Launch of industry-focused seminar series DataScience@Work

Compass is excited to announce the launch of the DataScience@work seminar series. This new seminar series invites speakers from external organisations to talk about their experiences as Data Scientists in industry, government and the third sector. The dual meaning of DataScience@work focuses talks on both the technical side of the speakers’ roles as well as working as part of a wider organisation, and building a career in data science.

Highlighting the importance of the new seminar series, Prof Nick Whiteley (Compass Director) says…

Prof Nick Whiteley addresses industry partners

Compass aims to develop scientific and professionally agility in its students. Our goal is to connect technical expertise in data science with experience of thinking, communicating and collaborating across disciplines and across sectors. In our new DataScience@Work seminar series, Compass partners from industry will share insights into the key role of Data Science within their organisations, their objectives and future outlook. This is a great opportunity for our students to learn about career trajectories beyond academia, helping shape their aspirations and personal goals for life beyond the PhD. I’m especially grateful to Adarga, CheckRisk, IBM Research, Improbable, and Shell for leading this first season of DataScience@Work and for their ongoing support for Compass.

For further information on the seminar series, including invited speakers to the 2020/21 session, see the DataScience@work page.


Compass Special Lecture: Jonty Rougier

Compass is excited to announce that Jonty Rougier (2021 recipient of the Barnett Award) will be delivering a Compass Special Lecture.

Jonty’s experience lies in Computer Experiments, computational statistics and Machine Learning, uncertainty and risk assessment, and decision support. In 2021, he was awarded Barnett Award by the RSS, which is made to those internationally recognised for contributions in the field of environmental statistics, risk and uncertainty quantification. Rougier has also advised several UK Government departments and agencies, including a secondment to the Cabinet Office in 2016/17 to contribute to the UK National Risk Assessment.


New opportunity: a jointly funded studentship with FAI Farms

Compass is very excited to advertise this PhD studentship in collaboration with FAI Farms on a vision-based system for automated poultry welfare assessment through deep learning and Bayesian modelling.

About the Project

This is an exciting opportunity to join Compass’ 4-year programme with integrated training in the statistical and computational techniques of Data Science. You will be part of a dynamic cohort of PhD researchers hosted in the historic Fry Building, which has recently undergone a £35 million refurbishment as the new home for Bristol’s School of Mathematics.

FAI Farms

FAI Farms is a multi-disciplinary team working in partnership with farmers and food companies to provide practical solutions for climate and food security. FAI’s state-of-the-art strategic advice, data insight, and education services, are powered by science, technology and best practice. Our strategic and evidence-based approach is focused on driving meaningful improvements across supply chains, mitigating risks and realising long term business benefits for our partners.

The aim of this PhD project is to create a vision-based system for the automated assessment of chicken welfare for use in poultry farms. The welfare of broiler chickens is a key ethical and economic challenge for the sustainability of chicken meat production. The presentation of natural, positive behaviour is important to ensure a “good life” for livestock species as well as being an expectation for many consumers. At present there are no ways to measure this, with good welfare habitually defined as the absence of negative experience. In addition, automated tracking of individual birds is very challenging due to occlusion and complexity. In this project the student will instead harness and develop novel deep learning approaches that consider individual animals and their behaviours probabilistically within the context of local and general activity within the barn and wider flock. The inferred behaviour rates amongst the flock will then be integrated with on-farm production, health and environmental data through Bayesian time series modelling to identify risk factors for positive welfare, predict farms at risk of poor welfare, and suggest interventions that avoid this scenario.


IBM Research is newest Compass partner to sponsor PhD project

The University of Bristol is excited to announce IBM Research Europe as a new partner of Compass – the EPSRC Centre for Doctoral Training in Computational Statistics and Data Science. IBM scientists are collaborating with Prof. Robert Allison and Compass PhD student Anthony Stephenson, on a research project entitled Fast Bayesian Inference at Extreme Scale. The project’s aim is to extend Bayesian inference algorithms to the ‘extreme scales’ that many deep learning workloads occupy, by placing more focus on AI methodologies which furnish both an accurate prediction, and critically, a high-quality uncertainty representation for predictions.

For more than seven decades, IBM Research has defined the future of information technology with more than 3,000 researchers in 19 locations across six continents. Scientists from IBM Research have produced six Nobel Laureates, 10 U.S. National Medals of Technology, five U.S. National Medals of Science, six Turing Awards, 19 inductees in the National Academy of Sciences and 20 inductees into the U.S. National Inventors Hall of Fame

IBM has European research locations in Switzerland (Zurich), England (Hursley and Daresbury), and Ireland (Dublin), with a large development lab in Germany focused on AI, quantum computing, security and hybrid cloud.

IBM’s global labs are involved hundreds of joint projects with universities particularly throughout Europe, in research programs established by the European Union and the local governments, and in cooperation agreements with research institutes of industrial partners.

Compass is a 4-year PhD training programme focusing on Computational Statistics and Data Science. This new venture is part of the Compass mission to promote academic and professional agility in its students, equipping them with the skills and experience to work across disciplines in academia and beyond.

Anthony Stephenson is the PhD student recruited to this project says, “After several years working in industry, I am pleased to be starting the Compass programme and shifting my focus to research. Having the combined forces of the University of Bristol and IBM behind me inspires confidence and I look forward to working with members of each of them. My project, scalable inference in non-linear Bayesian models, is also a highly relevant and exciting area to work on, with many applications in modern machine learning.”

Dr Ed Pyzer-Knapp is World-Wide IBM Research Lead in AI Enriched Modelling and Simulation and says, “I am very excited to work with Anthony and Robert – scaling Bayesian inference is a really important area of machine learning research; bringing to bear our mantra of fusing of bits and neurons to further develop the future of computing. This project is a great opportunity to further strengthen our relationship with the University of Bristol.”

Prof Robert Allison is Anthony’s academic supervisor at the University of Bristol and says, “I’m really looking forward to working with Anthony and Ed on a highly important and widely applicable area of machine learning which encompasses mathematical research, data-analysis, algorithm development and efficient large-scale computation. In addition, I see this project as an ideal opportunity to seed wider ranging data-science and machine learning collaborations between IBM Research, their academic partners and the University of Bristol.”

As Director of Compass, Prof Nick Whiteley say “I’m absolutely delighted to welcome IBM Research to Compass. This project is a fantastic opportunity for Anthony to tackle a very challenging and increasingly important AI research problem under Prof. Allison and Dr. Pyzer-Knapp’s supervision. As this collaboration develops, I look forward to all Compass students learning about IBM’s vision for the future of AI and its connection to the expertise in statistical methodology and computing they will acquire through the Compass training programme.”

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