Menu

Home / Events / Accelerate Science's 2021 Annual Symposium

Accelerate Science's 2021 Annual Symposium

Friday, 19 November 2021, 1.00pm to 4.00pm

How can we harness the potential of AI to accelerate scientific discovery? Find out more about the frontiers, opportunities and challenges of AI for science at Accelerate’s 2021 Annual Symposium.

AI has the potential to become an engine for scientific discovery across disciplines. From identifying new phenomena in the stars, to helping understand the materials around us here on Earth, and from mapping the climate system to investigating our genetic code.

Realising these benefits will require new technologies, new collaborations, and new interfaces between AI and the sciences. The Accelerate Programme for Scientific Discovery works to create these connections, developing AI tools and methods that can enhance scientific discovery. To explore recent advances in the application of AI for science and the ways in which the Cambridge community is deploying AI technologies, join us on 19 November for our first Accelerate Science Annual Symposium!

Hosted by Professor Neil Lawrence, the event will feature a mix of invited talks and community-led unworkshops:

13:00 Welcome and introduction to Accelerate - Ann Copestake and Neil Lawrence, Department of Computer Science and Technology
13:30 Alphafold and the frontiers of AI for science - Pushmeet Kohli (Head of Research AI for Science, Robustness, and Reliability, DeepMind) in conversation with Neil Lawrence
14:30 Community-led unworkshops (topics to be announced)
15:30 Roundtable: issues and opportunities in AI for science at Cambridge
16:00 Close

To attend, please register at this link.

Date: 19 November 2021

Time: 13:00 - 16:00

FAQs

What is an unworkshop?
Unworkshops are a space for conference participants to set the agenda. They can be seminars, talks, or discussion groups, on whatever topics are exciting or interesting to you at the interface of AI and the sciences. At the Accelerate Symposium, our unworkshop session will provide a space for the AI for science community to share ideas. If you’re interested in proposing a session, please fill in the form at this link - link here - or contact us at accelerate-science@cst.cam.ac.uk

What support will Accelerate provide to unworkshop convenors?
The team will provide technical support, along with someone in the session to help guide the discussion or activity.

How long will unworkshops be?
They will be an hour long. After the hour, we’ll ask workshop leads if they would like to join us in a plenary session that explores the topics covered by their session.

What can I do in a workshop?
The unworkshop is run at the discretion of the leader. These can be through lectures, seminar format, activities- the session is completely yours to explore.

  • Date published: 5 October 2021

REGISTER HERE

Forthcoming talks

Achieving Consistent Low Latency for Wireless Real-Time Communications with the Shortest Control Loop

Thursday, 18 August 2022, 4.00pm to 5.00pm
Speaker: Zili Meng, Tsinghua Unversity
Venue: FW11 and https://cl-cam-ac-uk.zoom.us/j/97216272378?pwd=M2diTFhMTnppckJtNWhFVTBKK0REZz09

Real-time communication (RTC) applications like video conferencing or cloud gaming require consistent low latency to provide a seamless interactive experience. However, wireless networks including WiFi and cellular, albeit providing a satisfactory median latency, drastically degrade at the tail due to frequent and substantial wireless bandwidth fluctuations. We observe that the control loop for the sending rate of RTC applications is inflated when congestion happens at the wireless access point (AP), resulting in untimely rate adaption to wireless dynamics. Existing solutions, however, suffer from the inflated control loop and fail to quickly adapt to bandwidth fluctuations. In this paper, we propose Zhuge, a pure wireless AP based solution that reduces the control loop of RTC applications by separating congestion feedback from congested queues. We design a Fortune Teller to precisely estimate per-packet wireless latency upon its arrival at the wireless AP. To make Zhuge deployable at scale, we also design a Feedback Updater that translates the estimated latency to comprehensible feedback messages for various protocols and immediately delivers them back to senders for rate adaption. Trace-driven and real-world evaluation shows that Zhuge reduces the ratio of large tail latency and RTC performance degradation by 17% to 95%.

Speaker Bio: Zili is a 3rd-year PhD student in Tsinghua University. His current research interest focuses on real-time video communications. He has published several papers in SIGCOMM / NSDI and received the Microsoft Research Asia PhD Fellowship, Gold Medal of SIGCOMM 2018 Student Research Competition, and two best paper awards.

BSU Seminar: "Genome-wide genetic models for association, heritability analyses and prediction"

Monday, 22 August 2022, 4.30pm to 5.30pm
Speaker: David Balding, Honorary Professor of Statistical Genetics at UCL Genetics Institute and University of Melbourne
Venue: Seminar Rooms 1 & 2, School of Clinical Medicine, Hills Road, Cambridge CB2 0SP

Although simultaneous analysis of genome-wide SNPs has been popular for over a decade, the problems posed by more SNPs than study participants (more parameters than data points), and correlations among the SNPs, have not been adequately overcome so that almost all published genome-wide analyses are suboptimal. While there has been much attention paid to the shape of prior distributions for SNP effect sizes, we argue that this attention is misplaced. We focus on what we call the "heritability model": a low-dimensional model for the expected heritability at each SNP, which is key to both individual-data and summary-statistic analyses. The 1-df uniform heritability model has been implicitly adopted in a wide range of analyses. Replacing it with better heritability models, using predictors based on allele frequency, linkage disequilibrium and functional annotations, leads to substantial improvements in estimates of heritability and selection parameters over traits, and over genome regions, as well as improvements in gene-based association testing and prediction. Key collaborators Doug Speed, Aarhus, Denmark and Melbourne PhD student Anubhav Kaphle.

Statistics Clinic Summer 2022 III

Wednesday, 31 August 2022, 5.30pm to 7.00pm
Speaker: Speaker to be confirmed
Venue: Venue to be confirmed

If you would like to participate, please fill in the following "form":https://forms.gle/b1UzrTNBig7hkr1e7. The deadline for signing up for a session is 12pm on Monday the 29th of August. Subject to availability of members of the Statistics Clinic team, we will confirm your in-person or remote appointment.

This 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.

Statistics Clinic Summer 2022 IV

Wednesday, 21 September 2022, 5.30pm to 7.00pm
Speaker: Speaker to be confirmed
Venue: Venue to be confirmed

Abstract not available

Title to be confirmed

Monday, 26 September 2022, 3.00pm to 4.00pm
Speaker: Christopher Yau, University of Manchester
Venue: CRUK CI Lecture Theatre

Abstract not available