CV

I am a Ph.D. candidate in applied mathematics at Université Paris-Saclay, enrolled in the Hadamard Doctoral School of Mathematics (EDMH). I am based in the Statistics group at LaMME. My research is supervised by Juhyun Park and Nicolas Brunel. My Ph.D. 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 beginning my Ph.D. 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 dual master's programme in industrial engineering and general engineering at École Centrale de Pékin (Beihang University) (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.

I have been a teaching assistant for 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.