TRKOY

Incoming PhD in MLG@Cambridge

Hi there 👋. I’m Tony RuiKang OuYang (歐陽瑞康 in Chinese; SeoiHong AuYeung pronounced in Cantonese). I’m an incoming PhD in Machine Learning 🤖 at the Machine Learning Group, University of Cambridge, supervised by Prof. José Miguel Hernández-Lobato and fully funded by the EPSRA DLA scholarship.

Recently, I completed my MPhil in Machine Learning and Machine Intelligence from the University of Cambridge 🎉. My MPhil thesis focus on energy-based neural sampler for sampling from Boltzmann distribution, which is supervised by Prof. José Miguel Hernández-Lobato. Prior to that, I finished my BEng in Data Science in Harbin Institute of Technology, Shenzhen (HITsz) and spent a wonderful year visiting in the University of Oxford studying Mathematics and Statistics (fully-funded by HITsz).

My current research interests include generative models, neural samplers, and their applications to molecular generation 🧬. Generally, I’m interested in probabilistic machine learning and AI4Science, especially developing powerful, efficient, and scalable methods that can be applied to physics ⚛️ and biochemistry 🧪.

news

Jul 31, 2025 I will start my PhD in the Machine Learning Group @ Cambridge in this October, fully funded by the DLA scholarship.
Jul 14, 2025 One paper is accepted by ICML 2025 🎉
Dec 05, 2024 I gave an oral presentation for BNEM in Workshop on ML4Molecules @ ELLIS 2024.
Nov 01, 2024 I started a new position as Research Assistant in Machine Learning @ Cambridge.
Oct 31, 2024 I completed MPhil in Machine Learning and Machine Intelligence @ Cambridge 🎓.

selected publications

  1. ptsd.png
    Progressive Tempering Sampler with Diffusion
    Severi Rissanen*RuiKang OuYang*, Jiajun He, and 4 more authors
    In International Conference on Machine Learning, 2025
  2. bnem.png
    BNEM: A Boltzmann Sampler Based on Bootstrapped Noised Energy Matching
    RuiKang OuYang*, Bo Qiang*, and José Miguel Hernández-Lobato
    2025
    In Workshop on Machine Learning and the Physical Sciences @ NeurIPS 2024; and Workshop on ML4Molecules @ ELLIS 2024