Axel Faes
Postdoctoral Researcher
- Data Scientist
- Computational Neuroscientist
- Computer Engineer
Work & Research Experience
Postdoctoral Researcher: Scientific Coordinator and Artificial Intelligence
UHasselt
January 2024 - Current
- Scientific Coordinator of the Flanders AI Research program, Use Case Real World Evidence.
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Technical Machine Learning lead of the Biomedical Data Sciences Group, UHasselt
Postdoctoral Researcher: Brain-Computer Interfacing and Machine Learning
KU Leuven
May 2023 - January 2024
- Project: "Sign Language Alphabet decoding from intracranial brain activity"
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Group: Prof. Marc van Hulle, Computational Neuroscience, Laboratory for Neuro-and Psychophysiology, KU Leuven
Data Science Consultant
Flanders BCI
2022 - 2024
- Provided consulancy for physical experiments using Synamps RT and Neuvo EEG Systems.
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Supported the data analysis for hybrid BCI with new analytical EEG modeling techniques & signal detection- and classification algorithms.
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Infer emotion from EEG signals using machine learning techniques.
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Usage of ECoG signals from semi-invasive recording for imagined movement detection and language processing.
Research Stay Idrogenet Srl, Gloreha: Robotic Rehabilitation
Lumezzane, Italy
Dec. 2022 - Jan. 2023
- Develop custom software for the control of the Gloreha robotic rehabilitation device,
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Specifically the R-TOUCH PRO Sinfonia, a custom-built robotic exoskeleton for hand rehabilitation.
PhD Researcher in Computational Neuroscience
KU Leuven
Sep. 2018 - May 2023
- Cognitive and Molecular Neuroscience
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PhD Thesis: Finger Movement Decoding: From Source-Localisation to Tensor Regression Modelling
Web Performance Research Internship
UHasselt
Jul. 2016 - Sep. 2016
- I worked on the iMinds PRO-FLOW project @ Expertise centre for Digital Media (EDM)
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focus on the difference between the http versions (http1.1, https, http2).
Summer Research Internship Physical Computing
UHasselt
Aug. 2015 - Sep. 2015
- Interfacing between human entity, a drone and virtual objects @ Expertise centre for Digital Media (EDM).
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(C++, Optitrack motion capture, custom built drone)
Teaching & Academic Activities
BKO (Basis Kwalificatie Onderwijs) traject - Onderwijsprofessionalisering
UHasselt
2025
Advanced Topics in Data Science (4569 & 4585) Lecturer Federted Learning (lid onderwijsteam)
UHasselt
June 2024 - Sept. 2025
Bio-informatica (3740) Co-lecturer (co-titularis)
UHasselt
June 2024 - Sept. 2025
Guest Associate Editor Use of Big Data and Artificial Intelligence in Multiple Sclerosis
Frontiers in Immunology
2024 - 2025
Student Research Competition Judge (International Conference on Functional Programming)
ICFP
2024
Brain-Computer Interfacing (B-KUL-H08M0A) Guest Lecturer
KU Leuven
2022-2025
Educational background
Flemish Sign Language course
Flemish Sign Language Centre (Vlaams Gebarentaal Centrum)
Sep. 2022 - May 2024
- Graduates are able to engage in day-to-day conversations with deaf and hard-of-hearing individuals.
Doctoral Programme in Biomedical Science (PhD) in Computational Neuroscience
KU Leuven
Sep. 2018 - May 2023
- Cognitive and Molecular Neuroscience
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PhD Thesis: Finger Movement Decoding: From Source-Localisation to Tensor Regression Modelling
Advanced Master of Science in Engineering (M.Sc.) in Artificial Intelligence
KU Leuven
Sep. 2017 - Jul. 2019
- Engineering and Computer Science (76% - Cum Laude)
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Thesis: An Information Theoretical Approach to EEG Source-Reconstructed Connectivity (on Github)
Honoursprogramme of the Faculty of Engineering Science (Research Track)
KU Leuven
Sep. 2016 - Oct. 2018
- Research Assistant: design of type-&-effect system for Eff based on row polymorphism
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Research Assistent: efficient compilation of algebraic effect handlers (in Eff)
Master of Science in Engineering (M.Sc.) in Computer Science (Burgelijk Ingenieur - ir.)
KU Leuven
Sep. 2016 - Sep. 2018
- Artificial Intelligence & Theoretical Computer Science (76% - Cum Laude)
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Thesis: Algebraic Subtyping for Algebraic Effects and Handlers (on Github)
Business Summer School: United in Manchester (0739)
The University of Manchester
Jul. 2015 - Aug. 2015
Bachelor of Science (B.Sc.) in Computer Science
UHasselt
Sep. 2013 - Jul. 2016
- Physics and General courses (79% - Magna Cum Laude)
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Thesis: Machine learning techniques for flow-based network intrusion detection systems (on Github)
Publications
Papers in Preparation
[1] |
Axel Faes
Liesbet Peeters
Marc Van Hulle
"Federated Transfer Learning for intracranial motor brain-computer interfaces"
|
[2] |
Axel Faes
Liesbet Peeters
"Block-Term Tensor Regression as an autoencoder "
|
[3] |
Axel Faes
Liesbet Peeters
"Federated Block-Term Tensor Regression for Heart Diseases in Realistic Healthcare Settings"
Spotlight
|
[4] |
Ashkan Pirmani
Edward De Brouwer
Adam Arany
Martijn Oldenhof
Antoine Passemiers
Axel Faes
Tomas Kalincik
et al.
"Personalized Federated Learning for Predicting Disability Progression in Multiple Sclerosis Using Real-World Routine Clinical Data"
Submitted to npj Digital Medicine (15.357 IF) (Under review)
|
[5] |
Valentina Pergher*
Axel Faes*
Yide Li
Marc M. Van Hulle
(* equal contribution)
"How stimulus type and task structure can affect ERP signatures"
Submitted to Frontiers in Psychology, section Cognition (2.6 IF) (Under review)
|
[6] |
Axel Faes
Eva Calvo Merino
Anais Van Hoylandt
Elina Keirse
Tom Theys
Marc M. Van Hulle
"Finger abduction trajectory prediction from high-density ECoG"
Submitted to Journal of Neural Engineering (5.4 IF) (Under review)
|
[7] |
Axel Faes
Mariana P. Branco
Anais Van Hoylandt
Elina Keirse
Tom Theys
Nick F. Ramsey
Marc M. Van Hulle
"Decoding Sign Language Finger Movements from high-density ECoG using Graph-Optimized Block Term Tensor Regression"
Submitted to Journal of Neural Engineering (5.4 IF) (Under review)
|
International Journal Papers
Conference Papers
Other publication
Thesis
Posters
Extended Abstracts
Supervised students, talks and other media
Students
[1] |
"Matteo Ramina"
Estimating Household Wealth in Guyana - Remote Sensing and Convolutional Neural Network Approach
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[2] |
"Mohsen Soleimanisemsani"
AI for time series imputation
|
[3] |
"Meseret Assefa Kerga"
Predicting Cirrhosis Patient Survival Using Machine Learning - A Data-Driven Approach
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[4] |
"Dongho Chun"
(Federated) Machine Learning for Health Data
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[5] |
"Dries Cornelissen"
Federated Learning for Regression modelling with Cardiovascular Health Data
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[6] |
"Ward Ceyssens"
Brain-Computer Interfacing - population-based finger movement decoding
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[7] |
"Qiang Sun"
Hand exoskeleton dexterity achieved by shared control with a semi-invasive brain-computer interface
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[8] |
"Eva Calvo Merino"
Restoring finger dexterity with an exoskeleton controlled by human intracranial recordings
|
[9] |
"Aurélie de Borman"
Investigating the effect of Source Mixing on Directed Connectivity estimated between Simulated Reconstructed EEG Sources
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[10] |
"Diogo Sousa Morais"
Estimating the effectiveness of source localized EEG for BCIs
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[11] |
"Guilherme de Borras Silva"
Cluster Permutation Analysis of N-Back related EEG-ERP Data
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[12] |
"Iris Vantieghem"
Using Neural Networks to derive Directed Connectivity between Reconstructed EEG Sources
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[13] |
"Didier Quintius"
Neural Network Approach to the Inverse Problem
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Talks, presentations and other media