About
I am currently a part-time Research Assistant in the IntellEcT Systems group at the UCL AI Centre with Dr. Jagmohan Chauhan, also I am doing a research internship at Vectify AI. Upon the internship, I will join the Generic Technology Research Group, Deep Learning Theory Team at RIKEN-AIP as a Research Associate (2025-2026), under the supervision of Prof. Taiji Suzuki. My role will focus on improving diffusion models through a density ratio–based approach.
Education
I completed my Bachelor’s degree in Mathematics with Statistics, graduating with First Class Honours, at the University of Bristol (2021–2024). I completed my Master’s degree in Computational Statistics and Machine Learning (CSML) at University College London (UCL) (2024–2025). My Master’s thesis project is supervised by Prof. David Barber and Dr. Mingtian Zhang at the UCL AI Centre.
I also work closely with Prof. Song Liu in my spare time.
Publications & Works in Progress
- Leyang Wang*, Mingtian Zhang*, Zijing Ou, David Barber. VarDiU: A Variational Diffusive Upper Bound for One-Step Diffusion Distillation — NeurIPS 2025 Workshop on Structured Probabilistic Inference & Generative Modeling
- Daniel J. Williams*, Leyang Wang*, Qizhen Ying, Song Liu, Mladen Kolar. High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching — AISTATS 2025
- Song Liu, Leyang Wang, Yakun Wang. Guiding Time-Varying Generative Models with Natural Gradients on Exponential Family Manifold — UAI 2025 & ICLR Deep Generative Model in Machine Learning: Theory, Principle and Efficacy Workshop Outstanding Long Paper Award
- Jiahao Yu, Qizhen Ying, Leyang Wang, Ziyue Jiang, Song Liu. Missing Data Imputation by Reducing Mutual Information with Rectified Flows — NeurIPS 2025
* Equal contribution
The first project was conducted during my master’s thesis project while the second and forth projects were (partially) carried out during my undergraduate summer bursary placement at the University of Bristol School of Mathematics, funded by the Heilbronn Institute for Mathematical Research.
Awards, Scholarships & Bursaries
- Conference on Uncertainty in Artificial Intelligence (UAI) Scholarship — 2025
- ICLR DeLTa Workshop Outstanding Long Paper Award — 2025
- Summer Research Bursary, School of Mathematics, University of Bristol — 2024
My research interests lie in statistical machine learning, with a focus on deep generative models and their applications to computer vision. I am particularly interested in developing principled methods for solving high-dimensional machine learning problems through statistical discrepancies minimisation.
Research Interests
- Probabilistic Modelling
- Statistical Discrepancy Minimisation
- Density Estimation