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 Journal of Advanced Transportation for the special issue "Empirical Research on Pedestriansâ€™ Behavior and Crowd Dynamics".

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

Machine Learning for Turbulence (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)

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

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

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

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)