Events

Forthcoming events

This page lists C2D3 events, University events, as well as related external conferences and events of interest to our members.

Ideas to Reality Programme
University of Cambridge event
Thursday, 26 September 2024, 12.00pm to Tuesday, 19 November 2024, 5.30pm

 

Our Ideas to Reality Programme, is returning in Autumn 2024 and features 5 workshops: 

AI and LLM training courses
University of Cambridge event
Monday, 14 October 2024, 9.30am to Wednesday, 4 December 2024, 5.00pm

The Accelerate Programme for Scientific Discovery, based in the Department of Computer Science and Technology, offers support for researchers across the University to use AI in their research. We are pleased to announce that our training courses & workshops for next term are open for booking!

Join us for courses exploring key topics in AI as well as two hands on workshops to apply your AI skills:

Generative Models AI Ellis
University of Cambridge event
Friday, 15 November 2024, 2.00pm to 3.30pm

The Cambridge ELLIS Unit Seminar Series holds talks by leading researchers in the area of machine learning and AI. Our next speaker for November 2024 will be Simon Olsson. Details of his talk can be found below.

Title: “Generative models as efficient surrogates for molecular dynamics simulations”

Communicating Mathematical and Data Sciences – What does Success Look Like?
External event
Thursday, 21 November 2024, 12.00am

This one-day workshop will explore evidence for effectively communicating research in mathematical and data science to non-experts such as policy makers, mainstream media and the wider public.

How can we make public health more precise?
University of Cambridge event
Thursday, 21 November 2024, 9.00am to 4.30pm

Join Cambridge Public Health for an exciting showcase, co-hosted by Cambridge Public Health Interdisciplinary Research Centre and Precision Health Strategic Research Initiative, to discover how advances in precision medicine are transforming public health.

From tailored health and well-being interventions to individualised early diagnostics and personalised therapies, our understanding of individual health and its impact on both communities and populations is rapidly evolving.

Computational and Systems Biology Seminar Series
University of Cambridge event
Thursday, 21 November 2024, 4.00pm to 5.00pm

The Computational and Systems Biology Seminar Series have an exciting lineup for the Michaelmas term, with a good mix of disciplines.

These talks will be held fortnightly at 16:00 on Thursdays.

Location: Department of Pathology Lecture Theatre, Tennis Court Road.

Abstracts for each talk can be found here.

Contact: Michael Boemo (mb915@cam.ac.uk)

for Science Summit, University of Cambridge
University of Cambridge event
Monday, 25 November 2024, 9.00am to Tuesday, 26 November 2024, 4.00pm

On Monday 25 and Tuesday 26 November  the Accelerate Programme for Scientific Discovery are inviting members of the AI for Science community to attend an AI for Science Summit, bringing together our community to combine our shared insights and experiences to drive progress in building the AI for Science community and deliver an impactful research agenda.


Confirmed speakers and panellists include:

AI and Science: An opportunity to strengthen the African scientific landscape
University of Cambridge event
Tuesday, 26 November 2024, 4.30pm to 5.30pm

ai@cam are delighted to be hosting a keynote seminar on AI and Science: An opportunity to strengthen the African scientific landscape with Dr Ciira Maina (Director of the  Centre for Data Science and Artificial Intelligence, and Associate Professor at Dedan Kimathi University of Technology, Nyeri, Kenya).

Synthetic Biology UK 2024
University of Cambridge event
Wednesday, 27 November 2024, 9.00am to Thursday, 28 November 2024, 5.00pm

Synthetic and Engineering Biology stand at the forefront of innovation, combining advances in biosciences, physical sciences, computer sciences, and engineering. These fields take rigorous engineering principles and apply them to the design of new biological systems.

How can we harness biology to address global challenges in healthcare, agriculture, manufacturing, and the environment? What are the latest scientific breakthroughs and advancements that will allow us to deliver on the promise of synthetic and engineering biology?

Validation data: strategies to avoid overuse
C2D3 event
Wednesday, 27 November 2024, 9.30am to 6.00pm

Are we overfitting to our validation data?  How can we do better?

Large Language Models in Practice: A Hands-On Journey from Data Collection to Insight Discovery
University of Cambridge event
Monday, 27 January 2025, 1.00pm to 5.00pm

Convenor: Jacob Forward, CDH Methods Fellow 2024–25

Jacob will offer hands-on experience of a full research pipeline in this methods workshop, from data collection and cleaning to deploying large language models (LLMs) to uncover new insights from our textual sources.

The session will cover:

Forthcoming talks

A collation of interesting data science talks from across the University.

Managing complexity of Weather and Climate Code with diversity of skills and workflows

Thursday, 14 November 2024, 1.00pm to 2.00pm
Speaker: Iva Kavcic - UK Met Office
Venue: West Hub, East 1

LFRic is the new weather and climate model developed by the Met Office to replace the existing Unified Model (UM). LFRic is at the core of Momentum®, a new Unified Earth Environment Prediction Framework created by the Met Office and its partners to deliver a seamless modelling capability that meets the challenges of exascale computing. LFRic relies on fundamentally different data structures to UM. Those, as well increase in resolution, led to complex technical challenges, such as compiler support, high volume of data and utilising opportunities presented by heterogeneous architectures. These fundamental changes mean changing several components of the operational forecast workflow. The key elements for success of any complex programme are expertise and skills of people working on it. People working in NGMS need to have a wide range of skills that are at intersection of several STEM-related areas, which poses challenges in identifying and developing technical expertise. In NGMS we are making use from resources across multiple teams, as well as from collaboration with external partners. We are continuously working on widening and diversifying our talent pool and developing it by providing training and support, as well as improving our recruitment process to support this.

The zoom link is https://cam-ac-uk.zoom.us/j/81161988457?pwd=TB5DgLyL0RLQROGBA4LC9jLnlKAh... (Password 355996)

Title to be confirmed

Thursday, 14 November 2024, 2.00pm to 3.00pm
Speaker: Dominik Diak (Entrepeneur First)
Venue: Maxwell Centre

Abstract not available

Title to be confirmed

Friday, 15 November 2024, 12.00pm to 1.00pm
Speaker: Janet Pierrehumbert (Oxford University)
Venue: Zoom link: https://cam-ac-uk.zoom.us/j/4751389294?pwd=Z2ZOSDk0eG1wZldVWG1GVVhrTzFIZz09

Abstract not available

Programmable Kernel Abstractions Wanted for Fun (and Profit)!

Friday, 15 November 2024, 2.00pm to 3.00pm
Speaker: Theophilus A. Benson, Professor of Electrical and Computer Engineering, Carnegie Mellon University
Venue: FW26

All traffic at Meta, Cloudflare, and many large companies are inspected, optimized, and balanced by tiny eBPF programs. Today, the eBPF ecosystem caters to the dominant open-source use cases, i.e., debugging (observability), and network functions (e.g., Firewalls, and cloud networking). However, a growing set of use cases within the enterprise and hyperscaler domains remain unaddressed. As a consequence, eBPF programs in these programs are susceptible to significant performance and availability issues, as evidenced by recent outages.

In this talk, I will provide a brief overview of these emerging use cases and the challenges they introduce. Then, I will discuss recent work at Meta to generalize BPF-management heuristics by introducing mechanisms to decouple BPF management primitives from the kernel's heuristics. Finally, I will describe ongoing efforts to increase flexibility and reactivity by introducing a novel orchestration paradigm.

Bio: Theophilus A. Benson is a professor of Electrical and Computer Engineering at Carnegie Mellon University. He earned his B.S. from Tufts, Ph.D. from U of Wisconsin-Madison, and post-doctorate from Princeton. Prof. Benson's research focuses on improving the performance and availability of computer networks. In particular, he works with a broad set of cloud providers to improve their infrastructures. He has recently been developing an initiative to address the digital divide in the Global South. His research was recognized by paper awards, including IMC, EuroSYS, ANRP. Dr. Benson received the SIGCOMM Test of Time Award, NSF CAREER Award, NEC Faculty Award, Google Faculty Award, Facebook Faculty Award (X2), and Faculty Research and Engagement Program (X2). Prof. Benson was recently named to DARPA's ISAT (Information Science and Technology) study group.

Generative models as efficient surrogates for molecular dynamics simulations

Friday, 15 November 2024, 2.00pm to 3.00pm
Speaker: Simon Olsson - Chalmers University of Technology
Venue: ​ https://cam-ac-uk.zoom.us/j/82615098116?pwd=cBUqlkyJqfNWqbn5DkBlVmDpmcjV0d.1

The Cambridge ELLIS Unit Seminar Series holds talks by leading researchers in the area of machine learning and AI. Our next speaker for November 2024 will be Simon Olsson. Details of his talk can be found below. ​

​Title: “Generative models as efficient surrogates for molecular dynamics simulations”​

Abstract: ​

Molecular dynamics (MD) is an important simulation technique in the natural sciences and engineering. In principle, it allows for establishing detailed, mechanistic models of molecular systems to explain and design experiments, or engineer molecules towards desirable properties. Unfortunately, these simulations are prohibitively expensive to use on a large scale. In this talk, I will present our work on using Generative AI methods to accelerate these simulations by orders of magnitude.​

https://cam-ac-uk.zoom.us/j/82615098116?pwd=cBUqlkyJqfNWqbn5DkBlVmDpmcjV...