We are excited to invite you to the third edition of the Breaking Topics in AI Conference 2025, supported by the I-X AI in Science Centre.
The conference, this year bringing speakers from NeurIPS and ICML to London, will serve as a platform for sharing cutting-edge knowledge, discussing emerging trends, and fostering collaborative efforts to advance the field further. Our speakers will give overview talks outlining what they consider to be the exciting breakthroughs and future challenges in their area. The conference will also feature Flash Talks and Research Poster competitions.
Confirmed speakers so far:
- Georgia Channing (University of Oxford)
- (º£½ÇÉçÇø)
- Kevin Han Huang (University College London)
- (University College London)
- (º£½ÇÉçÇø)
- (University of Cambridge)
- (University College London)
- Paula Cordero Encinar (º£½ÇÉçÇø)
- (º£½ÇÉçÇø)
- (University of Cambridge)
- (University College London)
- (University of Oxford)
- Marta Aparicio Rodriguez (º£½ÇÉçÇø)
- (º£½ÇÉçÇø)
This is an in-person event.
Please note, this event is expected to quickly reach full capacity, so please make sure you have registered for your ticket well in advance.
Breaking Topics in AI Conference Programme
09:00 – 09:20 RegistrationÂ
09:20 – 09:30 Opening Remarks
Professor Sophia Yaliraki, º£½ÇÉçÇø
09:30 – 10:30 AI Deep Dive Session | Two Focus Talks
Chair: Sophia YalirakiÂ
Tolga Birdal, º£½ÇÉçÇø: Topological Deep Learning: A New Hope for Molecular Modelling and 3D Vision
Paula Cordero Encinar, º£½ÇÉçÇø: Sampling by Averaging: A Multiscale Approach to Score Estimation
10:30 – 11:00 Coffee BreakÂ
11:00 – 12:00 Flash Talk Session | Five 10-Minute Flash Talks
Chair: Ben MoseleyÂ
Kevin Han Huang, University College London: Diagonal Symmetrization of Neural Network Solvers for the Many-Electron Schrödinger Equation
Cristiana Diaconu, University of Cambridge: Gridded Transformer Neural Processes for Spatio-Temporal DataÂ
Hugh Dance, University College London: Efficiently Vectorized MCMC on Modern AcceleratorsÂ
Yedi Zhang, University College London: Training Dynamics of In-Context Learning in Linear Attention
Lisa Alazraki, º£½ÇÉçÇø: Reverse Engineering Human Preferences with Reinforcement Learning
12:00 – 13:00 Lunch and Poster Session
13:00 – 14:00 AI Deep Dive Session | Two Focus Talks
Chair: Laura M. Helleckes
Naoki Kiyohara, º£½ÇÉçÇø: Neural Stochastic Flows: Solver-Free Modelling and Inference for SDE SolutionsÂ
Lauri Laatu, º£½ÇÉçÇø: Sub-Microsecond Transformers for Jet Tagging on FPGAs
14:00 – 14:30 Coffee BreakÂ
14:30 – 15:30 Flash Talk Session | Five 10-Minute Flash Talks
Chair: Elli Heyes
Marta Aparicio Rodriguez, º£½ÇÉçÇø: Concept Reachability in Diffusion ModelsÂ
Guiomar Pescador Barrios, º£½ÇÉçÇø: Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?Â
Jan Ole Ernst, University of Oxford: Reinforcement Learning for Quantum Control Under Physical Constraints Â
Aya Kayal, University College London: Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
Krzysztof Kacprzyk, University of Cambridge: Skip the Equations: Learning Behavior of Personalized Dynamical Systems Directly from DataÂ
15:30 – 16:00 Coffee BreakÂ
16:00 – 17:00 AI Deep Dive Session | Three Focus Talks
Chair: Nick JonesÂ
Eleonora Giunchiglia, º£½ÇÉçÇø: Right for the Right Reasons: Avoiding Reasoning Shortcuts via Prototype-Augmented Neurosymbolic AIÂ
Peter Ochieng, University of Cambridge: Diversity Is All You Need for Contrastive Learning: Spectral Bounds on Gradient Magnitudes
Georgia Channing, University of Oxford: MAD-Sherlock: Multi-Agent Debate for Visual Misinformation DetectionÂ
17:00 – 17:10 Closing RemarksÂ
Professor Nick Jones, Director of I-X Centre for AI in Science, º£½ÇÉçÇø