About Me
Welcome to my home page. Here, you can find some information about my professional activities and projects. Please use the tabs above to navigate through the site.
I am a Full Professor on Stochastic Processing Interacting Networks at the University of Twente (UT), an Associate Professor at the Eindhoven University of Technology (TU/e), and a Research Fellow of the European research institute EURANDOM.
My research interests centre on stochastic processes on interacting networks. Typical applications I focus on are energy networks, data centres, and high-tech manufacturing. You can find recent publications and project information in the "Research" and "Projects" tabs above.
Next to my research, I am active in promoting gender diversity in academia through my roles as the representative for the Netherlands to the European Women in Mathematics association and to the Committee for Women in Mathematics of the International Mathematical Union. Additionally, I am a member of the advisory boards of the national associations of women in mathematics in Cyprus and in Greece.
Last, I currently serve at the editorial boards of IISE Transactions, Mathematical Methods of Operations Research, OR Spectrum, and INFOR, and have frequently served on the programme committees for conferences in applied probability and operations research.
Links
Energy group @UT
My research @UT
arXiv
ORCiD
Research Gate
ResearcherID
Scopus
Expertise
Organisations
Ancillary Activities
-
Eindhoven University of Technology
Employed for 0.8 fte -
OR Spectrum (Springer Nature Switzerland AG)
Associate editor -
Mathematical Methods of Operations Research (Springer)
Associate editor -
IISE Transactions (Taylor and Francis Online)
Associate editor -
European Women in Mathematics
National representative of EWM -
VHTO
Volunteer and role model at VHTO -
INFOR: Information Systems and Operational Research
Associate editor INFOR
Research
I focus on the performance of stochastic processing networks with layered architectures with typical application domains on energy networks, data centers, and high-tech manufacturing. In addition, I have worked on perturbation analysis for heavy-tailed risk models, Lévy processes, large deviations for non-monotone stochastic recursions, and proportional fairness in heavy traffic for bandwidth-sharing networks.
Publications
UT Research Information System
Google Scholar Link
Education
I teach courses in probability, stochastic processes, infectious-disease epidemiology, and performance modelling. I regularly supervise BSc, MSc, and PhD theses, internships, and PDEng projects on these topics. Please contact me for more information on available projects.
I have obtained my University Teaching Qualification diploma (UTQ / BKO) in 2010 and I have continued my training in education through various professional development courses. I have served in the departmental Didactics committee and UTQ committee. I have obtained several grants on research in mathematics education. Find information on my latest project here.
Affiliated Study Programmes
Bachelor
Master
Courses Academic Year 2022/2023
Courses Academic Year 2021/2022
Current Projects
-
AI for Energy Grids
The project focuses on developing a decentralized control framework for controlling assets on the distribution grid. Due to the increase of decentralized electricity production and rapid electrification, the distribution grid is becoming ever more unpredictable and overloaded. Simultaneously, the number of controllable assets on the distribution grid is increasing which provides the opportunity to optimize distribution grid operation. However, optimizing operation of all assets is difficult due to scalability, privacy concerns, and infrastructure considerations. The goal of this project is to maintain and improve operation of the distribution grid, by developing a framework for controlling smart assets in real time and in a decentralized way, to optimize grid operation while being scalable and safe while considering privacy, infrastructure, legality, and fairness. This research involves machine learning, decentralized control, reinforcement learning, and optimization. This project is part of the ICAI lab “AI for Energy Grids” in the LTP ROBUST programme.
-
Layered stochastic networks with limited resources
This project studies a class of mathematical models that are important in the performance analysis of networks, such as communication, computer, and energy systems. Specifically, the project focuses on the analysis of systems with multiple interacting layers that share limited resources, where the degree of resource sharing is limited by necessity (e.g. a buffer) or by choice (e.g. to guarantee a minimal performance level). These systems are mathematically very challenging, with few known results and insights. We focus on asymptotic and algorithmic techniques for networks where all active servers share a common single resource in a limited processor sharing fashion. We incorporate user impatience and general service times. We prove fluid and diffusion limit theorems of stochastic multi-node networks with multiple interacting layers by using Markov, renewal, and measure-valued processes. On a high level, the methods that we use and develop are from the areas of queueing theory, probability theory, optimization theory, and power systems engineering.
-
Stochastic processes driven by non-convex resource allocation problems
The project focuses on stochastic processes of which the dynamics are driven by resource allocation problems related to non-convex optimisation problems. These processes naturally occur as multi-scale models that describe congestion in man-made systems such as energy and communication networks. Being Markov processes on infinite-dimensional state spaces, their analysis is mathematically challenging and current techniques insufficient: Linear approximations of the driving resource allocation problem can lead to a poor understanding of such systems and to suboptimal designs, especially under critical loading. We develop mathematical results in the context of electric vehicle charging, analysing their fluid models and applying them to derive control rules that handle congestion in electricity networks efficiently.
-
Extreme-Value Theory for Large Fork-Join Queues
The project is inspired by modeling delays in supply chains for high-tech manufacturers, such as ASML, Philips Healthcare, and Boeing. These supply chains are very large compared to the typical supply chain in industry. A common property is that many high-tech suppliers specialize in producing and delivering a specific component of the final product. In this system, the slowest supplier determines the delay of the manufacturer. To model this delay, we consider the N-server fork-join queueing network, in which each server represents a unique supplier, and the arrival stream denotes orders from the manufacturer. We investigate the behavior of the longest queue and the longest waiting time by proving limiting results as the number of servers N converges to infinity. We additionally propose centralized base-stock and capacity policies to minimize costs incurred by delays. To achieve these objectives, we use results from extreme-value theory, diffusion approximations, large deviations principles, theory on heavy-tailed random variables, and newsvendor problems.
In the press
- Matematicas en el mundo (in Spanish)
- UPS Smith Prize Winner Reprise
- Feestelijke prijsuitreiking voor gelauwerde wiskundemaster
- We are taking decisions based on bad numbers
- Faces of Women in Mathematics
- Why the amount of queuing time depends on mathematics
- Students gain most from maths-interests balance
- Een snelle knipbeurt of de schoonheid van een vergelijking
News on utwente.nl
Tweets
Contact Details
Visiting Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
(building no. 11)
Hallenweg 19
7522NH Enschede
The Netherlands
Mailing Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
P.O. Box 217
7500 AE Enschede
The Netherlands