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Antoine Aspeel


Antoine Aspeel received his Engineering Master’s degree in Applied Mathematics from Université catholique de Louvain in 2017.

His interest domains are machine learning, graph theory, medical imaging and proton therapy.

He is currently doing a PhD thesis under the supervision of Benoît Macq. His research is about online tumor tracking during treatment by proton therapy. It includes the characterisation of the tumor motion, the design of algorithms for fast tumor contouring and motion prediction.




Aspeel, Antoine. Optimal sampling for state estimation of stochastic dynamical systems - Thèse (Dissertation)


Duterme, Tom ; Thomas, Quentin ; Aspeel, Antoine. The development of Model Risk Management: a Luhmannian perspective in 1st MUSEES Conference Modeling Uncertainty in Social, Economic, and Environmental Sciences, EMLyon Business School, du 16/03/2022 au 18/03/2022



Aspeel, Antoine. Optimal Control for Linear Networked Control Systems with Information Transmission Constraints in 60th IEEE Conference on Decision and Control (CDC)60th IEEE Conference on Decision and Control (CDC), Austin, Texas, du 14/12/2021 au 17/12/2021


Aspeel, Antoine ; Legay, Axel ; Jungers, Raphaël M. ; Macq, Benoit. Optimal measurement budget allocation for Kalman prediction over a finite time horizon by genetic algorithms in EURASIP Journal on Advances in Signal Processing



Aspeel, Antoine ; Gouverneur, A. ; Jungers, Raphaël M. ; Macq, Benoît. Optimal Measurement Budget Allocation For Particle Filtering in IEEE International Conference on Image Processing, Abu Dhabi (United Arab Emirates), du 25/10/2020 au 28/10/2020



Aspeel, Antoine ; Legay, Axel ; Macq, Benoît. Genetic Algorithms for optimal intermittent measurements for tumor tracking


Aspeel, Antoine ; Dasnoy-Sumell, Damien ; Jungers, Raphaël M. ; Macq, Benoît. Optimal intermittent measurements for tumor tracking in X-ray guided radiotherapy. in SPIE Medical Imaging conference, San Diego, US, du 16/02/2019 au 21/02/2019



Aspeel, Antoine ; Delvenne, Jean-Charles. Community detection in large-scale time-varying networks : a modularity based approach - Mémoire (Thesis)