08. August: Went to San Francisco and launched our API platform for data scientists.
07. July: Raised a pre-seed round from EF and Transpose Platforms VC together with my co-founder Jeremy.
04. April: Was accepted at the Entrepreneur First Paris spring cohort as a founder-in-residence. A special thanks to Clémence and Joachim for their support.
03. March: Successfully defended my Ph.D. Thesis!
01. January: Our paper "A Data-Driven Measure of Relative Uncertainty for Misclassification Detection" was accepted to appear at the ICLR2024 conference in Vienna, Austria. A huge thanks to my great co-authors Marco, Georg, and Pablo for their fantastic work!
2023
12. December: Presented at the NeurIPS 2023 Conference Workshop on Mathematics of Modern Machine Learning.
10. October: Our short paper entitled "A Data-Driven Measure of Relative Uncertainty for Misclassification Detection" was accepted to appear at the NeurIPS 2023 Conference Workshop on Mathematics of Modern Machine Learning.
07. July: Served as a reviewer for the NeurIPS 2023 Conference.
06. June: Attended the 2023 edition of the Nordic Probabilistic AI School (ProbAI), hosted by the Norwegian University of Science and Technology (NTNU) and sponsored by DeepMind.
05. May: Released, together with colleagues, Detectors: an open-source library for out-of-distribution detection in computer vision applications.
01. January: Released, along with colleagues, Todd: an open-source library for text out-of-distribution detection built on top of the Huggingface Transformers library. Big shoutout to Maxime for his amazing work!
2022
12. December:
Presented at the NeurIPS 2022 Conference in New Orleans, LA, USA.
Served as a reviewer for the CVPR 2023 Conference.
10. October: I started a graduate research internship with Mila in the ILLS team.
09. September: The work titled “Beyond Mahalanobis Distance for Textual OOD Detection” was accepted to appear at the NeurIPS 2022 Conference. Many thanks to Pierre and his great work!
06. June: I was awarded the MITACS Globalink scholarship for a four-month research internship in partnership with MILA and ÉTS in Montreal, QC, Canada, in uncertainty estimation for medical imaging segmentation.
04. April: Presented at the ICLR 2022 Conference.
01. January: The work entitled “IGEOOD: An Information Geometry Approach to Out-of-Distribution Detection” was accepted to appear at the ICLR 2022 Conference!
2021
12. December: Presented virtually at the NeurIPS 2021 workshop track.
10. October: The condensed version of the work “IGEOOD: An Information Geometry Approach to Out-of-Distribution Detection” was accepted to appear at the NeurIPS 2021 DistShift Workshop.
08. August: The work titled “CSI-Aided Robust Neural-Based Decoders” was accepted to appear at the 11th International Symposium on Topics in Coding (ISTC).
05. May: Served as a reviewer for the NeurIPS 2021 Conference.
2020
12. December: Took on the role of teaching assistant for the course “Introduction to Deep Learning” at CentraleSupélec.
10. November: Started my Ph.D. in Machine Learning at CentraleSupélec!
2018
08. August: I was awarded an excellence scholarship to pursue my master's degree at ISAE-SUPAERO in Toulouse, France. There, I was selected for the Data Science and Applied Mathematics major.