I am a 2nd-year PhD student in Machine Learning at Imperial College London, supervised by Yingzhen Li. I obtained my MPhil degree in Machine Learning and Machine Intelligence from the University of Cambridge in 2020, supervised by José Miguel Hernández-Lobato. Before that, I graduated with a BSc (Hons) in Mathematics and Statistics from McMaster University.

During my PhD, I mainly study uncertainty estimation, robustness in large-scale machine learning models and generative modelling. In general, I am also interested in probabilistic model design, meta learning, and explainable AI. I aim to develop reliable algorithms with improved generalization, robustness and interpretability.

I am currently working as a research intern in the Responsible AI team at ByteDance in London, where I research on machine learning fairness and machine unlearning.

Publication

• Wenlong Chen, Yingzhen Li. Calibrating Transformers via Sparse Gaussian Processes. ICLR 2023 [link]
• Andrew Campbell*, Wenlong Chen*, Vincent Stimper*, Jose Miguel Hernandez-Lobato, Yichuan Zhang. A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter Optimization. ICML 2021 [link]

*equal contribution