CV
Education
- B.S. in GitHub, GitHub University, 2012
- M.S. in Jekyll, GitHub University, 2014
- Ph.D in Version Control Theory, GitHub University, 2018 (expected)
Work experience
- Summer 2015: Research Assistant
- Github University
- Duties included: Tagging issues
- Supervisor: Professor Git
- Fall 2015: Research Assistant
- Github University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
Skills
- Skill 1
- Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
- Skill 3
Publications
Talks
Oracle inequalities for adaptive context trees
at Statistics seminar, Ecole normale supérieure, Paris, France
Adaptive context trees for string modelling
at Statistics and genome seminar, Evry university, Evry, France
Universal prediction with double mixture estimators
at Garchy Seminar on Mathematical Statistics and Applications, Garchy, France
Adaptive context trees and text categorization
at Mathematical foundations fo natural Language modeling IMA workshop, University of Minnesota, Minneapolis, USA
Text categorization using adaptive context trees
at Second International Conference on Intelligent Text Processing and Computational Linguistics (CICLing '01), Mexico City, Mexico
Generalization error bounds for aggregated classifiers
at Department of Mathematics, Paris South University, Orsay, France
Statistical methods for language modelling (PhD defense)
at Department of Mathematics, Ecole normale supérieure, Paris, France
Statistical sequence modelling
at Bioinformatics Center colloquim, Kyoto University, Kyoto, Japan
Mathematics and post-genomics
at Science and Technology workshop 2001, French embassy in Tokyo, Tokyo, Japan
Kernels for discrete objetcs
at Computational Biology Research Center, Tokyo, Japan
SVM prediction of signal peptide cleavage site using a new class of kernels for strings
at Pacific Symposium on Biocomputing (PSB'02), Lihue, Hawaii, USA
SVMs in bioinformatics
at Mathematical modeling and statistical analysis in biomedical research Symposium, Hiroshima university, Hiroshima, Japan
SVMs in bioinformatics
at Genetic knowledge science lab seminar, JAIST, Kanazawa, Japan
Kernel methods in bioinformatics
at Bioinformatics center colloquim, Kyoto University, Kyoto, Japan
Support vector machines and applications in bioinformatics
at Graduate school of mathematics seminar, Kyushu University, Fukuoka, Japan
Data mining the proteome in Reproducible Kernel Hilbert Spaces
at Research Institute for Mathematical Science seminar, Kyoto University, Kyoto,Japan
SVM, kernel methods and bioinformatics (3 days)
at Human genome center, University of Tokyo, Tokyo, Japan
Extracting correlations between pathways and microarray data
at 4th BioPathways Consortium Meeting, Edmonton, Canada
A tree kernel to analyse phylogenetic profiles
at 10th International Conference on Intelligent Systems for Molecular Biology (ISMB '02), Edmonto, Canada
Méthodes à noyau en bioinformatique
at INSA Toulouse, Toulouse, France
Extracting active metabolic pathways from gene expression data using kernel CCA
at Statistical learning, theorey and application conferences at CNAM, Paris, France
Méthodes à noyau en bioinformatique
at INRIA Rhône-Alpes, Grenoble, France
Graph-driven features extraction from microarray data using diffusion kernels and kernel CCA
at NIPS'02 conference, Vancouver, Canada
Probabilistic kernels
at Computer Science Departments, Paris South University, Orsay, France
Methodes a noyau en bio-informatique
at Statistics and genome seminar, Evry University and INRA, Jouy-en-Josas, France
Probabilistic kernels for structured objects
at Statistical Learning in Classification and Model Selection workshop, EURANDOM, Eindhoven, The Netherlands
DNA microarrays and Kernel methods in computational biology
at Mathematical aspects of molecular biology : Towards new constructions workshop, Nara, Japan
Monitoring the activity of metabolic pathways with DNA chips
at Statistical analysis of DNA microarray data workshop, Toulouse, France.
Kernel methods and applications in computational biology
at SABRES statistics seminar, University Bretagne South, Vannes, France.
Kernel methods in computational biology
at INRIA, Roquencourt, France.
Probabilistic kernels for structured objects
at Department of statistics, UC Davis, Davis, CA, USA.
Kernel methods in computational biology: Three examples
at Computer science division, UC Berkeley , Berkeley, CA, USA.
Kernels for phylogenetic trees
at Geometric models of biological phenomena workshop, American Institute of Mathematics, Palo Alto, CA, USA.
Kernel methods in computational biology: tree examples
at Center for applied mathematics, Ecole Polytechnique, Palaiseau, France.
Support vector machines and applications in bioinformatics.
at Centre de bio-informatique, Sanofi, Toulouse, France.
Kernel methods in computational biology: two examples
at Molecular Physiology of lower Eukaryots group seminar, INSA Toulouse, Toulouse, France.
Kernel methods in computational biology
at Le Mirail Toulouse University, Toulouse, France.
Extracting metabolic pathways activity from microarray data
at Bioinformatics seminar, Institut Curie, Paris, France.
Krigeage sur graphes et groupes
at Journées de Géostatistiques, Ecole des Mines de Paris, Fontainebleau, France.
Extracting metabolic pathway activity from microarray data
at European Conference on Computational Biology (ECCB 2003), Paris, France.
Support vector machines in bioinformatics: three examples
at Machine Learning in Bioinformatics industrial workshop, Bruxelles, Belgium
SVM, kernel methods, and applications in bioinformatics
at Machine Learning in Bioinformatics conference, Bruxelles, Belgium
SVM, kernel methods and applications in bioinformatics
at Bioinformatics Center, Kyoto University, Kyoto, japan
SVM, kernel methods and applications in bioinformatics
at Bioinformatics seminar, Ghent University, Ghent, Belgium
Statistical learning theory, SVMs, and Bioinformatics
at Department of Computer science, Ecole normale supérieure, Paris, France
SVMs, kernel methods, and applications in bioinformatics
at Statistics seminar, Paris 6 University, Paris, France
Inférence sur graphes et groupes
at Spatial statistics seminar, INAPG, Paris, France
SVMs, kernel methods, and applications in bioinformatics
at Geometrica seminar, INRIA, Nice, France
SVMs, kernel methods, and applications in bioinformatics
at MODBIO seminar, LORIA, Nancy, France
Extracting metabolic pathway activity from microarray data
at Functional genomics seminar, CEA, Evry, France
Inference on graphs with support vector machines
at Marketing seminar, INSEAD, Fontainebleau, France
Extracting pathway activity from gene expression data
at Saminar at the Max Planck Institut für Informatik, Saarbrücken, Germany
Kernel Methods in Computational Biology
at The learning workshop, Snowbird, USA
Network inference and inference on networks
at Department of Genome Sciences, University of Washington, Seattle, USA
Metabolic networks: activity detection and inference
at Gene regulatory network workshop, INRIA, Grenoble, France
Metabolic networks: activity detection and inference
at Advanced microarray data analysis course, Center for Biological Sequence Analysis, Elsinore, Denmark
Analysis and inference of gene networks from genomic data
at SIG Bioinformatics and Statistical Physics, Glasgow, UK
Un noyau d’alignement local pour la classification de séquences biologiques
at 11èmes Rencontres de la Société Francophone de Classification, Bordeaux, France
Analysis and inference of metabolic networks
at EBI Industry Program Meeting, European Bioinformatics Institute, Cambridge, UK
Analysis and inference of gene networks from genomic data
at Complex stochastic systems in biology and medicine workshop, Ludwig-Maximilians University, Munich, Germany
Analysis and inference of gene networks from genomic data
at Statistics seminar, Institute of Statistical Mathematics, Tokyo, Japan
Analysis and inference of gene networks from genomic data
at Bioinformatics Center, Kyoto University, Kyoto, Japan
Analysis and inference of gene networks from genomic data
at Bioinformatics seminar, INRA, Jouy-en-Josas, France
Kernel methods in computational biology
at Habilitation à Diriger les Recherches defense, Ecole des Mines de Paris, Paris, France
Supervised graph inference
at NIPS'04 conference, Vancouver, Canada
Kernel methods in computational and systems biology
at Symposium on perspectives in computational and theoretical biology, Shanghai, P.R. China
Supervised graph inference
at Séminaire parisien de statistiques, Institut Henri Poincaré, Paris, France
Supervised network inference
at 50th NIBB conference on Structure and Dynamics of Complex Biological Networks, Okazaki, Japan
Supervised network inference
at ICPB seminar, Mathematics Institute, University of Warwick, Warwick, UK
Voyage au coeur du génome
at Science for all seminar, Ecole des Mines de Paris, Fontainebleau, France
Supervised gene network inference
at Journees de Statistiques de ls SFdS, Pau, France
Analyse du transcriptome
at JOBIM'05 conference, Lyon, France
Supervised gene network inference
at Institute for Genomics and Bioinformatics seminar, UC Irvine, Irvine, USA
Support vector machines and kernel methods in bioinformatics
at Bioinformatics Center Lecture, Kyoto University, Kyoto, Japan
Motif finding in promoter region with support vector machines
at Bioinformatics Center Seminar, Kyoto University, Kyoto, Japan
Supervised gene network inference
at Seminar of applied statistics, University of Montpellier, Montpellier, France
Supervised gene network inference
at Reverse modeling of biological regulatory networks: expectation and limitations workshop, Evry, France
Kernels for biological sequences
at Kernel methods and structured domain workshop, NIPS'05, Whistler, Canada
Supervised gene network inference
at Bioinformatics: algorithms, structures and statistics workshop, Ecole Polytechnique, Palaiseau, France
Machine learning approaches for reconstruction of genetic networks
at Workshop on Knowledge Discovery and Emergent Complexity in Bioinformatics (KBECB 2006), Ghent, Belgium.
Classification of biological sequences with kernel methods
at CMLA workshop, Ecole Normale Superieure de Cachan, Cachan, France
Analysis of microarray data with pathway information
at Seminar of the Centre d'Ecologie Cellulaire, Faculté de médecine Pitié-Salptrière, Paris, France
Virtual screening with support vector machines
at Seminar at the Pierre Fabre Institute of Drug Sciences and Technologies, Toulouse, France
Regularization of kernel methods by decreasing the bandwith of the Gaussian kernel
at Mathematical foundations of learning theory conference, Ecole normale supérieure, Paris, France
Spectral approaches to integrate gene expression and gene networks
at ESBIC meeting, Institut Curie, Paris, France
Kernel methods in bioinformatics
at Machine Learning Summer School (MLSS 2006), Taipei, Taiwan
Regularization of kernel methods by decreasing the bandwidth of the Gaussian kernel
at Machine Learning Summer School (MLSS 2006), Taipei, Taiwan
Classification of biological sequences with kernels
at International Conference on Grammatical Inference (ICGI 2006), Tokyo, Japan
Kernels and kernel methods for biological sequences
at Current Challenges in Kernel Methods workshop (CCKM'06), Brussel, Belgium
QSAR and virtual screening with support vector machines
at Chimiometrie'06 conference, Paris, France
Metric learning pairwise kernel for graph inference with SVM
at Open problems in computational biology workshop, NIPS'06, Whistler, Canada
Motif finding in promoter region with support vector machines
at Journée thématique Promoteurs, Ouest Génopole, IRIS, Rennes, France
Statistical learning on graphs and groups
at International conference on Embeddings of Graphs and Groups into Hilbert and Banach spaces with applications, EPFL, Lausanne, Switzerland
Supervised inference of biological networks from heterogeneous genomic data
at ENFIN NoE Meeting, Genoscope, Evry, France
Kernels methods for strings and graphs
at Bioinformatics Center, Kyoto University, Kyoto, Japan
Supervised inference of biological networks
at Institute for Infocomm Research, Singapore
Classification of gene expression data using gene networks
at Statistics and Genome workshop, University of Nice, Nice, France
Statistical learning with graphs
at Journées de statistiques du sud, University of Nice, Nice, France
Classification of gene expression data using gene networks
at Second Systems Biology workshop, Paris 5 University, Paris, France
Classification of gene expression data using gene networks
at Systems Biology seminar, Institut Pasteur, Paris, France
Regularization of kernel methods by decreasing the bandwidth of the Gaussian kernel
at Seminar statistics and probability, University of Lille, Lille, France
Kernel matrix regression
at The 12th International Conference on Applied Stochastic Models and Data Analysis (ASMDA'07), Chania, Greece
A kernel for time series
at Signal, pattern recognition and kernel methods workshop, Telecom Paris, Paris, France
Graph kernels and applications in chemoinformatics
at 6th IAPR -TC-15 Workshop on Graph-based Representations in Pattern Recognition (GbR 2007), Alicante, Spain
Supervised reconstruction of biological networks
at JOBIM'07 conference, Marseille, France
QSAR and virtual screening with support vector machines
at VI Colloquium Chemiometricum Mediterraneum, Saint-Maximin, France
Supervised inference of biological networks
at Machine Learning in Systems Biology Conference (MLSB'07), Evry, France
Kernels for strings and applications in bioinformatics
at Institute of Mathematicsl Statistics open forum, Tokyo, Japan
Statistical learning with graph kernels
at The International Workshop on Data Mining and Statistical Science (DMSS'07), Tokyo, Japan
Collaborative filtering with attributes
at The 2nd Workshop on Machine Learning and Optimization at the ISM, Tokyo, Japan
QSAR and virtual screening with support vector machines
at Tokyo Institute of Technology, Tokyo, Japan
Virtual screening with support vector machines
at Multimodal Project Meeting, National Institute of Informatics, Tokyo, Japan
The context tree weighting kernel
at Context tree models workshop, Telecom Paris, Paris, France
Kernel methods for QSAR and virtual screening
at 10th European Symposium on Statistical Methods for the Food Industry (AGROSTAT'08), Louvain-la-Neuve, Belgium
Statistical learning on graphs
at Seminar of Probability, Institut Joseph Fourier, Grenoble, France
Some contributions of machine learning to bioinformatics
at cBio seminar, Memorial Sloan Kettering Cancer Center, New York, USA
Collaborative filtering with attributes
at The learning workshop, Snowbird, USA
Machine learning in computational biology
at Informatics for Biology course, Institut Pasteur, Paris, France
How to infer gene networks from gene expression data?
at The Third Conference on Systems Biology, University Paris Descartes, Paris, France
Inference of biological networks with supervised machine learning
at Statistical modelling and analysis of biological network INSERM workshop (atelier 184), Saint-Raphael, France
Inference of biological networks with supervised machine learning
at U900 seminar, Institut Curie, Paris, France
Collaborative filtering with attributes
at Machine learning seminar, Xerox Research Centre Europe, Grenoble, France
Collaborative filtering in Hilbert spaces with spectral regularization
at Second Canada-France congress of mathematics, Montreal, Canada
A path following approach for graph matching
at National Institute of Informatics, Tokyo, Japan
Inference of biological networks with supervised machine learning
at Bioinformatics Center, Kyoto University, Kyoto, Japan
Inference of biological networks with supervised machine learning
at Institute of Statistical Mathematics, Tokyo, Japan
Inference of missing edges in biological networks
at Statistics and modelling of networks workshop, Rennes, France
Inference of missing edges in biological networks
at Telecom ParisTech, Paris, France
Some contributions of machine learning to bioinformatics
at Laboratoire d'informatique, University of Laval, Quebec, Canada
Infering and using biological networks
at Research Centre, Centre hospitalier de l'Université Laval (CHUL), Quebec, Canada
Inference of missing edges in biological networks
at Bristol University, Bristol, UK
Machine learning in postgenomics
at Atelier statistique de la SFDS, Paris, France
Analyzing the transcriptional response of P. falciparum to drugs and stress
at Bioinformatics of plasmodium falciparum workshop, Paris, France
Some contributions of machine learning to bioinformatics
at Centre for applied mathematics, Ecole Polytechnique, Palaiseau, France
Machine learning for cancer informatics
at Scientific and Medical Days, Institut Curie, Paris, France
In silico chemogenomics with support vector machines
at MedChem'09 Europe conference, Berlin, Germany
Some contributions of machine learning to bioinformatics
at Mathematics, evolution and genome seminar, University of Provence, Marseille, France
Inference of missing edges in biological networks
at MAP5 colloquium, University of Paris Descartes, Paris, France
Kernel design and learning
at Symposium on Learning and Data Science (SLDS'09), University Paris Dauphine, Paris, France
In silico virtual screening for drug discovery
at Mathematics and industry workshop, IHES, Bures-sur-Yvette, France
Including prior knowledge in shrinkage estimators for genomic data
at Statistical advances in Genome-scale Data Analysis workshop, Ascona, Switzerland
Supervised classification for structured data: applications in bio- and chemoinformatics
at The analysis of patterns summer school, Cagliari, Italy
Inference of biological networks
at Advances in the Theory of Control, Signals, and Systems, with Physical Modeling workshop, Bernoulli center, EPFL, Lausanne, Switzerland
Inferring and using biological networks
at 6th international workshop on computational systems biology (WCSB'09), Aarhus, Denmark
Global alignment of protein-protein interaction networks by graph matching methods
at Bioinformatics Center, Kyoto University, Kyoto, Japan
Global alignment of protein-protein interaction networks by graph matching methods
at Department of Informatics, Kyushu University, Fukuoka, Japan
Inferring and using biological networks
at Human Genome Center, Institute of Medical Science, Tokyo University, Tokyo, Japan
Including prior knowledge in shrinkage estimators for genomic data
at The Institute of Statistical Mathematics, Tokyo, Japan
Kernel methods for virtual screening and in silico chemogenomics
at Computational Biology Research Center, Tokyo, Japan
Supervised classification for structured data: applications in bio- and chemo-informatics
at The third school on Analysis of Patterns, Cagliari, Italy
Machine learning in bioinformatics and drug discovery
at Biology of cellular systems graduate course, Ecole normale supérieure, Paris, France
Collaborative filtering in Hilbert spaces with spectral regularization
at Journees STAR, IRISA, Rennes, France
Machine learning in bioinformatics and drug discovery
at Workshop on Bioinformatics for Medical and Pharmaceutical Research, Institut Curie, Paris, France
Collaborative filtering in Hilbert spaces with spectral regularization
at Statistics seminar, Paris 6-7 Universities, Paris, France
Some contributions of machine learning in bioinformatics
at Department of Computer Science, Ecole normale supérieure, Paris, France
Collaborative filtering in Hilbert spaces with spectral regularization
at Center for Statistics, Goettingen University, Goettingen, Germany
Designing and combining kernels: some lessons learned from bioinformatics
at Understanding multiple kernel learning methods workshop, NIPS'09, Whistler, Canada
Machine learning for ligand-based virtual screening and chemogenomics
at In silico discovery of molecular probes and drug-like compounds: Success & Challenges INSERM workshop, Saint-Raphael, France
Including prior knowledge in shrinkage estimators for genomic data
at Systems and Modeling Seminar, University of Liege, Liege, Belgium
Machine learning for ligand-based virtual screening and chemogenomics
at 2nd Strasbourg Summer School on Chemoinformatics, Obernai, France
Shrinkage classifiers for genomic and chemical data
at 1st spring school on machine learning (EPAT'10), Cap Hornu, France
Including prior knowledge in shrinkage classifiers for genomic data
at Statistical Genomics in Biomedical Research workshop, Banff International Research Station (BIRS), Banff, Canada
Including prior knowledge in machine learning for genomic data
at 10th annual International Workshop on Bioinformatics and Systems Biology (IBSB'10), Kyoto University, Kyoto, Japan.
Multiple change-point detection in multiple signals
at Mathematical Statistics and Applications Workshop, Frejus, France.
Some challenges in high-throughput high-content phenotypic screening
at From phenotypes to pathways ESF exploratory workshop, Lucy Cavendish College, Cambridge, UK
Some topics on machine learning in bioinformatics
at 50th workhop on Optimization, machine learning and bioinformatics, Centre Ettore Majorna for Scientific Culture, Erice, Italy
Statistical inference for complex systems
at U900 seminar, Institut Curie, Paris, France
Machine learning in computational and systems biology
at Malaysia Genome Institute, Bangi Selangor, Malaysia
Inference of biological networks: from de novo to supervised approaches
at University College London, London, UK
On feature selection and pattern detection in high dimension
at Point de vue seminar, Paris 7 University, Paris, France
Including prior knowledge in machine learning for genomic data
at StatLearn'11, Grenoble, France
Genomique et apres-genome: promesses et defis
at Public talk, Theatre de Fontainebleau, Fontainebleau, France
Machine learning for cancer genomics
at Informatics and mathematics sciences: interactions with biomedical sciences workshop, Paris, France
Machine learning in bioinformatics
at Biointelligence symposium, Sophia Antipolis, France
Inference of gene regulatory networks
at From phenotypes to pathways ESF exploratory workshop, Lucy Cavendish College, Cambridge, UK
Machine learning and feature selection in bioinformatics
at Machine learning for neuroimaging workshop, Marseille, France
Machine learning in cancer genomics
at Mathematics and Systems seminar, Mines ParisTech, Paris, France
Machine learning in cancer genomics
at Machine learning seminar, UCL, Louvain-la-Neuve, Belgium
Machine learning in cancer genomics
at Modeling and analysis in the life sciences conference, Tokyo, Japan
Group lasso for genomic data
at Department of statistics, University of Oxford, Oxford, UK
Machine learning with prior knowledge for genomic data
at UCLA Bioinformatics seminar, Los Angeles, CA, USA
Machine learning with prior knowledge for genomic data
at Statistics and genomics seminar, UC Berkeley, Berkeley, CA, USA.
Group lasso for genomic data
at IMA workshop on Machine Learning: Theory and Computation, University of Minnesota, Minneapolis, USA
Structured feature selection for genomic data
at 8th World Congress in Probability and Statistics, Istanbul, Turkey
Structured feature selection for genomic data
at 2012 Sapporo Workshop on Machine Learning and Applications to Biology, Sapporo, Japan
Machine learning for predictive biology
at From phenotypes to pathways 2012 workshop, Lucy Cavendish College, Cambridge, UK
Learning with structured sparsity in computational biology
at The 15th information-based inductive science workshop (IBIS'12), Tsukuba University, Tokyo, Japan
Fast sparse methods for genomic data
at Optimization and statistical learning workshop (OSL'13), Les Houches, France
Fast sparse methods for genomic data
at Chalmers University, Gothenburg, Sweden
Fast sparse methods for genomic data
at Congress SMAI'13, Seignosse, France
Learning with structured sparsity in computational biology
at Eighth IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB'13), Nice, France
Learning with structured sparsity in computational biology
at Departments of Informatics, Kyoto University, Kyoto, Japan
Flip-Flop: fast lasso-based isoform prediction from RNA-Seq data
at Bioinformatics Center, Kyoto University, Kyoto, Japan
On segmentation of DNA copy number profiles
at 13th Annual International Workshop on Bioinformatics and Systems Biology (IBSB'13), Kyoto, Japan
Flip-Flop: fast lasso-based isoform prediction from RNA-Seq data
at 2013 International Workshop on Machine Learning and Applications in Biology (MLAB'13), Sapporo, Japan
Machine learning in computational biology (the frequentist approach)
at Machine Learning for Personalized Medicine summer school, Tuebingen, Germany
On segmentation of DNA copy number profiles
at Genome Sciences seminar, University of Washington, Seattle, USA
Machine learning for personalized Medicine
at ML meetup, Paris, France
On segmentation of DNA copy number profiles
at Biostatistics seminar, UC Berkeley, Berkeley, USA
The group fused Lasso for multiple change-point detection
at Inference for Change-Point and Related Processes workshop, Isaac Newton Institute for Mathematical Sciences, Cambridge, UK
Learning with kernels: an introduction
at Kernel methods for big data workshop, Polytech'Lille, Lille, France
Le nombre d’or
at Gouter scientifique pour 10-15 ans, Mines ParisTech, Fontainebleau, France
Machine learning for personalized medicine
at MascotNum workshop, ETH Zurich, Zurich, Switzerland
Kernel methods and computational biology
at Machine Learning Summer School, Reykjavik University, Reykjavik Iceland
Machine learning for personalized medicine
at SeMoVi seminar, Grenoble, France
Machine learning for personalized medicine
at 46th annual days of Statistics, Rennes, France
Inferring a genome 3D structure and how it is related to gene regulation in malaria parasite
at ABS4NGS project meeting, Lyon, France
Machine learning for personalized genomics
at Paris-Saclay Center for Data Science kick-off meeting, Saclay, France
Inferring a genome 3D structure and how it is related to gene regulation in malaria parasite
at RADIANT project meeting, EMBL, Heidelberg, Germany
Machine learning for personalized medicine
at Genentech, South San Francisco, USA
Reconstructing the 3D architecture of the genome
at CEA, Grenoble, France
New matrix norms for structured matrix estimation
at Sparse Representations, Numerical Linear Algebra, and Optimization workshop, BIRS, Banff, Canada
Machine learning for personalized medicine
at Grenoble Computer Science Laboratory, Grenoble, France
Machine learning for personalized medicine
at PROSPECTOM workshop, Grenoble, France
New matrix norms for structured matrix estimation
at Optimization and Statistical Learning workshop (OSL'15), Les Houches, France
Structured feature selection
at U900 lab meeting, Institut Curie, Paris, France
Machine learning for personalized genomics
at Computational Biology Institute, Montpellier, France
Machine learning for personalized genomics
at C3BI kick-off meeting, Institut Pasteur, Paris, France
A Convex Formulation for Joint RNA Isoform Detection and Quantification from Multiple RNA-Seq Samples
at Statistics and Genomics seminar, UC Berkeley, Berkeley, USA
Learning in high dimension
at BIRS workshop on Statistical and Computational Challenges In Bridging Functional Genomics, Epigenomics, Molecular QTLs, and Disease Genetics, Banff, Canada
Machine Learning for Toxicogenetics and Drug Response Prediction
at Festival of Genomics, San Mateo, USA
Can big data cure cancer?
at Miller Institute, UC Berkeley, Berkeley, USA
Learning from rankings
at Nonparametric Methods for Large Scale Representation Learning workshop, NIPS'15, Montreal, Canada
Learning from Omics Data
at Computational cancer biology workshop, Simons Institute, UC Berkeley, Berkeley, USA
Patient stratification and cancer prognosis from molecular profiles
at Computational biology seminar, Memorial Sloan Kettering Cancer Center, New York, USA
Machine learning for computational genomics and precision medicine
at Distinguished speaker lecture, KAIST, Daejeon, South Korea
Can big data cure cancer?
at Data Science Colloquium, ENS Paris, Paris, France
Machine learning for precision medicine
at Krupp symposium From Machine Learning to Personalized Medicine, Max Planck Institute, Munich, Germany
Fighting cancer with chinese lanterns
at Les Mathematiques seminar, ENS Paris, Paris, France
Machine learning for patient stratification from genomic data
at Paris Sciences and Data, Institut Curie, Paris, France
Cancer prognosis on the symmetric group
at CFM-ENS data science chair inauguration, ENS Paris, Paris, France
Machine learning for patient stratification from genomic data
at Distinguished speaker colloquium, Max Planck Institute for Informatics, Saarbrücken, Germany
Machine learning for patient stratification from genomic data
at Distinguished speaker seminar, Department of Statistics, University of Oxford, Oxford, UK
Machine learning for precision medicine
at BIG N2N seminar, Ghent University, Ghent, Berlgium
Machine learning for patient stratification from genomic data
at LCQB seminar, Paris 6 University, Paris, France
Cancer stratification from mutation profiles
at BIRS workshop on Statistical and Computational Challenges in Large Scale Molecular Biology, Banff, Canada
Learning on the symmetric group
at StatScale workshop, Lancaster University, Lancaster, UK
ZinbWave, a general and flexible method for signal extraction from single-cell RNA-seq data
at Algorithmic challenges in genomics reunion workshop, Simons Institute, UC Berkeley, Berkeley, USA
Machine learning for cancer precision medicine
at AI and health seminar, National Academy of Medicine, Paris, France
Learning on the symmetric group
at Mathematical methods of modern statistics workshop, CIRM, Luminy, France
Identifying predictive biomarkers in high-dimensional genomic data from randomized clinical trials
at 8th SFdS International Meeting on Statistical Methods in Biopharmacy, Paris, France
Learning on the symmetric group
at 1st France-Japan machine learning workshop, ENS Paris, Paris, France
Machine learning on the symmetric group
at Google Tech talk, Zurich, Switzerland
Graph wavelets to analyze genomic data with biological networks
at Emerging Topics in Biological Networks and Systems Biology symposium, Swedish Collegium for Advanced Study, Uppsala, Sweden
Learning on the symmetric group
at Department of Statistics, Imperial College, London, UK
Machine learning for patient stratification from genomic data
at Neurospin, Saclay, France
A weighted Kendall kernel
at Learning on Distributions, Functions, Graphs and Groups workship, NeurIPS'17, Long Beach, USA
Machine learning for patient stratification from genomic data
at From molecules and cells to human health: ideas and concepts workshop, IHES, Bures-sur-Yvette, France
Perm2vec
at Deep learning: theory, algorithms and applications, RIKEN AIP, Tokyo, Japan
Patient stratification from somatic mutation profiles using gene networks
at First NCI - Institut Curie Symposium, Institut Curie, Paris, France
Machine learning for precision medicine
at The 14th ICGC/1st ICGC-ARGO Scientific Workshop, Paris, France
The 3D genome
at 3nd GENMED Workshop on Medical Genomics, Institut Pasteur, Paris, France
Machine learning for precision medicine
at 2nd Data Science Summer School, Ecole Polytechnique, Palaiseau, France
Some challenges with single-cell gene expression data
at Joint ICML and IJCAI Workshop on Computational Biology, Stockholm, Sweden
Learning with permutations
at Takeuchi lab seminar, Nagoya Institute of Technology, Nagoya, Japan
From DNA mutations to embeddings of permutations
at Seminaire des eleves, Orsay University, Orsay, France
Relating Leverage Scores and Density using Regularized Christoffel Functions
at Learning theory workshop, Google, Mountain View, USA
Learning from permutations
at Journees des prix mathematiques de l'Academie des Sciences, Rennes, France
Machine learning for precision medicine
at Ethics, Law and New applications of AI seminar, Ecole Polytechnique, Saclay, France
Machine learning on the symmetric group
at Artificial intelligence and physics, Institut Pascal, Orsay, France
Machine learning on the symmetric group
at Imaging and machine learning workshop, Institut Henri Poincaré, Paris, France
Machine learning for precision medicine
at Chaire Pari seminar, Paris, France
Machine learning for precision medicine
at The future of epidemiology in the big data era symposium, College de France, Paris, France
Machine learning for precision medicine
at Google Accra inaugural AI Symposium, Accra, Ghana
Post-Selection Inference for Nonlinear Feature Selection
at DALI'19, San Sebastian, Spain
Network inference from single cell data
at EMBO workshop Network inference in biology and disease, Naples, Italy
Learning from ranks, learning to rank
at Data Science Day, MINES ParisTech , Paris, France
Jointly embedding multiple single-cell omics measurements
at Cellimageomics workshop, Paris, France
Single-cell genomics: Learning gene networks and integrating multi-omics data
at LifeTime unconference 2.0, Montpellier, France
Learning from ranks, learning to rank
at SOLARIS workshop, INRIA, Grenoble, France
Computational analysis of tumour heterogeneity, from bulk to single-cell genomics
at ICB seminar, Helmholtz Center, Munich, Germany
Learning from ranks, learning to rank
at Statistics and Computation workshop at the Alan Turing Institute, London, UK
Learning from single-cell genomic data
at ICBBB'20, Kyoto, Japan
Computational analysis of tumour heterogeneity, from bulk to single-cell genomics
at Bioinformatics Center, Kyoto University, Kyoto, Japan
Differentiable ranking and sorting
at CIS colloquim, EPFL (virtual), Lausanne, Switzerland
Differentiable ranking and sorting
at Google Research India AI summer school (virtual), Bengalore, India
Computational analysis of tumour heterogeneity, from bulk to single-cell genomics
at Computational medicine and bioinformatics seminar, University of Michigan (virtual), Ann Arbor, USA
Deep embedding of biological sequences
at AI and data science for biology symposium, Sorbonne University, Paris, France
Machine learning against cancer
at PAISS summer school (virtual), Paris, France
Deep embedding of biological sequences
at JOBIM'21 (virtual), Paris, France
Machine learning against cancer
at 4th course on Computational Systems Biology of Cancer, Institut Curie, Paris, France
Machine learning for single-cell omics data
at When AI meets Biology: a workshop (virtual), Lyon, France
Framing RNN as a kernel method: a neural ODE approach
at Learning theory workshop, Google (virtual), New-York, USA
Deep embedding of biological sequences
at Mathematical Institute for Data Science seminar, Johns Hopkins University (virtual), Baltimore, USA
Machine learning against cancer
at #FocusAI conference, Institut Henri Poincare, Paris, France
Machine learning for single cell omics
at ELLIS Life / NCT Data Science seminar, Heidelberg University (virtual), Heidelberg, Germany
Deep learning for biological sequences
at Computational Biology Department Days, Pasteur Institute, Les Barils, France
Machine learning against cancer
at Sorbonne Center for Artificial Intelligence (SCAI), Sorbonne University (virtual), Paris, France
Computational analysis of tumor heterogeneity
at The 25th Human Genome meeting (HGM'22), Tel Aviv, Israel
Learning to align biological sequences
at The third annual workshop of the Koret - Berkeley - Tel Aviv University Initiative, Tel Aviv, Israel
Deep learning for biological sequences
at International Genome Graph Symposium (IGGSy'22), Ascona, Switzerland
AI in health and genomics
at 5th course on breast cancer, from clinics to biology, Institut Curie, Paris, France
Deep learning for biological sequences
at MLFPM symposium, Munich, Germany
AI in medicine, new approaches
at National Academy of Pharmacy, Paris, France
AI in medicine and drug discovery
at MathTech meeting, Bures-sur-Yvette, France
Deep learning for biological sequences
at University of Toronto, Toronto, Canada
Large language models for DNA and proteins
at Institut Pasteur symposium on AI in biology and health, Paris, France
Teaching
Service and leadership
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