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C2D3 Research Symposium

Wednesday, 22 April 2020, 9.00am to 6.10pm
Location: West Court, Jesus College, Jesus Ln, Cambridge CB5 8BL


Updated 16 March 2020

The organising committee for the C2D3 Research Symposium, 22 April 2020, would like to inform you we have taken the decision to postpone the event due to Covid-19. We would like to thank you for your enthusiasm to join us for a day of exciting discussions.

We hope to reschedule the Symposium and would very much like you to join us. When we have more information, the C2D3 Network will be informed (join our mailing list to stay in touch).


Symposium 2020

During this one-day symposium, leading Cambridge academics will showcase their latest research alongside lightning talks from early career researchers. Invited industry leaders from innovative businesses will being joining us to discuss the use of advanced data science methodologies in real-world applied applications. Talks and discussions will come from across the academic Schools and a variety of industry sectors, delivered at an accessible scientific level; delegates are welcomed from all backgrounds.


University of Cambridge Keynote Speaker

Professor Neil Lawrence

Neil Lawrence is the DeepMind Professor of Machine Learning at the University of Cambridge, Senior AI Fellow at the Alan Turing Institute, visiting Professor at the University of Sheffield and the co-host of Talking Machines.

Neil’s main research interest is machine learning through probabilistic models. He focuses on both the algorithmic side of these models and their application. His recent focus has been on the deployment of machine learning technology in practice, particularly under the banner of data science.


Guest Keynote Speaker

Dr Orlando Machado, Aviva

Orlando is currently Chief Data Scientist of Aviva Quantum, a global data science practice with over 500 members. Starting his career in academia, he has spent over 20 years helping organisations get value out of their data…long before ‘data scientist’ was crowned the ‘sexiest job of the 21st century’.

In 2019, Orlando was ranked #1 'DataIQ' list of the 100 most influential people in data-driven business. Orlando is based in Aviva’s Digital Garage in London’s fashionable Hoxton Square. He holds a PhD in Statistics from the University of Warwick. Prior to joining Aviva in 2016, Orlando was: Chief Data Scientist at MoneySuperMarket, the UK's largest price comparison website; Head of Customer Insight at dunnhumby, a company at the cutting edge of data science for more than 20 years; Head of Analytics at Wunderman, one of the world's largest communications agencies.


Programme Schedule

The Symposium will start with delegate registration at 09:00 and finish with a wine reception and networking opportunity at 18:10.

A full programme schedule will be available shortly.


Lightning Talk & Poster - Abstract Call

Applications to present a lightning talk with a poster, or to present a poster only, are open to PhD students and Early Career Researchers, from across all the University Schools.

We are looking for talks that showcase the depth and breadth of data science applications from the University, and research that industry will find interesting and informative. A prize will be awarded to the best lightning talk with poster, assessed by our industry colleagues.

Applications for Lightning Talks will open on Monday 3rd February 2020. Spaces are very limited, you are advised to apply as early as possible. Closing date extended to 23:59 Wednesday 11 March 2020, or sooner if symposium registrations are full.

Before applying: you must read the Further Information document below, where you will find important dates and instructions. 

To present a lightning talk with a poster​: Apply Here



Speakers and Chairs

Speakers and Chairs will receive a separate email containing their personal registration link.


Aviva Industry Partner

Registration for our Industry Partner, Aviva is free of charge. Aviva delegates will receive a registration link separately by email.


University of Cambridge Staff and Students

Registration for University of Cambridge Staff and Students are ESSENTIAL as places are limited but attendance is free of charge. Registration will open at 09:00 on Monday 2nd March 2020 and close at 23:59 on Sunday 5th April 2020. Register here.


Industry, Other Organisations and Other Universities

There is a Registration Fee of £80 for Industry, Other Organisations and Other Universities. Registration will open at 09:00 on Monday 2nd March 2020 and close at 23:59 on Sunday 5th April 2020. Register here.

The Registration Fee includes admission to all seminars, copy of the programme, lunch, refreshments and a wine reception. Other meals or accommodation are not included.

Your registration will be confirmed once your online payment has been received.  Details of payment will be noted within the registration form and booking confirmation.


Further Information

Further information including, Lightning Talk application process, directions to the venue and our Event Terms and Conditions are available below.

Forthcoming talks


Thursday, 7 July 2022, 4.00pm to 5.00pm
Speaker: Heidi Howard, Microsoft Research
Venue: FW11 and


Synthetics with Digital Humans

Friday, 8 July 2022, 12.00pm to 1.00pm
Speaker: Dr. Erroll Wood (Staff Software Engineer at Google)
Venue: (meeting ID: 649 250 9351 / passcode: 7mu5ZJ)


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.


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:

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


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.


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": 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.