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Beverley Lane

Administrative and Events Officer

Areas of work

Contact me for: 

  • Events management: the organisation of department events, workshops and conferences including managing budgets, raising purchase orders, processing expense claims and setting up payment processes via the University's Online Store
  • Facilities hire: enquiries and quotes for the hiring out of the department's meeting rooms to host groups outside of the department
  • Admin support for EDI Committee
  • Athena Swan and Race Equality work
  • Mental Health First Aid
  • Desks in the building: allocation of desks for new staff, students and visitors
  • Alumni relations
  • PA work for Gesine Reinert and Judith Rousseau
  • Green Impact 

About me

I joined the Department in January 2008 as a part time administrator.   My role has evolved over the years into a very varied and full-time role.  I have four grown up daughters and two delightful grandsons.

 

Contact Details

Email: beverley.lane@stats.ox.ac.uk

Office: G.08

Working hours: 

  • Monday 9.00 am - 6.00 pm
  • Tuesday 9.00 am - 5.00 pm
  • Wednesday 9.00 am - 5.30 pm
  • Thursday 9.00 am - 5.00 pm
  • Friday 9.00 am - 4.30 pm

                               

Working pattern:  In the office Tuesday, Thursday, Friday; from home Monday, Wednesday

Personal pronouns: She/her

Professor James Martin

Associate Professor of Probability

Biographical Sketch

Before arriving in Oxford in September 2005, I worked in Paris (for the CNRS, based in University Paris 7) and at the University of Cambridge.

 

Research Interests

My research is in probability theory, with strong links to statistical physics and theoretical computer science. Research interests include:

  • Interacting particle systems;
  • Models of random growth and percolation;
  • Algorithms on trees (for example models of broadcasting and reconstruction);
  • Models of coagulation and fragmentation;
  • Performance analysis of queueing and communication networks

Publications

Contact Details

Email: james.martin@stats.ox.ac.uk

Office number: 3.06

Research Groups

Probability

Research in Statistical Theory and Methodology include causal inference, graphical models, generalised Bayesian inference, statistical analysis of complex stochastic systems, and  methodologies and theoretical foundations for large-scale learning problems. Our research is closely linked to that in Computational Statistics and Machine Learning.

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News

Welcome to Computational Statistics and Machine Learning

The members of the Computational Statistics and Machine Learning Group (OxCSML) have research interests spanning Statistical Machine Learning, Monte Carlo Methods and Computational Statistics, and Applied Statistics.

Research in Statistical Machine Learning spans Bayesian probabilistic and optimization based learning of graphical models, nonparametric models and deep neural networks, and complements research in Monte Carlo methods for related classes of problems. 

Research in Applied Statistics motivates the more theoretical work in this group and some staff focus on developing statistical methodology ‘on demand’ in a wide range of application domains.

Join us for doctoral study

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