Description
Leader of the group Stochastics: Bert Zwart.
Many natural and man-made systems and processes are driven by random phenomena. Examples can be found in areas such as communication, energy, information, logistics, and transportation systems. In order to model, describe, and improve such systems, our group develops and studies probabilistic, operational and statistical models. Our group’s analysis of these models relies on techniques from fundamental probability theory, queueing theory, stochastic scheduling, spatial stochastics and stochastic geometry. Our work with various companies in these areas, as well as with top researchers and universities across the globe, ensures our position at the forefront of every aspect of this research field.
Vacancies
No vacancies currently.
News
Transportation Research Board Showcase Paper for Stochastics Researchers
Their article "Long-Term Forecasting of Off-Street Parking Occupancy for Smart Cities was" selected by the Transportation Demand Committee from more than 100 papers submitted in 2020.
First prize for logistic innovation COVID-19 vaccination strategy
The jury was impressed by the submission titled ‘A fast and responsive supply chain’ by CWI (Rob van der Mei) and HvA (Dennis Moeke).
KUHN Award for Stochastics researchers
Naval Research Logistics (NRL) has awarded the Harald W. Kuhn Award 2020 to Bernard Zweers, Rob van der Mei and Sandjai Bhulai (VU) for their paper “Optimizing barge utilization in hinterland container transportation”.
CWI researchers analyze suicide prevention help calls during pandemic
Salim Salmi, PhD-student in CWI's Stochastics group, analyzed conversations between Stichting 113 Suicide Prevention caregivers and clients before and during the COVID-19 pandemic.
Current events
PhD Defence Mihail Bazhba - ST
- 2021-05-26T16:00:00+02:00
- 2021-05-26T17:30:00+02:00
PhD Defence Mihail Bazhba - ST
Start: 2021-05-26 16:00:00+02:00 End: 2021-05-26 17:30:00+02:00
On 26 May 2021 at 4 PM Mihail Bazhba will defend his dissertation "Large Deviations for Semi-exponential Distributions: Theory and Applications" at TU/e.
1st promoter: Prof. A.P. (Bert) Zwart - CWI and TU/e
Co-promotor: Chang-Han Rhee - Northwestern University (USA)
The defense is hybrid, but permitted audience is very limited. It will take place in Lecture room 4 in the Auditorium at TU/e in Eindhoven.
Members
- Rebekka Arntzen
- Rob van den Berg
- Wouter Berkelmans
- Guus Berkelmans
- Etienne van de Bijl
- Mark Blokland
- Tim de Boer
- Ruurd Buijs
- Elisabeth Fokker
- Arwin Gansekoele
- Thomas Koch
- Britt van Leeuwen
- Marie-Colette van Lieshout
- Robin Markwitz
- Rob van der Mei
- Marta Milewska
- Rudesindo Núñez Queija
- Joris Pries
- Salim Salmi
- Bert Zwart
Associated Members
Publications
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Ghazanfari, S, van Leeuwen, D, Ravner, L, & Núñez Queija, R. (2021). Commuter behavior under travel time uncertainty. Performance Evaluation, 148. doi:10.1016/j.peva.2021.102200
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van den Berg, J, & Nolin, P. (2021). Near-critical 2D percolation with heavy-tailed impurities, forest fires and frozen percolation. Probability Theory and Related Fields. doi:10.1007/s00440-020-01022-4
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Garcia, B. L., Bekker, R, van der Mei, R.D, Chavannes, N.H, & Kruyt, N.D. (2021). Optimal patient protocols in regional acute stroke care. Health Care Management Science. doi:10.1007/s10729-020-09524-2
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Buijs, R.J.W, Koch, T, & Dugundji, E.R. (2021). Using neural nets to predict transportation mode choice: Amsterdam network change analysis. Journal of Ambient Intelligence and Humanized Computing. doi:10.1007/s12652-020-02855-6
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Koch, T, & Dugundji, E.R. (2021). Limitations of recursive logit for inverse reinforcement learning of bicycle route choice behavior in Amsterdam. In Proceedings of the Transportation Research Board 100th Annual Meeting.
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van Kampen, J.R.A, Pauwels, E.J.E.M, van der Mei, R.D, & Dugundji, E.R. (2021). Understanding the relation between travel duration and station choice behavior of cyclists in the metropolitan region of Amsterdam. Journal of Ambient Intelligence and Humanized Computing. doi:10.1007/s12652-020-02856-5
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Tabatabaei, S.A, Klein, J.G, & Hoogendoorn, M. (2021). Estimating the F1 score for learning from positive and unlabeled examples. In LOD 2020: Machine Learning, Optimization, and Data Science (pp. 1–12). doi:10.1007/978-3-030-64583-0_15
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Koch, T, & Dugundji, E.R. (2021). Determining the effect of lower public transit frequencies in COVID-19 timetables on perceived door-to-door travel times using Pareto optimal range queries. In Proceedings of the Transportation Research Board 100th Annual Meeting.
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Salmi, S, Mérelle, S, Gilissen, R, & Brinkman, W.-P. (2021). Content-based recommender support system for counselors in a suicide prevention chat helpline: Design and evaluation study. Journal of Medical Internet Research, 23(1). doi:10.2196/21690
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Zweers, B.G, Bhulai, S, & van der Mei, R.D. (2020). Pre-processing a container yard under limited available time. Computers & Operations Research, 123(105045). doi:10.1016/j.cor.2020.105045
Current projects with external funding
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Ontwikkeling van Data Analytics, Data Science en Crypto Analyse technieken ()
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Impactstudie Noord/Zuidlijn Gemeente Amsterdam
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Samenwerkingsovereenkomst Stichting 113 / CWI - Zelfmoordpreventie
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Data-driven optimization for a vital elderly care system in the Netherlands (DOLCE VITA)
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Lane Analysis & Route Advisor (LARA)
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Evidence-based effective monitoring and control of Covid-19 after the initial outbreak (None)
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State estimation for spatio-temporal point processes with applications to criminology (None)
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PPS Engie
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Robust, Effective and Adaptable Ship Designs for Uncertain Transition Paths (READINESS)
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Urban Mobility Observatory (UMO)
Related partners
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Gemeente Amsterdam
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RIVM
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Stichting 113
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Universiteit Wageningen
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Academisch Medisch Centrum
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Engie Services West Nederland B.V.
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Erasmus Universiteit Rotterdam
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Leids Universitair Mediach Centrum
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Technische Universiteit Eindhoven
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Technische Universiteit Delft
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Universiteit Utrecht
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Vrije Universiteit Amsterdam