I am a PhD student at Ghent University, more precisely at the Foundations Lab for Imprecise Probabilities (FLip) of the Department of Electronics and Information Systems, part of the Faculty of Engineering and Architecture. Before October 2017, I was a member of the SMACS Research Group, part of the Department of Telecommunications and Information Processing, for two years. From November 2019 until January 2020, I was on a three month long research stay at the UNIMODE research group of the University of Oviedo, Spain.
My research is focussed around the theory and applications of imprecise probabilities.
I first became acquainted with imprecise probabilities during my Master thesis, in which I used imprecise probabilities to model the noise in a one-dimensional discrete-time linear-quadratic optimal control problem.
On the theoretical side, I am currently working on stochastic processes, mainly (an imprecise extension of) the Poisson process and (ergodicity of) imprecise continuous-time Markov chains.
These stochastic process are used as models in a lot of fields.
From a practical point of view, my main interest lies in using these imprecise stochastic processes to robustly model queueing systems.
If interested, you can scroll down to take a look at my scientific output, brief academic CV or contact details.
Scientific output
Journal articles
- . Bounding inferences for large-scale continuous-time Markov chains: A new approach based on lumping and imprecise Markov chains. In International Journal of Approximate Reasoning, 115:96–133, Dec. 2019.
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Optimal control of a linear system subject to partially specified input noise.
In International Journal of Robust and Nonlinear Control,
29(12):3892–3914,
Aug. 2019.
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- doi: 10.1002/rnc.4583
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Imprecise Markov Models for Scalable and Robust Performance Evaluation of Flexi-Grid Spectrum Allocation Policies.
In IEEE Transactions on Communications,
66(11):5401–5414,
Nov. 2018.
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- code
- doi: 10.1109/TCOMM.2018.2846235
- arXiv: 1801.05700
Articles in conference proceedings
- . A study of the set of probability measures compatible with comparative judgements. In the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2020), Jun. 2020.
- . First steps towards an imprecise Poisson process. In the proceedings of the 11th International Symposium on Imprecise Probability: Theories and Applications (ISIPTA 2019), Jun. 2019.
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An Imprecise Probabilistic Estimator for the Transition Rate Matrix of a Continuous-Time Markov Chain.
In the proceedings of the
9th International Conference on Soft Methods in Probability and Statistics (SMPS 2018),
Sep. 2018.
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- doi: 10.1007/978-3-319-97547-4_17
- arXiv: 1804.01330
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Computing Inferences for Large-Scale Continuous-Time Markov Chains by Combining Lumping with Imprecision.
In the proceedings of the
9th International Conference on Soft Methods in Probability and Statistics (SMPS 2018),
Sep. 2018.
Winner of the International Journal of Approximate Reasoning Best Paper Award.
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- award.pdf
- slides.pdf
- doi: 10.1007/978-3-319-97547-4_11
- arXiv: 1804.01020
- . Imprecise continuous-time Markov chains: Efficient Computational methods with guaranteed error bounds. In the proceedings of the 10th International Symposium on Imprecise Probability: Theories and Applications (ISIPTA'17), Jul. 2017.
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Modelling spectrum assignment in a two-service flexi-grid optical link with imprecise continuous-time Markov chains.
In the proceedings of the
13th International Conference on the Design of Reliable Communication Networks (DRCN 2017),
Mar. 2017.
Winner of the best paper award.
Posters and presentations
- . Extending the domain of Markovian imprecise jump processes. Presented at the International Conference on Uncertainty Quantification & Optimisation (UQOP 2020), 17/11/2020.
- . Imprecise stochastic processes. Invited talk at the University of Oviedo, 11/11/2019.
- . Computing limit expectations of imprecise continuous-time Markov chains. Presented at the 11th Workshop on Principles and Methods of Statistical Inference with Interval Probability (WPMSIIP 2018), 1/8/2018.
- . Lumping continuous-time Markov chains. Presented at the 10th Workshop on Principles and Methods of Statistical Inference with Interval Probability (WUML/WPMSIIP 2017), 12/9/2017.
- . Towards an imprecise Poisson process. Presented at the 10th Workshop on Principles and Methods of Statistical Inference with Interval Probability (WUML/WPMSIIP 2017), 12/9/2017.
- . Handling the state space explosion of Markov chains: How lumping introduces imprecision (almost) inevitably. Presented at the 10th International Symposium on Imprecise Probability: Theories and Applications (ISIPTA'17), 14/7/2017.
- . Modelling spectrum assignment in a two-service flexi-grid optical link with imprecise continuous-time Markov chains. Presented at the 10th International Symposium on Imprecise Probability: Theories and Applications (ISIPTA'17), 10/7/2017.
- . LQ optimal control for partially specified input noise. Presented at the 28th European Conference on Operational Research (EURO2016), 6/7/2016.
- . Optimal control of linear systems with quadratic cost and imprecise forward irrelevant input noise. Presented at the 9th International Symposium on Imprecise Probability: Theories and Applications (ISIPTA'15), 22/7/2015.
Academic CV
Working experience
I am currently pursuing my PhD under the supervision of Jasper De Bock, Gert de Cooman and Herwig Bruneel.
During a 4 week internship I built a model of the KPI of a chemical plant using data mining techniques available in the JMP software package.
Teaching
The aim of this course is to teach the student the basic principles and the reasoning methods of probability. Lecturer: Gert de Cooman