory. Theoretical division T5 - Plasma physics and applied mathematics

Sept. 2009 - Dec. 2011 Msc. Mathematical Engineering

Polytechnic university of Turin. Department of Mathematics.

Sept. 2006 - Oct. 2009 Bsc. Mathematics for Engineering Sciences

Polytechnic university of Turin. Department of Mathematics.

I am fluent in numerous programming languages for (and beyond) scientific computing, data analytics, web and automation.

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Editor-in-chief Collective Dynamics.

Guest editor of Safety Science for the special issue "Pedestrian and evacuation dynamics 2023".

Guest editor of Journal of Advanced Transportation for the special issue "Empirical Research on Pedestrians’ Behavior and Crowd Dynamics".

Machine Learning for Science (BSc, responsible teacher since 2019)

Machine Learning for Fluid Mechanics (Msc, responsible teacher since 2023)

Chaos (MSc in Physics, co-teacher since 2019)

Sociophysics 1,2,3 USE Learning Line (BSc, 2020-2022)

Computational and Mathematical Physics (Tutoring, MSc, 2016-2022)

2024-ongoing Apoorva Singh, Msc, PhD in Applied Physics. Topic: System identification for dynamical systems and pedestrian dynamics

2024-ongoing Lars Sickert Karam, Msc, PhD in Applied and Industrial Mathematics. Topic: Statistical methods and active learning for pedestrian dynamics

2023-ongoing Chiel vd Laan, Msc, PhD in Applied Physics. Topic: Methods and modeling for crowds dynamics

2020-ongoing Cas Pouw, Msc, PhD in Applied Physics. Topic: pedestrian flows analytics

2020-ongoing Giulio Ortali, Msc, PhD in Applied Physics. Topic: machine learning for fluid mechanics

2020-2022 dr. Alessandro Gabbana, Post-doc in Applied Physics. Topic: pedestrian flows analytics

2024-ongoing Youri Martin, Particle-in-cell simulations of flowing plasmas. Topic: (with H. Clercx)

2024-ongoing Chris v Ham, Machine learning optimization of porous materials. Topic: (with H. Huinink)

2024 Bram vd Buijs, A maximum entropy approach to model pedestrian waiting distributions. Thesis: ** (with C. vd Laan)

2024 Clement Le Berre, Erasmus internship (Télécom Physique Strasbourg). Thesis: *Radio-optical sensor fusion* (with C. vd Laan)

2024 Maude Willems, Msc in Industrial Engineering and Innovation Sciences. Thesis: *Interactions in queuing environments: The influence of situational characteristics and sociophysical structures on queuing behavior* (with dr. A. Haans)

2023 Lex Woestemeier, Externship Msc in Physics (ProRail BV). Thesis: *High statistics pedestrian dynamics data analysis*

2023 Tom Harmsen, Bsc in Physics. Thesis: *Unveiling dynamical features of small size social groups*

2023 Gijs van Bakel, Bsc in Physics. Thesis: *Stairs or escalator? Exploring and modelling routing choices at a train station*

2023 Imre Atmodimedjo, Bsc in Physics. Thesis: *Embedding symmetry into neural networks with applications for lattice Boltzmann collisions* (with dr. A. Gabbana)

2023 Lysander Herrewijn, Bsc in Physics. Thesis: *Quantifying turbulence intensity via velocity signals through one-shot and autoregressive deep learning models* (with G. Ortali)

2022 Rik Heitzer, Bsc in Physics. Thesis: *Multisensor 3D depth vision for real-life pedestrian tracking: Geometry and temperature calibration* (with dr. A. Gabbana)

2022 Lex Woestemeier, Bsc in Physics. Thesis: *Nudging pedestrian flows via sonification* (with dr. T. Senan)

2022 Stijn van Hees, Msc in Applied Physics. Thesis: *Modelling individual routing of pedestrians as a utility maximization process using inverse reinforcement learning* (with dr. A. Gabbana, prof. F. Toschi)

2022 Bob Beunen, Msc in Applied Physics | Msc in Mechanical Engineering. Thesis: *Learning the Lattice Boltzmann method gas-wall interaction scattering kernel from molecular dynamics data* (with dr. A. Gabbana, prof. F. Toschi, prof. H. v Brummelen)

2022 Joost Prins, Msc in Applied Physics. Thesis: *Lattice Boltzmann method with a neural network collision operator* (with dr. A. Gabbana, prof. F. Toschi, dr. V. Gyria, dr. D. Livescu)

2021 Nirvana Pecorari, Msc in Physics. Thesis: *Machine Learning and crowd dynamics: a real-life case study* (with dr. A. Gabbana)

2021 Tjerk Mathijssen, Bsc in Applied Physics. Thesis: *Approximation of pedestrian distribution on the train platform and the application of the Langevin equation on pedestrian data*

2021 Jesse van den Tempel, Bsc in Applied Physics. Thesis: *Tuning pedestrians: Research preparation on the influence of sound on trajectories* (with dr. T. Senan)

2021 Luc Geurts, Bsc in Applied Physics and Mathematics. Thesis: *Pedestrian Dynamics: modelling the trajectory of a single pedestrian on a curved path with a constant speed in a force-free environment* (with prof. W. Schilders)

2021 Andrea di Benedetto, Msc internship in Applied Physics. Thesis: *Graph-based real time estimation of secondary infection probabilities*

2021 Frenk Cleven, Msc in Applied Physics. Thesis: *Data-driven estimation of equilibrium distribution functions for pedestrian dynamics* (with prof. F. Toschi)

2021 Tim de Jong, Bsc Applied Physics. Thesis: *Pointing a movinghead to pedestrians using trajectory prediction* (with dr. P. Ross)

2021 Teodora Lazar, Bsc Applied Physics. Thesis: *Modeling of the emergent behavior for a unidirectional pedestrian flow at a bifurcation point* (with dr. A. Gabbana)

2021 Geert vd Vleeuten, Bsc in Applied Physics and Mathematics. Thesis: *Modeling fluctuations of single pedestrian dynamics on curved paths* (with prof. W. Schilders)

2021 Thomas Wagenaar, Bsc Applied Physics. Thesis: *Measuring turbulence intensity by deep learning short inertial measurements from quadcopters* (with prof. F. Toschi)

2021 Daan Eskes, Bsc in Applied Physics. Thesis: *Towards optimal automated crowd management via Reinforcement Learning*

2020 Joris Willems, Msc in Computer Science. Capita selecta. Thesis: *Learning Dynamical Systems With A Deep Generative Model*

2020 Cas Pouw, Msc in Applied Physics. Thesis: *Efficient and scalable analytics frameworks for high-statistics crowd dynamics*

2020 Joost Prins, Applied Physics External traineeship (at Sioux Lime Eindhoven). Thesis: *Sub-geometry-wise data-driven RANS modeling of turbulence*

2020 Danvy Vu, Bsc in Applied Physics. Thesis: *Towards automated crowd management via Reinforcement Learning*

2020 Victor Browers, Bsc in Applied Physics. Thesis: *Feature recognition in STM images: A conventional technique vs. a machine learning approach* (Machine Learning advisor role, with D. Tjeertes, P. Koenraad)

2020 Jay van Erve, Bsc in Applied Physics. Thesis: *Do pedestrians walk to minimize their travel time?*

2020 Arco van Beek, Msc internship in Applied Physics. Thesis: *Influence of light settings on pedestria dynamics*

2020 Arthur Groot Zevert, Bsc in Applied Physics. Thesis: *Modeling pedestrian dynamics on curved paths*

2020 Roberto Mella, Bsc Erasmus internship in Applied Physics. Thesis: *Optical Flow in Pedestrian Tracking*

2019 Stan vd Burg, Bsc in Applied Physics. Thesis: *Disentangling and Compressing usage patterns in Crowd Flows*

2019 Niels Peters, Bsc in Applied Physics. Thesis: *Optical Flow in Pedestrian Tracking*

2022 Dario Chinelli, Bsc in Applied Physics. Thesis: *Statistical learning and simulating the paths of walking pedestrians*

2019 Joost Visser, Msc in Computer Science.. Thesis: *StampNet: Unsupervised Multi-Class Object Discovery* (with dr. V. Menkovski)

2018-2019 Gerben Beintema, Msc in Applied Physics. Thesis: *Controlling Thermal Convection via Reinforcement Learning*

2019 Rick de Kreij, Bsc in Applied Physics. Thesis: *A multi-scale model for real-life pedestrian arrival processes*

2019 Lars Raaijmakers, Internship in Applied Physics. Thesis: *Learning conditional probability distributions from sampled data with application to kinetic simulations of fluids*

2018 Joris Willems, Bsc in Applied Physics. Thesis: *Pedestrian Orientation: Accurate Measurements and Dynamics*

2018 Lars Schilders, Bsc in Applied Physics. Thesis: *Superposition of interactions in pedestrian dynamics*

2017-2018 Werner Kroneman, Scientific software developer and research assistant. Thesis: *Accurate pedestrian localization via height-augmented HOG*

2017-2018 Joost Visser, Msc in Computer Science. Capita selecta. Thesis: *Unsupervised deep learning* (with dr. V. Menkovski)

2015-2016 Jasper A. Meeusen, Msc in Applied Physics. Thesis: *Dense crowd dynamics*

2016 Diana Gonzalez, Msc in Sustainable Energy Technology. Thesis: *Anticipatory Lighting Control Systems* (with prof. E. van Loenen, prof. F. Toschi, ir. C. de Bakker)