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Forthcoming Workshops

Each year CRiSM hosts several workshops focussing on both the statistical methodology and its applications. It provides a great opportunity to keep up-to-date with current research worldwide and to collaborate with academics from other institutions.

Here is a list of all workshops hosted since 2006.

More information on forthcoming workshops can be found by clicking on the links below:


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Mon 15 Apr, '24 - Fri 19 Apr, '24
All-day
Frag-coag Workshop
MS.03

Runs from Monday, April 15 to Friday, April 19.

This workshop is in association with CRiSM and is the fourth of series of earlier events held in 2012, 2015, and 2019. For this edition there will be an additional theme of fragmentation and coalescence, in association with the EPSRC project "Random fragmentation-coalescence processes out of equilibrium".

Thu 16 May, '24
Interdisciplinary workshop - Quantifying Carbon footprint
Scarman Space 24

TBC

Wed 5 Jun, '24 - Fri 7 Jun, '24
10:00 - 17:00
BioInference 2024
MS.01

Runs from Wednesday, June 05 to Friday, June 07.

If you are interested on mathematical modelling and statistical methods for (widely defined/interpreted) biological problems, then save the date for BioInference2024 (5th -7th June, here at Warwick), and consider sending an abstract for a poster/talk.

Mon 10 Jun, '24 - Wed 12 Jun, '24
All-day
Workshop on Heterogeneous and Distributed Data
MS.01

Runs from Monday, June 10 to Wednesday, June 12.

The aim of the event is to bring together researchers in areas such as missing data, (local) differential privacy, communication-constrained inference and transfer learning to share recent progress and motivate future directions.

Mon 9 Sep, '24 - Tue 10 Sep, '24
All-day
Data Visualisation -Paul Murrell Masterclass
Rootes Building, Chancellors 1 and 2

Runs from Monday, September 09 to Tuesday, September 10.

This 2-day course covers the big data visualisation questions: *what* should I draw and *how* should I draw it. Discover how to represent your data visually, following guidelines that play to the strengths of our visual system while avoiding its weaknesses, using the R package ggplot2.

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