Advancing fundamental AI research in a lost paradise.
The Probabilistic Machine Learning (PML) group, part of the Dept. of computing science at the University of Aberdeen, was founded by Dr. Yongchao Huang in Aug. 2023.
We are the first dedicated group of this kind at Aberdeen, focusing on fundamental research at the intersection of applied probability, computational statistics, and modern machine learning.
In the era of generative AI, our expertise in probabilistic, statistical and mathematical methods, along with industry experiences, uniquely position us to contribute to both theoretical understanding and practical applications of AI.
The inaugural probabilistic ML research group at the University of Aberdeen, establishing a new center of excellence.
Combined experience spanning Bayesian methods, sampling algorithms, and probabilistic programming since 2015/2016.
The group currently hosts 3 PhDs and 2 MRes students, building & expanding a vibrant research community.
Methodological innovations to machine learning through Bayesian inference, MCMC, variational inference, flows, GPs, physical and diffusion processes.
Physics, mechanics and dynamics of learning, dynamical systems, numerical methods, and computing.
Applying PML to real-world challenges in languages (e.g. SLM, uncertainties), vision, automation, and scientific computing.
Lecturer in Computing Science. Founder of the PML group & CPL Lab
Specializing in sampling and inference methods (MCMC, particle methods), Bayesian methods, computational and physical learning (CPL) approaches.
AICS @ AAAI 2026
NeurIPS 2017 & 2020, ICML 2021, ICRA 2025
We welcome inquiries from prospective PhD/Master students, postdoctoral researchers, and collaborators interested in probabilistic machine learning.
Department of Computing Science
University of Aberdeen
Aberdeen, Scotland, UK