members:grigaill:welcome
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members:grigaill:welcome [2019/12/11 09:39] Guillem [Guillem Rigaill] |
members:grigaill:welcome [2025/08/07 09:26] (current) Guillem [A Few Recent Publications] |
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| - | <wrap first column> {{:members:grigaill:photo_gr.png?150|}} </wrap> | + | <wrap first column> {{:members:grigaill:photoglm.png?150|}} </wrap> |
| - | <wrap second colum> Researcher at INRA (CR), Computational Statistics for Biology \\ | + | <wrap second colum> **Senior research scientist at INRAE** (aka directeur de recherche). \\ |
| - | I work in two labs: \\ | + | Research interests: Machine Learning, Statistics, and Applications to Molecular Biology. \\ |
| - | 1) Laboratoire de Mathématiques et Modélisation d'Évry (LaMME) \\ | + | I work between a statistics team and a bioinformatics team: \\ |
| - | 2) Genomics Networks Team, Institut des Sciences des Plantes de Paris-Saclay (IPS2) \\ | + | 1) [[http://www.math-evry.cnrs.fr/sg/welcome|Stat & Genome]], Laboratoire de Mathématiques et Modélisation d'Évry (LaMME) \\ |
| + | 2) [[http://ips2.u-psud.fr/en/research/pmin-department-plant-microbe-interactions-and-networks-biotic-interactions/gnet-genomics-networks.html|Genomics Networks Team]], Institut des Sciences des Plantes de Paris-Saclay (IPS2) \\ | ||
| ☎ +33 (0) 1 64 85 35 44 \\ | ☎ +33 (0) 1 64 85 35 44 \\ | ||
| - | <firstname.lastname@inra.fr> \\ | + | <firstname.lastname@inrae.fr> \\ |
| - | {{:members:grigaill:rigaill_cv_en.pdf|Curriculum Vitae}} \\ | + | {{:members:grigaill:rigaill_cv_en092020.pdf|Curriculum Vitae}}\\ |
| - | {{:members:grigaill:publications.pdf|List of publications}} \\ | + | [[https://scholar.google.com/citations?user=Ve7EEQgAAAAJ&hl=en|List of publications on Google Scholar]] \\ |
| + | [[https://orcid.org/0000-0002-7176-7511|ORCID]] | ||
| </wrap> | </wrap> | ||
| </WRAP> | </WRAP> | ||
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| ===== Research Themes ===== | ===== Research Themes ===== | ||
| - | My research focuses on the development of biostatistical models, statistical methods and algorithms for the analysis | + | My research focuses on the development of statistical models, statistical methods, and algorithms for the analysis |
| - | and interpretation of high throughput biological data. | + | and interpretation of high-throughput biological data. |
| 1. Modeling and inferring dependence in big data settings | 1. Modeling and inferring dependence in big data settings | ||
| * Models: Multiple changepoints, Clustering, Regression | * Models: Multiple changepoints, Clustering, Regression | ||
| - | * Methods: Computational statistics, Dynamic Programming, Convex relaxation, Penalized Likelihood | + | * Methods: Dynamic Programming, Convex relaxation, Penalized Likelihood |
| 2. Applications in molecular biology and bioinformatics | 2. Applications in molecular biology and bioinformatics | ||
| - | * DNA copy number, RNA-footprinting, Hi-C, RNA-seq, Gene networks inference | + | * RNA analysis (RNA-seq, RNA-footprinting, RIP-seq...), Chip-Seq, DNA copy-number analysis |
| - | * Practical evaluation of biostatistical tools for genomics | + | * Practical evaluation of statistical tools for genomics |
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| - | ===== Publications ===== | + | ===== A Few Recent Publications ===== |
| - | A full list of my publication is available {{:members:grigaill:publications.pdf|here}}. \\ | + | A list of my publications can be found on [[https://scholar.google.com/citations?user=Ve7EEQgAAAAJ&hl=en|Google Scholar]]. \\ |
| - | Here are a few recent publications: | + | |
| + | *[2025] Online Multivariate Changepoint Detection: Leveraging Links With Computational Geometry. \\ L. Pishchagina, G. Romano, P. Fearnhead, V. Runge and __G. Rigaill__. \\ **Journal of the Royal Statistical Society Series B: Statistical Methodology** [[https://academic.oup.com/jrsssb/advance-article-abstract/doi/10.1093/jrsssb/qkaf046/8223216?utm_source=advanceaccess&utm_campaign=jrsssb&utm_medium=email|Journal]] [[https://arxiv.org/abs/2311.01174|ArXiv]] | ||
| - | * [2019a] Adjacency-constrained hierarchical clustering of a band similarity matrix with application to Genomics. C. Ambroise, A. Dehman, P. Neuvial, G. Rigaill, and N. Vialaneix. In: **Algorithms for Molecular** | + | *[2024] Ms. FPOP: an exact and fast segmentation algorithm with a multiscale penalty. \\ A. Liehrmann, __G. Rigaill__. \\ **Journal of Computational and Graphical Statistics** [[https://www.tandfonline.com/doi/full/10.1080/10618600.2024.2402895|Journal]] and [[https://arxiv.org/abs/2303.08723|ArXiv]] |
| - | * [2019b] New efficient algorithms for multiple change-point detection with reproducing kernels. A. Celisse, G. Marot, M. Pierre-Jean, and G. Rigaill. In: **Computational Statistics and Data Analysis** | + | *[2023] Fast online changepoint detection via functional pruning CUSUM statistics. \\ G. Romano, I.A. Eckley, P. Fearnhead, and __G. Rigaill__. \\ **Journal of Machine Learning Research** [[https://www.jmlr.org/papers/volume24/21-1230/21-1230.pdf|Journal]] and [[https://arxiv.org/abs/2110.08205|ArXiv]] |
| - | * [2018a] Changepoint detection in the presence of outliers. P. Fearnhead and G. Rigaill. In: **Journal of the American Statistical Association** | + | *[2023] DiffSegR: an RNA-seq data driven method for differential expression analysis using changepoint detection. \\ A. Liehrmann, E. Delannoy, A. Launay-Avon, E. Gilbault, O. Loudet, B. Castandet and __G. Rigaill__. \\ **NAR Genomics and Bioinformatics** [[https://academic.oup.com/nargab/article/5/4/lqad098/7369456|Journal]] |
| - | * [2018b] Homoeologous exchanges cause extensive dosage-dependent gene expression changes in an allopolyploid crop. A. Lloyd, A. Blary, D. Charif, C. Charpentier, J. Tran, S. Balzergue, E. Delannoy, G. Rigaill, and E. Jenczewski. In: **New Phytologist** | + | *[2023] Adjusting the adjusted Rand Index: A multinomial story. \\ M. Sundqvist, J. Chiquet, __G. Rigaill__. \\ **Computational Statistics** [[https://link.springer.com/article/10.1007/s00180-022-01230-7|Journal]] [[https://arxiv.org/abs/2011.08708|ArXiv]] |
| + | ===== My Habilitation and Ph.D ===== | ||
| - | * [2016] Synthetic data sets for the identification of key ingredients for RNA-seq differential analysis. G. Rigaill Guillem et al. In: **Briefings in bioinformatics** | + | **Habilitation (a.k.a HDR) in applied Mathematics** in 2020 at the [[https://www.universite-paris-saclay.fr/en/doctoral-schools/hadamard-doctoral-school-mathematics|Hadamard Doctoral School of Mathematics]] |
| - | * [2016] On optimal multiple changepoint algorithms for large data. R. Maidstone, T. Hocking, G. Rigaill and P. Fearnhead. In: **Statistics and Computing** | + | My manuscript (in French) and slides are here: |
| + | * [[https://tel.archives-ouvertes.fr/tel-02955535|HDR-Manuscript]] | ||
| + | * {{:members:grigaill:Pres_18092020.pdf|HDR-Slides}} | ||
| - | * [2015a] Fast tree inference with weighted fusion penalties. J. Chiquet, P. Gutierrez, and G. Rigaill. In: **Journal of Computationnal and Graphical Statistics** | ||
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| - | * [2015b] T. D. Hocking, G. Rigaill, and G. Bourque. PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data. In: Proceedings of The 32nd International Conference on Machine Learning, **ICML** | ||
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| + | **Ph.D.in applied Mathematics** in 2010 at the [[https://abies.agroparistech.fr/|ABIES Doctoral School]] | ||
| + | My manuscript (in English) is here: | ||
| + | * [[https://tel.archives-ouvertes.fr/pastel-00593939|PhD-Manuscript]] | ||
members/grigaill/welcome.1576053567.txt.gz · Last modified: 2019/12/11 09:39 by Guillem
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