Eindhoven SPOR Seminar

This biweekly seminar invites excellent speakers from around the world to speak at the SPOR cluster at the department of Mathematics and Computer Science of Eindhoven University of Technology.  The talks concern all realms of stochastics, algorithmics, and discrete mathematics (e.g., probability theory, statistics, operations research, and combinatorial optimization). Emphasis is placed on the context, the motivation, and the main ideas behind the presented results. The audience ranges from senior researchers to first year Ph.D. students. 

The seminar is organized by Aida Abiad Monge, Elisa Perrone, Jaron Sanders, Neeladri Maitra, Noela MüllerIvo Stoepker, and Alexander Van Werde.

Upcoming and recent talks (2023)

Upcoming talks

September 26: Ralph Neininger (Goethe University Frankfurt)
Recursive distributional equations in applications

Recursive distributional equations (RDE) appear in various areas of probability such as the probabilistic analysis of algorithms, probabilistic number theory, stochastic geometry or, more recently, in distributional reinforcement learning (DRL). In this talk more applied aspects of RDE are discussed in the context of their applications. Some of the new results discussed on DRL are joint work with Julian Gerstenberg and Denis Spiegel

October 10: Richard Gill (Leiden University)
Statistical issues in the investigation of a suspected serial killer nurse

Investigating a cluster of deaths on a hospital ward is a difficult task for medical investigators, police, and courts. Patients do die in hospitals (the three most common causes of deaths in a hospital are, in order: cancer, heart disease, medical errors). Often such cases come to the attention of police investigators for two reasons: gossip about a particular nurse is circulating just as a couple of unexpected and disturbing events occur. Hospital investigators see a pattern and call in the police.

I will discuss two such cases with which I have been intensively involved. The first one is the case of the Dutch nurse Lucia de Berk. Arrested in 2001, convicted by a succession of courts up to the supreme court by 2005, after which a long fight started to get her a re-trial. She was completely exonerated in 2010. The second case is that of the English nurse Lucy Letby. Arrested in 2018, 2019 and 2020 for murders taking place in 2015 and 2016. Her trial started in 2022 and concluded with a “full life” sentence a couple of months ago.

There are many similarities between the two cases, but also a couple of disturbing differences. One difference being that Lucy Letby’s lawyers seem to have made no attempt whatsoever to defend her. Another difference is that statistics was used against Lucia de Berk but not, apparently, against Lucy Letby. But appearances are not always what they seem.

Report published by Royal Statistical Society on statistical issues in these cases

News feature in “Science” about myself and my work

October 31: Cassio de Campos (TU/e)
Credal Models for Uncertainty Treatment

There is a current trend on reevaluating artificial intelligence (AI), its advancements and their implications to society. Uncertainty treatment plays a major role in this discussion. This talk will hopefully convince you that we can make AI more reliable and trustworthy by a sound treatment of uncertainty. Uncertainty is often modelled by probabilities, while it has been argued that some broadening of probability theory is required for a more convincing treatment, as one may not always be able to provide a reliable probability for every situation. Credal models generalize probability theory to allow for partial probability specifications and are arguably a good direction to follow when information is scarce, vague, and/or conflicting. We will present and discuss credal approaches from simple examples to sophisticated credal machine learning models and even their reach into both adversarial and causal inferences. The talk argues that we must continue to push AI forward by investing in Cautious AI.

Recent talks

September 12: Carla Groenland (Delft University of Technology)
Counting graphic sequences via integrated random walks

Via a new probabilistic result, we provide (1+o(1))-asymptotics for the number of integer sequences n-1>= d_1 >= … >= d_n >= 0 that form the degree sequence of an n-vertex graph (improving both the upper and lower bound by a multiplicative n^{1/4}-factor). In particular, we determine the asymptotic probability that the integral of a (lazy) simple symmetric random walk bridge remains non-negative. This talk will explain how this problem arose, what the connection is with the problem about random walks (including what all the words in this abstract mean) and then provide a short sketch of the proof. This is based on joint work with Paul Balister, Serte Donderwinkel, Tom Johnston and Alex Scott.

June 6: Lars Rohwedder (Maastricht University)
Recent advances in the Santa Claus problem

Over the past 20 years, the Santa Claus problem has been the source of many beautiful algorithmic ideas and to date remains an active and fruitful research area. The problem takes its metaphorical name from the narrative of Santa Claus distributing his gifts to children in a way that the least happy child is as happy as possible. I will give an overview over the landscape of techniques used to approach the problem, previous results as well as open questions. Then I will focus on recent joint work with Bamas [STOC’23], where we make progress towards sublogarithmic approximations.

May 17: Varun Gupta (University of Chicago)
Greedy Algorithm for Multiway Matching with Bounded Regret

We consider a finite horizon online resource allocation/matching problem where the goal of the decision maker is to combine resources (from a finite set of resource types) into feasible configurations. Each configuration is specified by the number of resources consumed of each type and a reward. The resources are further subdivided into three types – offline, online-queueable (which arrive online and can be stored in a buffer), and online-nonqueueable (which arrive online and must be matched on arrival or lost). We prove the efficacy of a simple greedy algorithm when the corresponding static planning linear program (SPP) exhibits a non-degeneracy condition called the general position gap (GPG). In particular we prove that, (i) our greedy algorithm gets bounded any-time regret when no configuration contains both an online-queueable and an online-nonqueueable resource, and (ii) O(log t) expected any-time regret otherwise (we also prove a matching lower bound). By considering the three types of resources, our matching framework encompasses several well-studied problems such as dynamic multi-sided matching, network revenue management, online stochastic packing, and multiclass queueing systems.

May 9: Cécile Mailler (University of Bath)
Scaling limit of critical random trees in random environment

It has been well-known since Aldous’ seminal work in the 90s that a critical Galton-Watson tree conditioned to survive until generation n converges, as n goes to infinity, to a continuous random tree (CRT). This is the equivalent, in the world of random trees, of the fact that a random walk with finite-variance i.i.d. increments converges to the Brownian motion. In this is joint work with Guillaume Conchon-Kerjan and Daniel Kious, we prove that a Galton-Watson tree “in random environment” (GWRE) also converges to the CRT. GWREs are GW trees in which the offspring distribution of an individual depends on its generation, and the sequence of offspring distributions (indexed by the generation) is sampled in an i.i.d. way. I will review known results on GWREs before stating our main result and giving ideas of the proof.

April 25: Afrouz Jabal, Marek Skarupski (TU/e)
Research Introduction

During this seminar, two postdocs within our cluster will introduce themselves and their research.

April 4: Oliver Tse (TU/e)
Optimization with Interacting Particles

We discuss recent developments in the use of interacting particles for solving high-dimensional optimization problems, and provide insights into analytical guarantees for convergence in the particle mean-field limit.

March 21: M. Rosário Oliveira (Universidade de Lisboa)
Interval Principal Component Analysis: What if our data are intervals?

Symbolic Data Analysis gives a new way of thinking in Data Science by extending the standard variables to take into consideration new kinds of data, called “symbolic”, as they cannot be reduced to numbers without losing much information. Interval data are a prime example of symbolic data. There have been a series of proposed adaptations of the Principal Component Analysis method for interval-valued symbolic data, all of which have the downside of having intermediate steps that deal with conventional data. In this talk, we use algebraic structures on the intervals, to define symbolic principal components as linear combinations of the intervals that maximise the symbolic variance. This framework provides the mathematical tools needed to use the symbolic principal components to transform the original data in a way that is mathematically coherent with the remainder of the framework and defines the principal components as solutions to maximisation problems, like what is done in conventional Principal Component Analysis. As in the conventional case, our formulation of interval-based principal component analysis can be seen as a dimensionality reduction method, since we explicitly project the original symbolic observations on the reduced space spanned by the first principal components. We conclude by exploring real-world data from the telecommunications sector, in an attempt to detect Internet redirection attacks in real time. Joint work with Rodrigo Serrão Girão and Lina Oliveira

February 28: Johan Segers (ISBA)
Modelling multivariate extreme value distributions via Markov trees

Multivariate extreme value distributions are a common choice for modelling multivariate extremes. In high dimensions, however, the construction of flexible and parsimonious models is challenging. We propose to combine bivariate extreme value distributions into a Markov random field with respect to a tree. Although in general not an extreme value distribution itself, this Markov tree is attracted by a multivariate extreme value distribution. The latter serves as a tree-based approximation to an unknown extreme value distribution with the given bivariate distributions as margins. Given data, we learn an appropriate tree structure by Prim’s algorithm with estimated pairwise upper tail dependence coefficients or Kendall’s tau values as edge weights. The distributions of pairs of connected variables can be fitted in various ways. The resulting tree-structured extreme value distribution allows for inference on rare event probabilities, as illustrated on river discharge data from the upper Danube basin. Based on joint work with Shuang Hu and Zuoxiang Peng.

February 7: Benoît Corsini, Ralihe Villagran, Yaron Yeger (TU/e)
Research introduction

During this seminar, three postdocs within our cluster will introduce themselves and their research.

Past talks (2015-2022)


Dec 6 Luca Avena (LEI)
Nov 22 Peter Grunwald (CWI/LEI)
Nov 1 Sjoerd Dirksen (UU)
Oct 11 Debankur Mukherjee (GT)
Sep 27 Pieter Kleer (TiSEM)
Sep 13 Rik Versendaal (UU)
Jun 14 Alex Mey, Martin Frohn (TU/e)
May 31 Dirk Fahland (TU/e)
May 17 Rik Versendaal (UU)
Apr 26 Karl Rohe (UW Madison)
Feb 22 Adam Zsolt Wagner (Tel Aviv University)


Dec 21 Botond Szabo (Bocconi University)
Nov 9 Matthias Mnich (TUHH)
Oct 19 Noella Müller (TU Eindhoven)
Sep 14 Matteo D’Achille  (Université Paris-Est Créteil)
Jun 29 Tim van Erven (UvA
Jun 15 Alessandra Cipriani    (TUDelft)
Jun 1 Ahmad Abdi
May 18 Shaoji Tang
May 4 Matthieu Jonckheere
Apr 13 Oxana Zaal
Apr 13 Christopher Hojny   (TU Eindhoven)
Apr 6 Alessandra Cipriani (TU Delft)
Mar 23 Christian Brownlees   (UPF)
Mar 9 Tim Oosterwijk   (UM)
Feb 23 Miklos Racz   (Princeton University)
Feb 9 Christian Hirsch  (University of Groningen)
Jan  26 Piotr Zwiernik   (UPF)


Dec 8 Guillem Perarnau    (UPC)
Nov 24 Alessandro Zocca    (VU)
Nov 10 Jaap Storm (TUe)
Nov 10 Suman Chakraborty (TUe)
Oct 27 Bart Smeulders    (TUe)
Oct 27 Kathrin Möllenhoff
Oct 13 Wouter de Vries (KPN)
Sep 29 Laura Sanità
Sep 15 Zsolt Bartha
Sep 15 Elisa Perrone

March 2020: the STO-seminar programme has been discontinued due to the Covid-19 pandemic.

Feb 26 Rob van der Mei (CWI – VU)
Feb 4 Jim Portegies (TU Eindhoven)
Jan 16 Seva Shneer (Heriot-Watt University)


Dec 16 Gianmarco Bet (University of Florence)
Weighted Dyck paths for non stationary queues
Dec 3 Kay Bogerd (TU Eindhoven)
Detecting small communities in inhomogeneous random graphs
Nov 28 Johannes Schmidt-Hieber (UTwente)
Towards a statistical foundation of deep learning
Nov 12 Tim Hulsof (TU Eindhoven)
Oct 24 Joost Jorritsma (TU Eindhoven)
Typical weighted distance in preferential attachment models – Interpolating small and mini worlds
Oct 8 Albert Senén Cerdà ; Pim van der Hoorn; Martin Zubeldia (TU Eindhoven)
New colleagues introducing themselves and their research
Sep 18 Corli van Zyl (North-West University, Potchefstroom, South Africa)
Signed sequential rank cumulative sum charts
Sep 12 Richard Post (Eindhoven University of Technology)
Complex nanomaterials: a stochastic view
Feb 8 Siva Athreya (Indian Statistical Institute)
Respondent Driven Sampling and Random Graph Convergence
Jan 24 Sam Thomas (Cambridge)
Cutoff for Random Walk on Dynamical Erdos-Renyi
Jan 17 Jeannette Janssen (Dalhousie University)
Recognizing graphs formed by a spatial random process


Dec 12 Ziv Scully (Carnegie Mellon University)
SOAP: One Clean Analysis of All Age-Based Scheduling Policies
Dec 11 Stefan Klootwijk (University of Twente)
On Random Shortest Path Metrics
Oct 5 Andreas Kyprianou (University of Bath)
Some strange results in fragmentation-coalescence models
Oct 5 Joris Mulder (Tilburg University)
The Matrix-F Prior for Estimating and Testing Covariance Matrices
Aug 27 Nicolas Broutin (Sorbonne Université)
Fragmentations and tree-like fractals: a functional fixed-point approach
Aug 27 David Goldberg (Cornell University)
Beating the curse of dimensionality in options pricing and optimal stopping
Aug 27 Lutz Warnke (Georgia Institute of Technology)
A dynamic view on the probabilistic method: random graph processes
Aug 10 Yoshiaki Inoue (Osaka University, Dept. of Information and Communications Technology)
Sample-Path Analysis of the Age of Information (AoI) and Its Applications to FCFS Single-Server Queues
June 8 Santiago Duran (CNRS, LAAS & Universite de Toulouse)
Asymptotic Optimal Control of Markov-Modulated Restless Bandits
June 5 Ambedkar Dukkipati (Indian Institute of Science)
Spectral graph algorithms for community detection in networks: Statistical Analysis and Consistency
May 24 Adelle Coster (UNSW Sydney)
Mathematical Modelling of Insulin Regulation in Glucose Transport
May 23 Botond Szabo (Universiteit Leiden)
Bayesian nonparametric approach to log-concave density estimation
May 15 Chang-Han Rhee (CWI)
On Heavy-Tailed Rare-Event Analysis
May 8 Yutaka Sakuma (National Defense Academy)
An arrival distribution for the equilibrium expected waiting time in a discrete-time single-server queue with acceptance period and Poisson population of customers
Apr 25 Zhuozhao Zhan (Eindhoven University of Technology)
Optimal Unidirectional Switch Design
Apr 24 Frits Spieksma (Eindhoven University of Technology)
Robust Balanced Optimization Problems
Apr 4 Eyal Castiel (Toulouse Mathematical Institute (IMT) and ISAE)
Queuing Networks and separation of time scales using Log-Sobolev inequality
Mar 28 Liudmila Prokhorenkova (Yandex)
Community detection through likelihood optimization: in search of a sound model
Mar 21 Céline Comte (Nokia Bell Labs France and Telecom ParisTech)
Performance of Balanced Fairness in Resource Pools: A Recursive Approach
Feb 1 Benny van Houdt (Universiteit Antwerpen)
On the Response Time Distribution of a Class of Limited Processor Sharing Queues
Feb 1 Nicolas Gast (INRIA & University of Grenoble Alpes)
A Refined Mean Field Approximation


Dec 6 Nelly Litvak (University of Twente, TU/e)
Who needs mathematics: talking maths to a general public
Oct 11 Hermann Þórisson (University of Iceland)
Palm Versions and Extra Heads
June 21 Jan Nagel (TU/e)
The speed of biased random walk among random conductances
Jun 1 Ron Kenett (University of Turin)
On the Performance of Sequential Procedures for Detecting a Change, and Information Quality (InfoQ)
May 18 Galit Yom-Tov (Technion – Israel Institute of Technology)
An Invitation Control Policy for Proactive Service Systems: Balancing Efficiency, Value and Service Level
Feb 15 Paulo Serra (TU/e)
Dimension Estimation using Random Connection Models


Nov 30 Rob van den Berg (VU Amsterdam)
Near-critical and frozen percolation
Oct 18 Rob J Hyndman (Monash University, Australia)
Forecasting large collections of related time series
Sept 28 Tim Hulshof (TU/e)
Higher order corrections for anisotropic bootstrap percolation
Sept 13 Gábor Lugosi (Universitat Pompeu Fabra)
How to estimate the mean of a random variable?
Sept 13 Robert Nowak (University of Wisconsin – Madison)
How to estimate the mean of a random variable?
June 21 Alessandro Di Bucchianico (TU/e)
Developments in Monitoring Dynamic Data
June 15 Alexandre Mauroy (Luxembourg Centre for Systems Biomedicine)
An operator-theoretic approach to network identification
May 11 Nikhil Bansal (TU/e)
On the Komlos Conjecture, or, how to Control your Brownian Motion
Feb 23 Edwin van den Heuvel (TU/e)
Randomized Controlled Trials: The Stepped Wedge Design
Feb 10 Christian Borgs (Microsoft Research New England)
Graphon processes as a new model for large, sparse graphs
Jan 26 Miklós Telek Technical University of Budapest
Markovian point, terminating and branching processes
Jan 20 Joachim Arts TU/e, IE&IS, OPAC group
Repairable Stocking and Expediting in a Fluctuating Demand Environment: Optimal Policy and Heuristics


Dec 16 Sándor Kolumbán (Technical University Eindhoven)
Data perturbation methods for hypothesis testing in nonlinear estimation problems
Nov 24 Jan Ramon (INRIA-Lille and KU Leuven)
Learning evolutionary models from a snapshot
Oct 14 Luca Avena (Leiden University)
Random walks in Markovian environments: a perturbative approach
June 10 Jan-Pieter Dorsman (Leiden University)
Analysis of fibre-loop optical buffers with a void-avoiding schedule
May 26 Phil Whiting (Macquarie University)
Compute and Forward for Wireless Networks – Scheduling and Capacity in Heterogenous Networks
May 6 Botond Szabó (CWI and Budapest University of Technology and Economics)
Adaptive horseshoe estimation
Apr 29 Balázs Ráth (Budapest University of Technology and Economics)
Multiplicative coalescent with linear deletion: a rigid representation
Apr 22 Elena Pulvirenti (Leiden)
Metastability for the Widom-Rowlinson model
Mar 18
Rui Castro (TU/e)
On adaptive sensing for inference of structured sparse signals
Mar 11 Carlo Lancia (University of Rome TorVergata)
Parallel TASEP on a ring: blockage problem and non-analyticity of the current
Mar 4 Daniel Valesin (Groningen)
Percolation on the stationary distribution of the voter model on Z^d
Feb 25 Stella Kapodistria (TU/e)
Scheduling preventive maintenance on a wind turbine based on quantitative data
Feb 3 Martin Roth (KNMI and TU/e)
Analysis of trends in extreme rainfall: A regional approach
Feb 3 Murtuza Ali Abidini (TU/e)
Performance Analysis in Optical Networks
Jan 27 Laurens Smit (Leiden University)
Explicit Solutions, Properties and Applications of DES and RES Markov processes
Jan 10 Tobias Muller (Utrecht University)
A hyperbolic model for complex networks
Jan 6 Robert Fitzner (Stockholm Universiteit)
Using Super-Resolution Microscopy to Probe Exchange Pathways (a joint venture of chemistry and mathematics)



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