We’re excited to welcome speakers from IBM Research to the next DataScience@work seminar.
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.
We’re excited to welcome speakers from CheckRisk to the next DataScience@work seminar.
We’re excited to welcome speakers from Adarga to the next DataScience@work seminar.
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
As part of UKRI NPIF Talent Funding 2019/2020, Compass applied for additional hardware and now has an operational GPU node*, specifically designed for the needs of statistical and machine learning analysis and with priority for COMPASS students.
This will enable our students to more rapidly train a wide variety of powerful, state of the art models in machine learning. GPUs have been essential to the rise of deep learning which, in the past decade, has revolutionised machine learning, rendering previously impossible tasks in image and natural language processing surmountable.
Upcoming seminars (if you are interested in attending you can sign up with Eventbrite using the links below):
- A picture is worth a thousand words. But what does it say? 19 November 2020, 11.00 AM – 19 November 2020, 12.00 PM Merve Alanyali, LV= via Zoom
- Detecting Local and Global Changes in Terrorism Incidence and the Effects of the COVID-19 Pandemic 3 December 2020, 11.00 AM – 3 December 2020, 2.00 PM Dr Sam Tickle, Data Science Heilbronn Research Fellow, University of Bristol via Zoom
- The Interface of Reinforcement Learning and Planning 17 December 2020, 11.00 AM – 17 December 2020, 12.00 PM Aviv Tamar, Technion – Israel Institute for Technology via Zoom