Ryan Chan

I’m a senior research associate focusing on end-to-end machine-learning weather forecasting. In particular, I’m working on Project Cumulus, an initiative to develop bespoke data-driven weather subseasonal forecasting systems tailored for farming communities in West Africa.

I have a background in statistics, machine learning and software engineering. I hold a PhD in Statistics from the University of Warwick, supervised by Professor Gareth Roberts and Professor Murray Pollock. In my PhD, I focused on developing Monte Carlo methods for combining distributed statistical analyses (Fusion). I completed my undergraduate studies at the University of Leeds, where I was awarded a first class honours MMath Mathematics degree and received the Royal Statistical Society Prize.

Research & Projects

I am interested in applying machine learning to environment and sustainability problems and currently focusing on end-to-end data-driven weather forecasting.

Current

• Project Cumulus — Data-driven forecasting systems to support farming communities in West Africa. Leading development of observationally driven models for global sub-seasonal forecasting. [Press release]

Previous

• FastNet: AI for Numerical Weather Prediction — A Graph Neural Network for medium-range weather forecasting, developed in collaboration between the Met Office and The Alan Turing Institute. [Technical report] [Pre-print]
• Project t0 — Lean language models using knowledge retrieval and fine-tuning for reasoning and test-time scaling. [Blog] [Technical report] [Code]
• prompto — Open source software for reproducible experiments on LLMs at scale, supporting self-hosted and API-based models. [NAACL 2025]
• Rough Paths — Software and applications of rough path theory and path signatures for complex data streams, with applications in NLP.
  • nlpsig: Python library for constructing paths of transformer embeddings.
  • sig-networks: PyTorch library for signature neural networks for longitudinal NLP. [EACL 2024]
  • SigMahaKNN: Anomaly detection on multivariate streams using path signatures. [Paper]
• IceNet — Probabilistic deep learning sea ice forecasting system led by British Antarctic Survey and The Alan Turing Institute. [Nature Communications] Nominated for the Arctic Circle Frederik Paulsen Award.

Miscellaneous

• Maya — Multilingual multimodal model based on Cohere’s Aya and LLaVA, part of C4AI’s Expedition Aya 2024. Won the Most Promising Award. [CVPR 2025 Workshop]
• Reginald — LLM chatbot for The Alan Turing Institute using RAG and llama-index, deployed on the Turing’s Slack workspace.
• AIrsenal & AIrgentina — Machine learning for Fantasy Premier League and World Cup prediction. AIrgentina came 6th in @Futbolmetrix1’s WC2022 contest, outperforming FiveThirtyEight, Opta, and Betfair. [Blog] [New Scientist]
• Podcast recommendation systems — Topic modelling and collaborative filtering for podcast discovery, with Entale at ATI Data Study Group (April 2021). [Report]
• Bayesian Sports Modelling — Bayesian hierarchical models for football match prediction (masters project). [Code]

Selected Publications

• Daub, E. G. et al. Technical overview and architecture of the FastNet Machine Learning weather prediction model, version 1.0. 2025. [Report]
• Dunston, T. et al. FastNet: Improving the physical consistency of machine-learning weather prediction models through loss function design. 2025. [Pre-print]
• Chan, R.S.Y., Nanni, F., Lazauskas, T., Wood, R., Yong, P., Tarassenko, L., Girolami, M., Geddes, J., Duncan, A. Retrieval-augmented reasoning with lean language models. 2025. [Report]
• Bowler, E. et al. AI sea ice forecasts for Arctic conservation: A case study predicting the timing of caribou sea ice migrations. 2025. Ecological Solutions and Evidence. [Paper]
• Chan, R.S.Y., Nanni, F., Brown, E., Chapman, E., Williams, A.R., Bright, J., Gabasova, E. Prompto: An open source library for asynchronous querying of LLM endpoints. 2025. In Proceedings of NAACL 2025. [Paper]
• Williams, A.R., Burke-Moore, L., Chan, R.S.Y. et al. Large language models can consistently generate high-quality content for election disinformation operations. 2025. PLoS ONE. [Paper]
• Alam, N. et al. Maya: Multimodal Aya. 2025. In CVPR 2025 Workshop Vision Language Models For All. [Paper]
• Tseriotou, T., Chan, R.S.Y., Tsakalidis, A., Bilal, I.M., Kochkina, E., Lyons, T., Liakata, M. Sig-Networks Toolkit: Signature Networks for Longitudinal Language Modelling. 2024. In Proceedings of EACL 2024. [Paper]
• Mougan, C. et al. How to Data in Datathons. 2023. In NeurIPS 2023 Datasets and Benchmarks Track. [Paper]
• Chan, R.S.Y., Johansen, A.M., Pollock, M., and Roberts, G.O. Divide-and-Conquer Fusion. 2023. Journal of Machine Learning Research. [Paper]

Talks, Conferences & Awards

Awards

• C4AI Expedition Aya 2024: Most Promising Award for Maya: Multimodal Aya
• The Alan Turing Institute Doctoral Studentship (2018–2022)
• The Royal Statistical Society Prize (2018)
• The Top 10 Scholarship, School of Mathematics, University of Leeds (2015, 2016, 2017)
• Summer Vacation Bursary Scheme, School of Mathematics, University of Leeds (2016, 2017)

Presentations

• Robots in Disguise: Mechanistic Interpretability III — Sparse Autoencoders. 20/11/24
• Robots in Disguise: Mechanistic Interpretability II — Circuits and Superposition. 02/10/24
• Robots in Disguise: Mechanistic Interpretability I — Introduction. 23/09/24
• Robots in Disguise: An overview of Llama 3.1. 12/08/24
• Robots in Disguise: Vision Transformers. 07/08/23
• Robots in Disguise: GPT. 24/07/23
• Robots in Disguise: BERT. 07/07/23
• Greek Stochastics Nu [Naxos]. 07/07/23
• Robots in Disguise: Transformer Encoder and Decoder models. 26/06/23
• Robots in Disguise: Sequence-to-sequence models Part II. 03/05/23
• Robots in Disguise: Sequence-to-sequence models Part I. 17/04/23
• AIUK Demo (IceNet) [London]. 21/03/23
• Lunchtime Tech Talk [The Alan Turing Institute]. 25/10/22
• 2022 World Meeting of the International Society for Bayesian Analysis [Montreal]. 28/06/22
• Data Study Group (April 2021) Entale [The Alan Turing Institute]. 29/04/21
• Young Researchers’ Meetings [University of Warwick]. 09/02/21
• Statistics Group Seminar [Newcastle University]. 10/07/20
• RSS Discussion Meeting — “Quasi-stationary Monte Carlo and ScaLE” [The Royal Statistical Society]. 24/06/20 [Video]
• The Student Seminar Series [The Alan Turing Institute]. 21/04/20
• University of Warwick Departmental Conference [Gregynog]. 24/03/20
• Algorithms & Computationally Intensive Inference Seminar [University of Warwick]. 08/03/19
• Student Seminar [University of Leeds]. 22/05/18 [Handout]

Posters

• 2022 World Meeting of the International Society for Bayesian Analysis [Montreal]. 28/06/22
• Bayes at CIRM 2021 [Marseille]. 25/10/21
• 2021 World Meeting of the International Society for Bayesian Analysis [Online]. 28/06/21
• The Turing Research Showcase [Online]. 24/09/20 [Video]
• Greek Stochastics Lambda [Corfu]. 28/08/19
• O’Bayes 2019 [University of Warwick]. 29/06/19

Miscellaneous

• Cycling from Manchester to London for Ambitious for Autism
• PhD Thesis: Monte Carlo methods for combining sample approximations of distributions; examined by Professor Nicolas Chopin and Dr. Krzysztof Łatuszyński
• Advent of Code 2022 with Julia
• R package for Fusion methodologies: DCFusion
• R package for layered Brownian bridges: layeredBB
• Advent of Code 2021 with R
• Masters Thesis: Bayesian Sports Modelling
• Undergraduate project: Automatic Puzzle Solving
• Fundraising for FareShare: Cycling challenge