CV

I am a Ph.D. candidate in applied mathematics at EDMH, Université Paris-Saclay. I am based in the Statistics group at LaMME. My doctoral research is supervised by Juhyun Park and Nicolas Brunel. It is supported by DeMythif.AI, a Marie Skłodowska-Curie Actions COFUND programme associated with DataIA.

My research centres on conformal prediction and uncertainty quantification when data are missing. I am also exploring tabular foundation models as part of my doctoral work, alongside interests in robust uncertainty quantification and diffusion models.

Before starting my doctorate in 2024, I completed the M2 Probabilités et Finance (Ex-DEA El Karoui) at Sorbonne University and École Polytechnique. Earlier, I studied mathematics and applied mathematics at Beihang University, followed by engineering studies at École Centrale de Lyon and a double master's programme in industrial engineering and French general engineering at Beihang (Master's thesis).

From 2020 to 2023, I worked as a data scientist in the AI Lab at China Merchants Bank. My earlier experience includes internships in the Machine Learning Group at Microsoft Research Asia and in R&D at Baidu. I also worked on supervised learning with label noise at the Sino-French Data Science Lab, indoor temperature prediction and fuel recognition with EDF China, and ChatOps with Schlumberger Beijing.

My teaching has included Statistics at ENSIIE and Python for Data Analysis at Beihang University.

I also co-organise the LaMME PhD students seminar and serve as a reviewer for NeurIPS 2026.

I have also shared my work through academic presentations; a selection is on my presentations page.