Department of Statistics

By Oxford University

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Episodes: 41

Description

The Department of Statistics at Oxford is a world leader in research including computational statistics and statistical methodology, applied probability, bioinformatics and mathematical genetics. In the 2014 Research Excellence Framework (REF), Oxford's Mathematical Sciences submission was ranked overall best in the UK. This is an exciting time for the Department. We have now moved into our new home on St Giles and we are currently settling in. The new building provides improved lecture and teaching space, a variety of interaction areas, and brings together researchers in Probability and Statistics. It has created a highly visible centre for the Department in Oxford. Since 2010, the Department has been awarded over forty research grants with a total value of £9M, not counting several very large EPSRC and MRC funded awards for Centres for doctoral training.The main sponsors are the European Commission, EPSRC, the Medical Research Council and the Wellcome Trust. We offer an undergraduate degree (BA or MMath) in Mathematics and Statistics, jointly with the Mathematical Institute. At postgraduate level there is an MSc course in Applied Statistics, as well as a lively and stimulating environment for postgraduate research (DPhil or MSc by Research). Our graduates are employed in a wide range of occupational sectors throughout the world, including the university sector. The Department co-hosts the EPSRC and MRC Centre for Doctoral Training (CDT) in Next-Generational Statistical Science- the Oxford-Warwick Statistics Programme OxWaSP.

Episode Date
A Theory of Weak-Supervision and Zero-Shot Learning
Jun 09, 2022
Victims of Algorithmic Violence: An Introduction to AI Ethics and Human-AI Interaction
Apr 06, 2022
The practicalities of academic research ethics - how to get things done
Apr 05, 2022
Statistics, ethical and unethical: Some historical vignettes
Apr 05, 2022
Joining Bayesian submodels with Markov melding
Apr 05, 2022
Neural Networks and Deep Kernel Shaping
Apr 05, 2022
Introduction to Advanced Research Computing at Oxford
Apr 05, 2022
Ethics from the perspective of an applied statistician
Mar 31, 2022
A Day in the Life of a Statistics Consultant
Mar 31, 2022
Metropolis Adjusted Langevin Trajectories: a robust alternative to Hamiltonian Monte-Carlo
Mar 31, 2022
Modelling infectious diseases: what can branching processes tell us?
Mar 31, 2022
Causality and Autoencoders in the Light of Drug Repurposing for COVID-19
Jul 29, 2021
Recent Applications of Stein's Method in Machine Learning
Jul 29, 2021
Do Simpler Models Exist and How Can We Find Them?
Jul 29, 2021
Practical pre-asymptotic diagnostic of Monte Carlo estimates in Bayesian inference and machine learning
Jul 29, 2021
Complexity of local MCMC methods for high-dimensional model selection
Jul 02, 2021
Assessing Personalization in Digital Health
Jun 23, 2021
Machine Learning in Drug Discovery
Jun 23, 2021
Several structured thresholding bandit problems
Jun 23, 2021
A primer on PAC-Bayesian learning *followed by* News from the PAC-Bayes frontline
May 28, 2021
Approximate Bayesian computation with surrogate posteriors
May 21, 2021
Introduction to Bayesian inference for Differential Equation Models Using PINTS
May 21, 2021
On classification with small Bayes error and the max-margin classifier
May 21, 2021
Convergence of Online SGD under Infinite Noise Variance, and Non-convexity
May 21, 2021
Distribution-dependent generalization bounds for noisy, iterative learning algorithms
Mar 17, 2021
Finding Today’s Slaves: Lessons Learned From Over A Decade of Measurement in Modern Slavery
Mar 01, 2021
Veridical Data Science for biomedical discovery: detecting epistatic interactions with epiTree
Feb 26, 2021
(Not) Aggregating Data: The Corcoran Memorial Lecture
Feb 05, 2021
Florence Nightingale Bicentennial Panel Session
Feb 05, 2021
Florence Nightingale and the politicians’ pigeon holes: using data for the good of society
Jan 07, 2021
Probabilistic Inference and Learning with Stein’s Method
Dec 04, 2020
Introduction to Deep Learning and Graph Neural Networks in Biomedicine
Dec 03, 2020
Looking back on 4 years in data science
Nov 28, 2020
Black History Month: Exploring the Data Visualizations of W.E.B. Du Bois
Oct 23, 2020
The Science Media Centre and its work
Jun 24, 2020
How To Set Up Continuous Integration to Make Your Code More Robust, More Maintainable, and Easier to Publish
Jun 10, 2020
Developing better code with automated testing
Jun 10, 2020
Cluster-Randomised Test Negative Designs: Inference and Application to Vector Trials to Eliminate Dengue
Jun 10, 2020
MCMC for Hierachical Bayesian Models Using Non-reversible Langevin Methods
Jun 10, 2020
Maths and Stats in Action – Real-time Analysis to Understand the Novel Coronavirus
Mar 11, 2020
Bioinformatics at the heart of biology and genomics medicine
Apr 27, 2016