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C2D3 Virtual Symposium 2020

Wednesday, 21 October 2020, 10.30am to 3.20pm
Location: Online

Research Rendezvous: An online showcase of exciting research from across the University alongside guest talks from industry and independent organisations. The C2D3 Virtual Symposium 2020 Research Rendezvous seeks to spark new research questions, create new collaborations and connect distant parts of the data science community at the University and beyond. Our audience will be diverse with delegates from across academia, industry, independent organisations, local councils. We are excited to hear talks from our Academic Keynote Speaker Professor Mihaela van der Schaar (University of Cambridge) and our Guest Keynote Speaker Dr Orlando Machado (Aviva). All of the talks will be presented at an accessible level and interesting for all data science abilities; each talk will be accompanied with live meet the speaker Q&A sessions. The talks will be accompanied by an e-poster session and for Early Career Researchers there will be a prize for the best poster. Everyone is welcome to join us.

The event is kindly sponsored by Intel and financial support provided by the Isaac Newton Trust.

C2D3 symposium

 

Academic Keynote Speaker

Professor Mihaela van der Schaar, John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge, a Fellow at The Alan Turing Institute in London, and a Chancellor’s Professor at UCLA

Guest Keynote Speaker

Dr Orlando Machado, Chief Data Scientist, Aviva Quantum

Academic and Guest Speakers

Professor Jennifer Gabrys, Chair in Media, Culture and Environment, Department of Sociology, University of Cambridge

Dr Rosana Collepardo, Interdisciplinary Lecturer at the Departments of Chemistry and Genetics, and a Winton Advanced Research Fellow at the Department of Physics, University of Cambridge

Dr Mireia Crispin, Borysiewicz Fellow, Cancer Research UK - Cambridge Institute, University of Cambridge

Dr Ajith Parlikad, Asset Management Group at the Institute for Manufacturing, University of Cambridge

Reema Patel, Head of Public Engagement, Ada Lovelace Institute

Parviz Peiravi, Global CTO/Principal Engineer, Financial Services Industry Solutions, Solutions Architecture Development, Sales and Marketing Group, Intel

 

Programme and Abstracts

For the full programme, please click here.

  • Academic talks, with live meet the speaker Q&A
  • Guest talks, with live meet the speaker Q&A
  • e-Poster session, a competition for Early Career Researchers with a chance to win a £100 gift voucher and Q&A with the audience

Quick-glance programme is below!

Programme

 

E-poster opportunity

We welcome an e-poster submission from anyone whether internal or external to the University (we have recently opened up this opportunity to anyone and the information may differ from previous communications).

  • Submission of your final poster design will close at 17:00 on Monday 12th October
  • After registering, you will be provided information on how to submit your e-poster. Poster specs: pdf, max. file size 8 MB, portrait or landscape

E-poster prize

  • Each early career researcher entry will be entered into our e-Poster competition, with a chance to win a £100 gift voucher. All delegates will have the opportunity to vote for their favourite poster.
  • You should be an Early Career Researcher: a Student or within your first five years of employment after confirmation of latest qualification (e.g. PhD), on application closing date.

 

Delegate registration with e-Poster - closed

 

Delegate registration - closed

 

 

Social Media

Follow us on Twitter for news and information #C2D3symposium2020

 

Intel

 

 

Symposium Principal Sponsor

CUP logo

Symposium Sponsor

 

In support of the event are three Cambridge University Press Gold open access journals focused on the cutting-edge applications of data science in engineering, in public policy and in the growing body of environment related modelling and analysis. Full details can be found here and in the pdf attachement below.

Data-Centric Engineering DCE is an open access journal run by an international team of distinguished experts. Editor-in-Chief: Mark Girolami University of Cambridge (& C2D3 Steering Committee) & The Alan Turing Institute, UK

Data & Policy A peer-reviewed, open access journal dedicated to the impact of data science on policy and governance. Editors include: Jon Crowcroft University of Cambridge & Alan Turing Institute, UK

Newly Launched Title: Environmental Data Science An interdisciplinary, open access journal dedicated to the potential of artificial intelligence and data science to enhance our understanding of the environment, and to address climate change. 

INT logo

 

 

Event financial support

C2D3 Industry Partner

 

 

C2D3 Industry Partner

Forthcoming talks

TBC

Thursday, 7 July 2022, 4.00pm to 5.00pm
Speaker: Heidi Howard, Microsoft Research
Venue: FW11 and https://cl-cam-ac-uk.zoom.us/j/97216272378?pwd=M2diTFhMTnppckJtNWhFVTBKK0REZz09

TBC

Synthetics with Digital Humans

Friday, 8 July 2022, 12.00pm to 1.00pm
Speaker: Dr. Erroll Wood (Staff Software Engineer at Google)
Venue: https://zoom.us/j/6492509351?pwd=U0hoSzJ0anlhRGhzYVFmTzltNk9wZz09 (meeting ID: 649 250 9351 / passcode: 7mu5ZJ)

*Abstract*

Nowadays, collecting the right dataset for machine learning is often more challenging than choosing the model. We address this with photorealistic synthetic training data – labelled images of humans made using computer graphics. With synthetics we can generate clean labels without annotation noise or error, produce labels otherwise impossible to annotate by hand, and easily control variation and diversity in our datasets. I will show you how synthetics underpins our work on understanding humans, including how it enables fast and accurate 3D face reconstruction, in the wild.

*Bio*

Dr. Erroll Wood is a Staff Software Engineer at Google, working on Digital Humans. Previously, he was a member of Microsoft's Mixed Reality AI Lab, where he worked on hand tracking for HoloLens 2, avatars for Microsoft Mesh, synthetic data for face tracking, and Holoportation. He did his PhD at the University of Cambridge, working on gaze estimation.

Google Calendar for Future Seminars: https://calendar.google.com/calendar/u/0?cid=c2pjcHN0YXM2N3QyMWU3c2FqNjB...

Combining multi-omics and biological knowledge to extract disease mechanisms

Monday, 11 July 2022, 3.00pm to 4.00pm
Speaker: Julio Saez-Rodriguez, Faculty of Medicine of Heidelberg University, Director of the Institute of Computational Biomedicine and Group Leader at the EMBL- Heidelberg University Molecular Medicine Partnership Unit (MMPU)
Venue: CRUK CI Lecture Theatre

Multi-omics technologies, and in particular those with single-cell and spatial resolution, provide unique opportunities to study deregulation of intra- and inter-cellular processes in cancer and other diseases. In this talk I will present recent methods and applications from our group towards this aim, with a focus is on computational approaches that combine data with biological knowledge within statistical and machine learning methods. This combination allows us to increase both the statistical power of our approaches and the mechanistic interpretability of the results. I will also discuss the value to perform perturbation studies, combined with mathematical modeling, to increase our understanding and therapeutic opportunities. Finally, I will show how, using novel microfluidics-based technologies, this approach can also be applied directly to biopsies, allowing to build mechanistic models for individual cancer patients, and use these models to propose new therapies.

Claim-Dissector: An Interpretable Fact-Checking System with Joint Re-ranking and Veracity Prediction

Tuesday, 12 July 2022, 3.00pm to 4.00pm
Speaker: Martin Fajčík ( Brno University of Technology )
Venue: Computer Lab, FW26

Abstract:

We present Claim-Dissector: a novel latent variable model for fact-checking and fact-analysis, which given a claim and a set of retrieved provenances allows learning jointly (i) what are the provenances relevant to this claim (ii) what is the veracity of this claim. We show that our system achieves state-of-the-art results on FEVER comparable to two-stage systems often used in traditional fact-checking pipelines, while using significantly less parameters and computation.
Our analysis shows that proposed approach further allows to learn not just which provenances are relevant, but also which provenances lead to supporting and which toward denying the claim, without direct supervision. This not only adds interpretability, but also allows to detect claims with conflicting evidence automatically. Furthermore, we study whether our model can learn fine-grained relevance cues while using coarse-grained supervision. We show that our model can achieve competitive sentence-recall while using only paragraph-level relevance supervision. Finally, traversing towards the finest granularity of relevance, we show that our framework is capable of achieving strong token-level interpretability. To do this, we present a new benchmark focusing on token-level interpretability ― humans annotate tokens in relevant provenances they considered essential when making their judgement. Then we measure how similar are these annotations to tokens our model is focusing on. Our code, dataset and demo will be released online.

Bio:

Martin Fajčík (read as Fay-Cheek) is a PhD candidate in Natural Language Processing from Knowledge Technology Research Group active at FIT-BUT in Brno, Czech Republic, advised by prof. Pavel Smrž (ž is read like j in french "Jean"). From 2021, he also works as a research assistant in IDIAP research institute based in Martigny, Switzerland. His PhD work is focusing on open-domain knowledge processing, mainly in question answering and fact-checking. He enjoys a good hikes and an informal discussions over tea.

Statistics Clinic Summer 2022 I

Wednesday, 13 July 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/J6kRGdFeUG8dYqYW8. The deadline for signing up for a session is 12pm on Monday the 11th of July. 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.