Hong Ge

photograph of Hong Ge

Principal Investigator
Department of Engineering
University of Cambridge

Research Lead, Alan Turing Institute
Fellow of Darwin College

Email: hg344 [at] cam.ac.uk
Office: James Dyson Building JD3-16, phone: +44 (0)1223 762438, map
Mail: Department of Engineering, Trumpington Street, Cambridge CB2 1PZ, UK
Curriculum Vitae (as of October 2025)

I am a member of the Machine Learning Group at the University of Cambridge, part of the Computational and Biological Learning Lab in the Department of Engineering.

If you are an undergraduate at Cambridge interested in research with our group, please send a short email about your interests and background (as specific as possible), with a resume/CV and any previous research papers. Thanks!

I'm always happy to hear from students about their research interests. However, due to the large number of inquiries, I'm unable to reply to most questions about PhD applications. Please don't take a lack of response as a lack of interest - if you mention my name in your research statement, I will see your application, and I'll make sure to look out for applications from students who have emailed me.

Research interests

My colleagues and I explore how intelligence works - mathematically and computationally. My current interests include Bayesian mathematics and neural networks. I also created the Turing probabilistic programming language.

Machine Learning Group @ Cambridge

Up-to-date publications (courtesy of Google scholar)

The Turing language project, State Space Programming, JuliaBUGS, Mooncake, AbstractGPs and my other Julia software.

Representative reading and talks

Turing.jl: A General-Purpose Probabilistic Programming Language. Fjelde, T. E., Xu, K., Widmann, D., Tarek, M., Pfiffer, C., Trapp, M., Axen, S. D., Sun, X., Hauru, M., Yong, P., Tebbutt, W., Ghahramani, Z., & Ge, H. (2024). ACM Transactions on Probabilistic Machine Learning, 1.
Practical Hamiltonian Monte Carlo on Riemannian Manifolds via Relativity Theory. Xu, K., & Ge, H. (2024). Forty-First International Conference on Machine Learning. (pdf, poster)
Neural characteristic activation analysis and Geometric Parameterization for ReLU networks. Chen, W., & Ge, H. (2023). Neural Information Processing Systems, 37, 97562–97586. (code)

Students and postdocs

Tor Erlend Fjelde
Adrian Goldwaser
Xianda Sun
Tim Hargreaves, co-supervised with Simon Godsill
Varun Jain
Nikolas Siccha
Markus Hauru, Alan Turing Institute
Penelope Yong, Alan Turing Institute

Former group members

Wenlin Chen, now at Bosch Research (Centre for Artificial Intelligence)
Will Tebbutt, now at Alan Turing Institute
Ross Viljoen, now at Graystone Technologies
Alexander Terenin, now Research Assistant Professor at Cornell University
Yongchao Huang, now Lecturer at Aberdeen University
Kai Xu, now Research Scientist at MIT-IBM Watson AI Lab
Colton Botta, now PhD student at Edinburgh University