About Me
I’m currently a Research Engineer at ONERA in Paris. As such, I work on R&D projects aiming at processing electromagnetic sensors data. I’m a permanent member of the advanced signal processing unit.
Before that I was a Data Scientist working on computational pathology at Aignostics in Berlin. As such, I mostly developed machine learning models and pipelines to run segmentation and classification on whole slide images depicting human tissue with immune cells and cancer.
Before that I was a PhD student in machine learning at Mines Paris (part of PSL University) and Thales. This research was financed by a Cifre-Défense grant.
Research Interest
My current work applies machine learning to images, signals, and time series associated with electromagnetic sensors.
I’m interested in anomaly detection, also called out-of-distribution detection or one-class classification, and representation learning for signal, time series and image processing.
Publications & abstracts
A novel, scalable deep learning-based approach to automated quality control of multipleximmunofluorescence images
2024 SITC poster (abstract 1283)
Thesis defense 18/01/2023
Near OOD detection for low-resolution radar micro-Doppler signatures
2022 ECML PKDD (previous URL leads to the expanded version on arXiv)
Paper experiments code
Dataset generation code
Deep random projection outlyingness for unsupervised anomaly detection
2021 ICML UDL Workshop (under review for publication)
From unsupervised to semi-supervised anomaly detection methods for HRRP targets
2020 IEEE Radar Conference (RadarConf20)
Teaching
Teaching assistant for the data science course of Mines Paris engineering program - 2nd semester of 2021-2022.
Teaching assistant for the deep learning for image analysis course of Mines Paris engineering program and IASD master program - fall 2021 and winter 2021-2022.
Teaching assistant for the probability course of Mines Paris engineering program - 1st semester of 2020-2021.
Misc
I talked about anomaly detection at a Franco-German University workshop on mathematical image processing in May 2022 in Kaiserslautern.
I contributed to the review of a paper for the ECML PKDD 2022 conference.
I co-supervised a master degree intern working on multivariate time series discrimination at Thales during the spring and summer of 2021.
I participated in the ICLR Computational Geometry & Topology Challenge 2021, which resulted in a white paper.
I talked about anomaly detection to IASD master program students as part of the deep learning for image analysis course during the winter 2020 edition.
I contributed to the review of a paper for the RADAR 2019 conference.