Trinity Term 2017


This lecture series now typically consists of three one and a half hour lectures in each of the following research areas:  Computational Statistics; Probability and Bioinformatics/Mathematical Genetics.

The lectures are usually held on Thursdays from 3.30 pm – 5.00 pm in LG.03, Department of Statistics, 24-29 St Giles unless indicated otherwise.

WEEK 1:   Thursday 27th April, 2.30 pm - 3.30 pm, Large Lecture Theatre (LG.01)

Speaker: Cecilia Lingren, Nuffield Department of Medicine, University of Oxford

Title:  Genetics of obesity and human fat distribution    

Abstract:  Prof. Cecilia Lindgren is a Senior Group Leader at the Big Data Institute, University of Oxford. Her research focuses on applying genomics to dissect the etiology of obesity related traits and their relationship with reproductive health.
In this seminar, Prof Lindgren will:
•      Introduce the background and rationale behind obesity trait genetic research
•      Give an overview of where we are in the field with our most recent research (including unpublished data)
•      Discuss what the clinical utility can be, and not be, of these discoveries
•      Outline the big data institute and what work she is doing, which is related to obesity genetics

WEEK 2:  Thursday 4th May, 3.30 pm - 5.00 pm, Small Lecture Theatre (LG.03)

Speaker:  Patrick Rubin-Delanchy, Department of Statistics, University of Oxford

Title:        Big Network Modeling and Anomaly Detection for Cyber-Security Applications

Abstract: Data arising in cyber-security applications often have a network, or `graph-like', structure, and accurate statistical modelling of connectivity behaviour has important implications, for instance, for network intrusion detection. We present a linear algebraic approach to network modelling, which is massively scalable and also very general. In this approach, nodes are embedded in a finite dimensional latent space, where common statistical, signal-processing and machine-learning methodologies are then available. A central limit theorem provides asymptotic guarantees on the statistical accuracy of the embedding. We explore an intriguing connection between `disassortivity', whereby nodes that are similar are relatively unlikely to connect, and space-time, as defined in special relativity. Mass testing for anomalous edges, correlations, and changepoints is then discussed. Results are illustrated on network flow data collected at Los Alamos National Laboratory. 

WEEK 3:  Thursday 11th May, 3.30 pm - 5.00 pm, Small Lecture Theatre (LG.03)

Speaker:  Arnaud Doucet, Department of Statistics, University of Oxford

Title:         What's new in Monte Carlo

WEEK 5:  Thursday 25th May, 3.30 pm - 5.00 pm, Small Lecture Theatre (LG.03)

Speaker:  Julien Berestycki, Department of Statistics, University of Oxford

Title:         An introduction to branching random walk models

WEEK 6:  Thursday 1st June, 3.30 pm - 4.30 pm, Small Lecture Theatre (LG.03)

Speaker:  Jotun Hein, Department of Statistics, University of Oxford

Title:         Combinatorics of Recombination

WEEK 7:  Thursday 8th June, 2.00 pm - 4.00 pm, Ground Floor social area

Graduate student poster session (second year)

WEEK 8:  Thursday 15th June, 1.00 pm - 6.00 pm

Careers Event for DPhil students and Postdocs (in collaboration with Medical Sciences)


Previous lectures: MT16; TT16; HT16