We are excited to share Dr Daniel Lawson’s (Compass CDT Co-Director) latest video where he will tell you about the Data Science behind Bristol’s COVID Modelling.
This month, the Cohort 2 Compass students have started work on their mini projects and are establishing the direction of their own research within the CDT.
Supervised by the Institute for Statistical Science:
Anthony Stevenson will be working with Robert Allison on a project entitled Fast Bayesian Inference at Extreme Scale. This project is in partnership with IBM Research.
Conor Crilly will be working with Oliver Johnson on a project entitled Statistical models for forecasting reliability. This project is in partnership with AWE.
Euan Enticott will be working with Matteo Fasiolo and Nick Whiteley on a project entitled Scalable Additive Models for Forecasting Electricity Demand and Renewable Production. This project is in partnership with EDF.
Annie Gray will be working with Patrick Rubin-Delanchy and Nick Whiteley on a project entitled Exploratory data analysis of graph embeddings: exploiting manifold structure.
Ed Davis will be working with Dan Lawson and Patrick Rubin-Delanchy on a project entitled Graph embedding: time and space. This project is in partnership with LV Insurance.
Conor Newton will be working with Henry Reeve and Ayalvadi Ganesh on a project entitled Decentralised sequential decision making and learning.
The following projects are supervised in collaboration with the Institute for Statistical Science (IfSS) and our other internal partners at the University of Bristol:
Dan Ward will be working with Matteo Fasiolo (IfSS) and Mark Beaumont from the School of Biological Sciences on a project entitled Agent-based model calibration via regression-based synthetic likelihood. This project is in partnership with Improbable
Georgie Mansell will be working with Haeran Cho (IfSS) and Andrew Dowsey from the School of Population Health Sciences and Bristol Veterinary School on a project entitled Statistical learning of quantitative data at scale to redefine biomarker discovery. This project is in partnership with Sciex.
Shannon Williams will be working with Anthony Lee (IfSS) and Jeremy Phillips from the School of Earth Sciences on a project entitled Use and Comparison of Stochastic Simulations and Weather Patterns in probabilistic volcanic ash hazard assessments.
Sam Stockman will be working with Dan Lawson (IfSS) and Maximillian Werner from the School of Geographical Sciences on a project entitled Machine Learning and Point Processes for Insights into Earthquakes and Volcanoes
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 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.
by Dr Daniel Lawson, Senior Lecturer in Data Science, University of Bristol and Compass CDT Co-Director
For the first time in history, data is abundant and everywhere. This has created a new era for how we understand the world. Modern Data Science is new and changing the world, but it is rooted in cleverness throughout history.
What is Data Science used for today?
Data Science is ubiquitous today. Many choices about what to buy, what to watch, what news to read – these are either directly or indirectly influenced by recommender systems that match our history with that of others to show us something we might want. Machine Learning has revolutionised computer vision, automation has revolutionised industry and distribution, whilst self-driving cars are at least close. Knowledge is increasingly distributed, with distributed learning ranging from Wikipedia to spam detection.
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.”
Mathematics from Dr Daniel Lawson‘s group at the University of Bristol found that the World’s largest ever DNA sequencing of Viking skeletons reveals they weren’t all Scandinavian. (Link to Paper.)
Invaders, pirates, warriors – the history books taught us that Vikings were brutal predators who travelled by sea from Scandinavia to pillage and raid their way across Europe and beyond.
Congratulations to Professor Anthony Lee – Unit Director for Statistical Computing 1 in the Compass CDT programme – and Professor Nick Whiteley – Compass CDT Director – who have been appointed to the position of Heilbronn Chairs in Data Science. Anthony and Nick have distinguished themselves as internationally outstanding leaders in their field and these appointments support our position as one of the top centres for statistical and data science in the UK.