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Events and Talks

 

In AI, Machine Learning and Data Science across the University and beyond.

Events

C2D3 event Talk In person

Computational Biology: Seminar Series

8 Oct 2026 - 18 Mar 2027

6 Jan 2027 - 8 Jan 2027

19 Nov 2026

Uni of Cambridge Conference Hybrid

AI for Science Summit 2026

24 Nov 2026

9 Dec 2026 - 10 Dec 2026

11 Jan 2027 - 15 Jan 2027

External Conference In person

Advances in AI Conference 2027

6 Apr 2027 - 7 Apr 2027

Talks

Upcoming related talks from talks@cam

Date Title Speaker Abstract
Variation is the Norm: Embracing Sociolinguistics in NLP Anne-Marie Lutgen (University of Luxembourg)

In Natural Language Processing (NLP), variation is typically seen as noise and "normalised away'' before processing, even though it is an integral part of language. Conversely, studying language variation in social contexts is central to sociolinguistics. I will present a framework to combine the sociolinguistic dimension of language with the technical dimension of NLP. I argue that by embracing sociolinguistics, variation can actively be included in a research setup, in turn informing the NLP side.

MRC Biostatistics Unit seminar Pawel Morzywolek, University of Copenhagen

Inference on Variable Importance for Treatment Effect Heterogeneity: Shapley Values and Beyond


How Do Language Models Reason? Foundations, Limitations and Neuro-Symbolic Approaches André Freitas (Idiap Research Institute & University of Manchester)

How do language models reason, and what would it take to build AI systems capable of sustained, complex reasoning? This lecture develops the foundations for answering these questions, connecting what we know about the internal workings of language models with methods for evaluating and extending their capabilities.


Optimising Julia code on GPUs: Case studies from ocean and atmosphere modelling Mikolaj Kowalski, Jack Franklin, David Kamm - RSEs, ICCS, University of Cambridge

Julia is a just-in-time (JIT) compiled language with a strong focus on scientific computing and performance. It has gained significant popularity in the climate science community, largely due to its flexibility and excellent native support for GPU computing. Over the last year, our team at the Institute for Computing for Climate Science (ICCS) has collaborated closely with the developers of major Julia-based ocean and atmosphere models to optimize their performance on GPU architectures.

Optiver.com


ALPS: An Efficient Request Scheduler for LLM Inference Dr Chen Chen, Nottingham Trent University

Abstract:

Computational Biology Seminar Series - Dr Benjamin Schuster-Boeckler Dr Benjamin Schuster-Boeckler, Ludwig Institute for Cancer Research, University of Oxford​

Talk title: The Exposome: how life leaves a trail of mutations in our genomes


Hosted by: Michael Boemo​


https://www.c2d3.cam.ac.uk/events/computational-biology-seminar-series-2026-27

Aligning LLMs to the Human Brain Mariya Toneva (Max Planck Institute for Software Systems)


The AI Exponential: Scientific Discovery, Engineering Simulation, and the New Student Space Race

Professor Bishop will discuss the rapid advancement of artificial intelligence and its transformative impact across fields including software engineering, weather forecasting, mathematics, scientific discovery, and engineering simulation. The lecture will also highlight an ambitious student rocketry project being undertaken within the Department.


Title to be confirmed Bálint Gyevnár (CMU)


Amazon.com Amazon.com


Scaling Analytical Benchmarks to Production Complexity   Jan Vincent Szlang, University of Cambridge

Abstract:

Red teaming frontier AI at the UK AI Security Institute M. Pawan Kumar (AI Security Institute)

Abstract: The UK’s AI Security Institute (AISI), situated within the Cabinet Office, works to equip government with an evidenced understanding of the risks posed by advanced AI. AISI's Red Team stress-tests frontier safety measures: finding ways misuse safeguards can fail, investigating unintended and harmful model behaviours, and assessing whether protocols intended to keep models under control actually work.


Statistics Clinic Michaelmas 2026 IV

This free event is open only to members of the University of Cambridge (and affiliated institutes). Please be aware that we are unable to offer consultations outside clinic hours.

Validity by Design for LLM "Reasoning" Rachel Lawrence (Microsoft Research Cambridge)


QBS - Dr Alexis Barr Dr Alexis Barr, Imperial College London

Title: Discovery research for better cell cycle targeting in cancer


How Prolific is accelerating frontier research: complex human-subjects studies built on a foundation of data quality Dr Simon Jones (Prolific)


Abstract

Title to be confirmed Simon Ostermann (German Research Centre for Artificial Intelligence)


[Rescheduled] Title to be confirmed Prof Jon Crowcroft, University of Cambridge

N/A

Cambridge AI in Medicine Seminar - December 2026 Shivani Sinha

Sign up on Eventbrite: details coming soon