Alessandro Corbetta, Ph.D. Resume
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Currently
Since December 2021 I am an Assistant Professor in the Fluids and Flows group, Department of Applied Physics, Technische Universiteit Eindhoven.
Research interests
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).
orcid.org/0000-0001-6979-3414Publication list
Previous positions & education
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.
Technology & IT
I am fluent in numerous programming languages for (and beyond) scientific computing, data analytics, web and automation.
More...
Editorial activity
Editor-in-chief Collective Dynamics.
Guest editor of Journal of Advanced Transportation for the special issue "Empirical Research on Pedestrians’ Behavior and Crowd Dynamics".
Teaching at TU/e
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)
Phd Students and Post-doctoral fellow supervision
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
Bsc and Msc Students
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)