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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

C2D3 event Talk In person

Beyond Academia - BBC, Head of Applied AI

10 Nov 2026

6 Jan 2027 - 8 Jan 2027

Uni of Cambridge Workshop In person

Accelerate Programme: Michaelmas Term training workshops

14 Sep 2026 - 11 Nov 2026

11 Nov 2026

12 Nov 2026

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

The Turing Lectures: How much can we limit the rising of the seas? External
Turing-Roche knowledge share: AI in Clinical Trials External
Turing-Roche knowledge share: AI in precision medicine External
Seminar: The environmental impact of computational science: how bad is it… C2D3 event
The Turing Lectures: Where next for self-driving vehicles? External
High Performance Computing Autumn Academy 2022 Uni of Cambridge
CCAIM AI and Machine Learning in Healthcare Summer School Uni of Cambridge
Aviva-Cambridge Annual Partnership Event 2022 Uni of Cambridge
Medical Image Understanding and Analysis Uni of Cambridge
Cambridge Mathematics of Information in Healthcare Hub (CMIH) - Academic Engagement… Uni of Cambridge
Open Science and Sustainable Software for Data-driven Discovery C2D3 event
Applied Process Mining for Management C2D3 event
Blending artificial intelligence with heterogeneous data sources to… External
An Introduction to Data and Commercialisation C2D3 event
Cambridge Imaging Festival 2022 Uni of Cambridge
CCBI/C2D3 Annual Computational Biology Symposium 2022 C2D3 event
Data science and AI for sustainability conference 2022 C2D3 event
AI UK: The UK’s national showcase of artificial intelligence and data science External
Cambridge Conference: AI in Drug Discovery Uni of Cambridge
Education Research Showcase - Department of Computer Science and Technology Uni of Cambridge
UTokyo-Cambridge Voices 2021: Engineering the future by leveraging digital… Uni of Cambridge
Interpretability, safety, and security in AI External
Software and Data Commercialisation for University Researchers C2D3 event
Networks to Collaborate in Cambridge Event Uni of Cambridge
The Turing Lectures: AI for drug discovery External
Cantab Capital Institute for the Mathematics of Information – Industry Engagement Uni of Cambridge
Statistics and modelling for policy in a COVID-zero setting External
Cambridge Public Health & Department of Engineering Workshop Uni of Cambridge
Accelerate Science's 2021 Annual Symposium External
Cambridge Zero Research Symposium: AI & Sustainability Uni of Cambridge
Structured missingness workshop External
Machine learning can identify newly diagnosed patients with Chronic… Uni of Cambridge
The Turing Lectures: The science of movement External
Cambridge-Turing sessions reloaded: collaborative data science and AI research C2D3 event
The cost of data: making sense in digital society Uni of Cambridge
The Turing Lectures: What are your chances? External
Aviva & University of Cambridge Annual Partnership Showcase C2D3 event
Entrepreneurial pathways to impact: Spinning-out your research Uni of Cambridge
Applied Process Mining for Management C2D3 event
Turing Data Study Group - Applications now open External
The Alan Turing Institute - DCEng Summit External
The Alan Turing Institute - Turing trustworthy digital identity conference External
Data x Biomedical Science Summer Event Series - Tuesday 20 July 2021 External
The Alan Turing Institute Digital Twins Workshop External
The Turing Lectures - Policy fights back: Mitigating algorithmic bias in AI… External
Data x Biomedical Science Summer Event Series - Tuesday 13 July 2021 External
The Trinity Challenge - Awards Ceremony External
Cambridge-Turing sessions: collaborative data science and AI research C2D3 event
Breaking the code: Alan Turing’s legacy in 2021 External
Cambridge Public Health Conference 2021: Children and Young People’s Mental… Uni of Cambridge

Talks

Upcoming related talks from talks@cam

Date Title Speaker Abstract
Beyond Academia - BBC, Head of Applied AI Nikolay Burlutskiy, Head of Applied AI, BBC

The Beyond Academia: AI & Data Science Applications seminar series at the University of Cambridge explores the transformative role of data and artificial intelligence in the world. Designed for postgraduate researchers, early-career academics, and students, the series bridges the gap between high-level research and real-world deployment.

BSU Seminar-"Hierarchical Causal Models" This is a free seminar- to attend remotely please use the following link: https://teams.microsoft.com/meet/3978637967598328?p=nw8RVurjolXhkz4sKy David Blei, Columbia University

Hierarchical Causal Models


David Blei

Columbia University


Title to be confirmed Jindřich Libovický (Charles University)


Neural networks for scientific discovery: hard-won insights Alex Matthew (cusp.ai)

Neural networks are powerful function approximators, but turning that flexibility into scientific discovery often requires a great deal of additional work. In this talk I will discuss two projects applying neural networks to partial differential equations. Although the applications and methods differ, they offer shared lessons about mathematical structure, and optimisation.


Expander Datacenters: From First Principles to the Cloud Prof. Michael Schapira, Hebrew University of Jerusalem

Abstract:

Statistics Clinic Michaelmas 2026 III

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.

Title to be confirmed Anne-Marie Lutgen (University of Luxembourg)


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:

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


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