Cohort research projects
Our first-year researchers have completed a diverse and impactful range of projects, applying AI methods to real-world challenges in science, engineering, and industry. These projects span domains such as biosystems, physics, astronomy, and optimisation — showcasing the CDT’s focus on AI for decision making in complex systems.
Projects
Project titles
- Graph-Neural Networks for Computational Fluid Dynamics
- Researcher: John (Gabriel) Colenso
- Supervisory Team: Alistair Revell, Julia Handl
- Image segmentation in radio astronomy with physical models on graphs
- Researcher: Jaroslav Prilepok
- Supervisory Team: Jonas Latz, Anna Scaife
- Unpaired Multimodal Representation Learning
- Researcher: Rachel Gaffney
- Supervisory Team: Mauricio Alvarez, Magnus Rattray, Jason Hartford
- Astrophysical Light Curve Analysis in the Era of Big Data
- Researcher: Charlie Drury
- Supervisory Team: Rene Breton, Challenger Mishra
- Generative sequential experimental design
- Researcher: Jack Lee
- Supervisory Team: Samuel Kaski, Mingfei Sun, and Patrick Cai
- Spatial-temporal markers of embryo viability for decision making in IVF
- Researcher: Ruben Moreno Aguado
- Supervisory Team: Julia Handl, Berenika Plusa
- Real-time decision making at 40 MHz at the Large Hadron Collider
- Researcher: Anna- Christina Tymchyshyn
- Supervisory Team: Caterina Doglioni, Sukanya Sinha
- Designing optimal strategies for controlling complex quantum systems
- Researcher: Tzu-liang Hsu
- Supervisory team: Philip Taranto, Mauricio Álvarez, Wei Pan
- Interpretable Self-Sustaining Systems
- Researcher: Harry Allen
- Supervisory Team: Christian Cabrera and Neil Lawrence
- [Sys2RL] Thinking, Fast and Slow: Leveraging Reinforcement Learning to Improve
- Researcher: Brendan Bennett
- Supervisory Team: Mingfei Sun, Manuel Lopez-Ibanez
- A foundation model for C elegans brain dynamics
- Researcher: Freya Harris
- Supervisory Team: Guillaume Hennequin
Project titles
- Artificial intelligence for the Discovery and Engineering of Microbial Biosynthetic Gene Clusters
- Researcher: Hanlin Xiao
- Supervisory Team: Mauricio Álvarez, Eriko Takano.
- Using Deep Probabilistic Machine Learning to Understand Cellular Decision-Making
- Researcher: Mingxin Shen
- Supervisory team: Mauricio Alvarez Lopez, Magnus Rattray.
- Holistic ML-guided Design for the High-throughput Optimisation of Biologics
- Researcher: Michael Dodds
- Supervisory team: Henry Moss (University of Lancaster), Mauricio Alvarez Lopez, Carl Henrik Ek.
- Searching for New Physics with Neutrinos in a Novel Pixel Detector
- Researcher: Mohammed Sultan
- Supervisory Team: Roxanne Guenette, Elena Gramellini.
- Explainability of Deep Learning Models: The Concept Learning Approach
- Researcher: Oscar Hill
- Supervisory team: Mateja Jamnik (University of Cambridge), Mauricio Alvarez Lopez.
- New AI Applications to Large Astronomical Data Sets
- Researcher: Kyle Madgwick
- Supervisory Team: Christopher Conselice, Anna Scaife.
- Understanding the Training of Neural Nets to Solve PDEs
- Researcher: Sebastien Andre- Sloan
- Supervisory team: Anirbit Mukherjee, Alex Frangi.
- Relationship Between Conformal Prediction and Credal Probabilistic Reasoning
- Researcher: Fanyi Wu
- Supervisory team: Michele Caprio, Samuel Kaski.
- Combinatorial Optimization on Graphs for Science Operations in Radio Astronomy
- Researcher: Joan Font-Quer Roset
- Supervisory team: Anna Scaife, Mingfei Sun, Julia Handl.
- Generative Modelling for Engineering Design
- Researcher: Jacob Cummins
- Supervisory team: Wei Pan, Mingfei Sun, Alex Skillen.
- AI-powered Heuristics for Industrial Mathematical Optimization
- Researcher: Guorui Quan
- Supervisory team: Manuel López-Ibáñez, Mingfei Sun, Silvino Fernandez Alzueta.