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The Leeds Workshop is a well established annual statistical meeting which was founded in 1974 by Kanti Mardia who led it over four decades until 2015. In 2017 it was directed jointly by Jeanine Houwing-Duistermaat and Kanti Mardia. Although begun as an internal event, it now enjoys the support of a number of visitors each year from other universities and research bodies around the world. These workshops usually extend over three days with input by several speakers. Over recent years, the theme of the workshop has reflected the growing, but not exclusive, departmental interest and expertise in bioinformatics, image and shape analysis, wavelets and machine learning. Four decades of the Leeds Workshops were celebrated at the 2015 LASR Workshop.
The LASR mission is to:
- Bring together world-class scientists and statisticians
- Encourage cutting-edge interdisciplinary research
- Sustain and develop workshops
Many of the topics addressed by the LASR workshop are connected to the theme of geometric statistics - the interpretation of information with a geometric flavour such as:
- Spatial statistics
- Image analysis
- Shape analysis
- Bioinformatics
Past LASR workshops
Geostatistics (Conference) | D.G. Kendall, A. Marechal | 1979 | |
1 | Spatial Processes on Regular Lattices | Dr. R.J. Martin | 1980 |
2 | Applied Spatial Processes | J. Besag | 1981 |
3 | Spatial Statistics | B.D. Ripley | 1982 |
4 | Estimation Procedures for Stationary Spatial Processes | X. Guyon | 1983 |
Statistics of Image Processing (Conference) | J.V. Kittler | 1984 | |
5 | Bispectral Analysis and Bilinear Time Series Models | T. Subba-Rao | 1985 |
6 | Statistics and Image Processing | J. Haslett | 1986 |
7 | Markov Random Fields | H.R. Küünsch | 1987 |
8 | Experimental Design Package | Dr. A. Baines | 1988 |
9 | Itô Calculus | W.S. Kendall | 1989 |
10 | Statistical Image Analysis | C. Jennison | 1990 |
11 | Shape Analysis, Landmarks and Biomedical Imaging | F.L. Bookstein | 1991 |
12 | Shape and Image Analysis for Industry and Medicine | C.R. Goodall | 1992 |
13 | Shape Recognition in 2D and 3D Imaging | M.I. Miller | 1993 |
14 | Medical Imaging: Shape and Visualization | S. Pizer | 1994 |
15 | Current Issues in Statistical Shape Analysis | F.L. Bookstein, J. Gower, P.J. Green, D.G. Kendall | 1995 |
16 | Image Fusion and Shape Variability Techniques | Dr. A. Guéziec, V.E. Johnson, J.J. Koenderink, D. Terzopoulos | 1996 |
17 | The Art and Science of Bayesian Image Analysis | U. Grenander, V.E. Johnson, M. Titterington | 1997 |
18 | Spatial-Temporal Modelling and its Applications | A. Blake, Sir David Cox, D.C. Hogg, C. Taylor | 1999 |
19 | The Statistics of Directions, Shapes and Images | J. Besag, W.S. Kendall, J.V. Kittler, A. Rosenfeld | 2000 |
20 | Functional and Spatial Data Analysis | A. Baddeley, M. Berman, B.W. Silverman, C.K. Wikle, K. Worsley | 2001 |
21 | The Statistics of Large Datasets: Functional and image data, bioinformatics and data mining | G. J.Barton, L. Edler, Dr M.J.K Gales, D.J. Hand | 2002 |
22 | Stochastic Geometry, Biological Structure and Images | C. Bystroff, Dr W. Gilks, J. Hein, A. Lesk, D. Stoyan | 2003 |
23 | Bioinformatics, Images and Wavelets | M.J.E. Sternberg, G.P. Nason | 2004 |
24 | Quantitative Biology, Shape Analysis, and Wavelets | P.J. Green, V.E. Johnson, Sir J. Kingman, A.F. Neuwald | 2005 |
25 | Interdisciplinary Statistics and Bioinformatics | B.D. Athey, J. Besag, Sir D.R. Cox, J.M. Goodfellow | 2006 |
26 | Systems Biology & Statistical Bioinformatics | S. Tavaré, A. Tramontano, G.M. Crippen | 2007 |
27 | The Art and Science of Statistical Bioinformatics | M. Levitt, Z. Yang, A. Trouvé | 2008 |
28 | Statistical Tools for Challenges in Bioinformatics | S. Richardson, D. Wild, Dr. W. Taylor, Dr. D. Theobald | 2009 |
29 | High-throughput Sequencing, Proteins and Statistics | T. Speed, E. Wit, G. McLachlan | 2010 |
30 | Next Generation Statistics in Biosciences | W.S. Kendall, C.A. Orengo, Y. Zhang | 2011 |
31 | New Statistics and Modern Natural Sciences | D. Wilkinson, J. Haslett, Z. Ghahramani | 2012 |
32 | Statistical Models and Methods for non-Euclidean Data with Current Scientific Applications | A. Azzalini, C. Deane, M. Hastings, C. Jones, P. Jupp, C. Rueda, A. Wood | 2013 |
33 | Geometry-Driven Statistics and its Cutting Edge Applications: Celebrating Four Decades of Leeds Workshops | F. Bookstein, C. Bowman, C. Deane, I. Dryden, C. Goodall, P. Green, T. Hamelryck, S. Huckemann, P. Jupp, A. Laha, J.S. Marron, C. Rueda |
2015 |
34 | Biostatistics and machine learning methods in omics research, joint with the EU MIMOmics network | F. Agakov, H. Battey, G. Bianconi, T. Burzykowski, A. Conesa, H. Guo, W. Hide, N. Intrator, P. Lio, E. Mosca, R. Pfeiffer, D. Remondini, J. Scealy, H. Uh, W. van Wieringen |
2017 |
35 | Big Data: On Time and Space | A. Frangi, I. Ionita-Laza, H. Le, K. Mardia, V. Rondeau | 2019 |
36 | Modern Statistics for Interdisciplinary Omics and Big Data, joint with the EU IMforFUTURE network | M. Girolami, H. Li, J. Scealy, C. van Duijn | 2021 |
37 | New Faces of Statistical Learning and Beyond | A. Tosi, E. Konukoglu, J. Firth | 2024 |