جست‌وجوی استاد و پژوهشگر

Hélène Morlonمشاهده پروفایل

استاد

• Ecology
• Evolutionary Biology
• Computational Biology
• +۷ مورد دیگر

Hélène Morlon is a Professor at the Biology Department of École normale supérieure (ENS) - PSL Research University Paris. She leads the Biodiversity Modeling team within the Center for Computational Biology, focusing on integrating ecological and evolutionary processes to explain biodiversity patterns through mathematical and bioinformatics approaches. Specializes in molecular phylogenies, speciation, extinction, and dispersal mechanisms Collaborates with mathematicians, phylogeneticists, and field ecologists Her research reveals non-equilibrium dynamics in biodiversity, challenging classical models by demonstrating speciation rate declines and climate-driven phenotypic evolution. She has developed probabilistic models applied to amphibians, mammals, birds, plants, and microorganisms. Scientific Awards: ERC Consolidator Grant (2013) Chaire d'Excellence en biologie/santé (France Innovation Santé 2030) ERC Advanced Grant (2024) for project PlankDiv Her work bridges macroecology, macroevolution, and conservation biology, with notable contributions to understanding tropical biodiversity gradients and climate impacts on evolutionary rates.

Tom Schrijversمشاهده پروفایل

استاد

• Programming Languages
• Functional Programming
• Type Systems
• +۶ مورد دیگر

Tom Schrijvers is a Professor at the Department of Computer Science in the Faculty of Engineering Science at KU Leuven, Belgium. He leads the Programming Languages Group within the Declarative Languages and Artificial Intelligence (DTAI) research group. His research focuses on programming languages, particularly functional and logic programming, with special emphasis on Haskell, type systems, and algebraic effects. His research interests include: Functional Programming, especially Haskell Type Systems and Type Theory Algebraic Effects and Handlers Logic Programming, particularly Prolog Constraint Programming Domain-Specific Languages Programming Language Theory Prof. Schrijvers' recent research has focused on effect systems, staged programming, and language composition. His work on algebraic effect handlers has been particularly influential, providing new insights into how effects can be modularly composed and handled in functional languages. He has also made significant contributions to the understanding of type classes and their implementation in Haskell. His publications demonstrate a consistent focus on practical applications of programming language theory, with work spanning from foundational type theory to applied domain-specific languages for areas like fluorescence microscopy. His research often bridges the gap between theoretical programming language concepts and practical implementation concerns. Prof. Schrijvers has supervised numerous PhD students to completion, including Pieter Wuille, Benoit Desouter, George Karachalias, Steven Keuchel, Amr Saleh, Alexander Vandenbroucke, and Ruben Pieters. He currently supervises PhD students Klara Mardirosian, César Santos, Gert-Jan Bottu, Koen Pauwels, Birthe van den Berg, and Roger Bosman. His research group has received funding from various sources including EU projects like GRACeFUL. The Programming Languages Group at KU Leuven, which he leads, focuses on functional (Haskell) and logic (Prolog, Datalog, CLP) programming languages, as well as general programming language theory. The group has been active in numerous research projects and collaborations across Europe.

• Machine Learning
• Artificial Intelligence
• Bioinformatics
• +۹ مورد دیگر

Florence d'Alché-Buc is a Professor at Télécom Paris (Institut Polytechnique de Paris), holding an Isaac Newton Institute Simons Chair (2025) and leading the Data Science and Artificial Intelligence for Digitalized Industry & Services (DSAI) Chair. She heads the Image, Data, and Signal Department and is part of the Signal, Statistics, and Learning (S2A) team at the LTCI laboratory. Her research focuses on machine learning, bioinformatics, and industrial applications, emphasizing kernel methods, structured prediction, and reliable AI. Education: Previously a professor at Université d’Evry and deputy director of the IBISC lab. Co-director of the Paris-Saclay Data Science Master and creator of specialized AI programs (e.g., Certificate of Specialized Studies in AI). Research highlights include contributions to operator-valued kernel methods, graph prediction, and frugal AI. She actively collaborates with institutions like Inria, École Polytechnique, and industry partners (Airbus, Engie, etc.). Notable roles: Scientific director of Digicosme Labex, Ellis Fellow, and board member of IVADO (Montreal). Her recent work addresses AI explainability, robustness, and sustainability, including projects on interpretable networks and energy-efficient models.

Hirokatsu Kataokaمشاهده پروفایل

پژوهشگر

• Computer Vision
• Deep Learning
• Artificial Intelligence
• +۵ مورد دیگر

Hirokatsu Kataoka serves as Chief Senior Researcher at the National Institute of Advanced Industrial Science and Technology (AIST) in Japan, with multiple academic affiliations including Academic Visitor at the Visual Geometry Group (VGG) at University of Oxford, Visiting Associate Professor at Keio University, and Adjunct Associate Professor at Tokyo Denki University. He is Principal Investigator of both cvpaper.challenge and LIMIT.Lab, and serves as Research Advisor for SB Intuitions. Dr. Kataoka earned his Ph.D. in Engineering from Keio University (April 2011 - March 2014), where he received the Fujiwara Prize in 2014 as valedictorian equivalent. His research primarily focuses on innovative pre-training methodologies that eliminate dependency on natural image datasets, with his Formula-Driven Supervised Learning (FDSL) framework being particularly influential in the field. Kataoka's research interests center around representation learning with limited data resources, including zero-shot, unsupervised, and synthetic learning approaches. His work explores how visual/multimodal models can be effectively trained with minimal real-world data, addressing critical ethical concerns related to large-scale datasets. He has pioneered methods using fractal geometry, mathematical formulas, and procedural generation to create effective pre-training frameworks that rival traditional ImageNet-based approaches. His publication record shows a clear trajectory toward solving the challenges of learning with limited resources, with recent work expanding FDSL to audio processing, microfossil analysis, and visible-to-infrared translation. His papers consistently address the core challenge of building robust visual recognition systems without relying on massive annotated datasets, with increasing focus on practical applications across diverse domains. Scientific Awards & Recognition ACCV 2020 Best Paper Honorable Mention Award for 'Pre-training without Natural Images' AIST Best Paper Award (2019, 2022) BMVC 2023 Best Industry Paper Finalist Featured in MIT Technology Review His 3D ResNets paper ranks among the top 0.5% most-cited CVPR papers over a five-year period Dr. Kataoka actively advises numerous researchers across multiple institutions, with his research team comprising Ph.D. and Master's students from various universities. He has served as Area Chair for CVPR 2024 and 2025, will serve as IEEE TPAMI Associate Editor beginning in 2025, and organizes the LIMIT Workshop series at major computer vision conferences. His LIMIT.Lab, established in June 2025, serves as a collaboration hub focused on building multimodal AI models under constrained resources including compute, data, and labels.

Hugues Aschardمشاهده پروفایل

پژوهشگر

• Statistical Genetics
• Genome-Wide Association Studies (GWAS)
• Microbiome Research
• +۷ مورد دیگر

Hugues Aschard is a Principal Investigator and Structure Manager at the Pasteur Institute in Paris, where he leads research in statistical genetics, microbiome analysis, and computational genomics. He is the principal investigator of the MicMat project, the EpiGenCOV Consortium, and several bioinformatics software initiatives including JASS, RAISS, and MGMM. Research Interests: Statistical and computational methods in genetics Genome-wide association studies (GWAS) Gene-environment interactions Microbiome and host genetics in inflammatory bowel disease Genetic epidemiology of infectious diseases like COVID-19 Development of open-source tools for multi-trait and summary-statistic analysis Recent Research Trends: His recent publications and projects emphasize integrative genetic modeling, multi-trait analysis across diverse populations, and the development of novel computational methods to handle missing data and improve SNP discovery. His work bridges statistical innovation with biological and clinical applications in complex diseases. Scientific Contributions: Development of JASS, RAISS, and MGMM software tools Leadership in large-scale consortia like EpiGenCOV Advancing methods for cross-ancestry genetic studies Advising and Collaboration: He supervises multiple PhD students and postdoctoral fellows, including Christophe Boetto, Antoine Auvergne, and Lucas Chataigner. He collaborates with major institutions such as APHP and CNRGH. His team includes research engineers and administrative staff, indicating an active and well-supported research group. Laboratories and Teams: He is a key member of the Biomaterials and Microfluidics team at the Pasteur Institute, where he contributes to interdisciplinary research involving Bayesian decision processes and genetic modeling.

Julia Chamot-Rookeمشاهده پروفایل

پژوهشگر

• Proteomics
• Structural Biology
• Mass Spectrometry
• +۷ مورد دیگر

Julia Chamot-Rooke is a Principal Investigator and Researcher at the Institut Pasteur in Paris, France, affiliated with the Department of Structural Biology and Chemistry and the Mass Spectrometry for Biology unit (UTechS MSBio), a joint CNRS service and research unit (USR2000). She leads multiple projects in advanced proteomics and is the PI for the Institut Pasteur in the European Proteomics Infrastructure Consortium providing access (EPIC-XS). Her research focuses on developing innovative methods in top-down proteomics , cross-linking mass spectrometry , and structural proteomics to study intact proteins, post-translational modifications, and protein complexes. Her work has applications in microbiology, infectious diseases, and host-pathogen interactions. She has developed the ProteoCombiner software to integrate proteomics data for improved proteoform characterization. The recent publications reflect a strong emphasis on structural and functional proteomics , particularly in microbial systems and immune interactions. Trends include the use of advanced mass spectrometry techniques (HDX-MS, cross-linking MS, top-down MS) to investigate protein structure, dynamics, and interactions in pathogens and host systems. There is also a growing focus on software and tool development to enhance data analysis and reproducibility in proteomics. Principal Investigator, EPIC-XS at Institut Pasteur Coordinator, Joint Research Activity on Future and Emerging Proteomics Technologies Lead Developer, ProteoCombiner software She supervises PhD students and research engineers and collaborates widely on projects involving bacterial pathogenesis, immune evasion, and structural biology. Her lab is equipped with state-of-the-art Orbitrap mass spectrometers and participates in transnational access programs, providing cutting-edge proteomics services to the European research community.

Frédéric Keckمشاهده پروفایل

پژوهشگر ارشد

• Biopolitics
• Food Safety
• Health Crises
• +۴ مورد دیگر

Frédéric Keck is a Research Fellow at the French National Centre for Scientific Research (CNRS) and heads the Social Anthropology Laboratory (Laboratoire d'Anthropologie Sociale, LAS) at the École des hautes études en sciences sociales (EHESS). He specializes in medical anthropology, focusing on health crises, zoonoses, and biosecurity. His work bridges philosophy, epidemiology, and ecological studies, with notable research on avian flu in Hong Kong and pandemic preparedness. Education: PhD in Philosophy (2003) from University of Lille-III DEA in Philosophy (1999) from University of Paris X-Nanterre Aggregation in Philosophy (1997) Exchange at UC Berkeley (1998-1999) Research Themes: Biopolitics, food risks, scientific networks, ecological disasters, conservation, and zoonotic diseases. His interdisciplinary approach spans anthropology, epidemiology, and policy analysis, with a focus on how scientific expertise shapes global health governance. Publications: Over 20 books and articles, including A World with Flu (2010), Pandemic Sentinels (2020), and works on avian influenza's societal impacts. His writing emphasizes the interplay between human and animal health, surveillance systems, and cultural perceptions of risk. Awards: CNRS Bronze Medal (2011), Fyssen Foundation Grant (2007), and membership in the Canadian Institute for Advanced Research (2015). Roles: Directed the Musée du Quai Branly's research department (2014–2018) and currently leads LAS. Engaged in global health initiatives and collaborative projects on veterinary anthropology and disaster preparedness. Labs/Teams: LAS (CNRS UMR 7130), collaborating with international networks on biosecurity, zoonoses, and environmental anthropology.

Alain Trouvéمشاهده پروفایل

استاد

• Shape Spaces and Applications
• Imaging Processing and Computational Vision
• Computational Biology
• +۳ مورد دیگر

Alain Trouvé is a Professor at the Center for Mathematics and Their Applications (CMLA) within the Ecole Normale Supérieure de Cachan , France. His research focuses on Shape Spaces , Computational Anatomy , Imaging Processing , and Biological Imaging , with applications in medical and computational fields. He directs the Mathematics Department at ENS Cachan and contributes to neuroanatomical studies through diffeomorphometry techniques. Key roles include membership in the Conseil National des Universités (Section 26) and teaching responsibilities such as courses on Geometry and Shape Spaces and Probability Theory . His work spans from theoretical frameworks (e.g., Hamiltonian modeling of shape evolution) to practical applications like 3D cell imaging and white matter fiber analysis. Publications emphasize interdisciplinary methods, including diffeomorphic registration, varifold-based image analysis, and stochastic shape evolutions. Current projects explore multi-scale modeling of biological systems and AI-driven medical diagnostics. Key Research Themes: Diffeomorphic mappings, computational vision, and functional shape analysis. Teaching: Courses on geometric modeling and probability at undergraduate and graduate levels. Tools Developed: xIV-LDDMM Toolkit for multi-modal biomedical data analysis.

Camille Berthelotمشاهده پروفایل

پژوهشگر

• Comparative Functional Genomics
• Evolutionary Genomics
• Gene Regulation
• +۱۲ مورد دیگر

Camille Berthelot is a Principal Investigator and head of the Comparative Functional Genomics research group at the Institut Pasteur in Paris, France. Her work lies at the intersection of evolutionary biology, genomics, and reproductive physiology, with a focus on understanding how genomic changes drive evolutionary innovations in vertebrates, particularly the evolution of menstruation in primates. Her research leverages cutting-edge technologies including single-cell RNA sequencing, organoid models, and computational frameworks to compare gene expression and regulation across species such as humans, macaques, and mice. She investigates how evolutionary changes in gene function contribute to novel traits and how these relate to diseases like endometriosis. A major focus is the use of menstrual fluid as a non-invasive biomarker source for endometriosis, a direction highlighted in her systematic review published in Reproductive Biology and Endocrinology . Her recent publications span high-impact journals such as Science , Genome Research , and Nature Ecology & Evolution , covering topics from teleost fish phylogeny to regulatory evolution in mole-rats. These works reveal a consistent trend in using comparative genomics to decode deep evolutionary questions, often in collaboration with institutions like QMUL and INSERM. ERC Starting Grant (EVOMENS) – Decoding the genetics of menstruation evolution in primates Collaborative project on hypoxia adaptation in mole-rats Development of bioinformatics tools like FINSURF for non-coding variant classification She actively mentors a team of postdocs, PhD students, and master’s interns, including Claire Lavergne, Leo Zeitler, and Eulalie Liorzou. Former members such as Malgorzata Gazda and Axelle Brulport have gone on to independent academic positions, reflecting her role in training next-generation scientists. Camille Berthelot returned from maternity leave in June 2024 and remains actively engaged in research, publication, and team leadership at the Institut Pasteur.

Thomas Cokelaerمشاهده پروفایل

پژوهشگر

• Bioinformatics
• Data Analysis
• Machine Learning
• +۱۲ مورد دیگر

Thomas Cokelaer is a researcher at the Institut Pasteur, affiliated with the Bioinformatics and Biostatistics HUB and based at the Platform Biomics. Since October 2018, he has led the SALSA (dry-lab) group, focusing on bioinformatics software development and data analysis. His interdisciplinary background spans astronomy, plant modeling, systems biology, and drug discovery. Institution: Institut Pasteur Unit: Bioinformatics and Biostatistics HUB Platform: Platform Biomics Group: SALSA (dry-lab group) leader His research interests center on bioinformatics, next-generation sequencing (NGS) analysis, machine learning, data visualization, and reproducible research. He develops and maintains several widely used open-source tools including Sequana (NGS pipelines), BioServices (biological web services), Bioconvert (format conversion), Sequanix (GUI for Snakemake), and GDSCTools (pharmacogenomics). He is deeply committed to promoting reproducibility in computational research through initiatives like reprohackathons. The recent publications reflect a strong trend in computational biology, with a focus on developing bioinformatics methodologies, improving data analysis workflows, and applying these tools to diverse biological problems such as fungal pathogenesis, cancer pharmacogenomics, mitochondrial metabolism, and viral evolution. The work spans genomics, transcriptomics, systems biology, and software engineering. He has contributed to numerous scientific software projects as Principal Investigator, including Sequana, Bioconvert, GDSCTools, DREAMTools, and Sequanix. He has also taught courses in scientific programming with Python and reproducible data analysis at the Institut Pasteur. His collaborative network includes researchers from EMBL-EBI, Sanger Institute, INRIA, and international partners within the Pasteur Network. The SALSA group hosts master’s students and visiting researchers annually.

• Immunology
• Genetics
• Dermatology
• +۲ مورد دیگر

Michele Boniotto is a researcher at the University of Verona's Department of Molecular and Translational Medicine, focusing on immunology, genetics, and dermatology. His work spans molecular mechanisms in skin diseases and evolutionary aspects of host defense peptides. Research Focus Dr. Boniotto's research examines: Genetic factors in hidradenitis suppurativa Beta-defensin evolution and function Aquaporin-3 role in skin homeostasis Photobiomodulation therapies HLA-DR expression in septic shock His publications show interdisciplinary approaches combining molecular biology, clinical dermatology, and bioinformatics to understand complex disease mechanisms. Scientific Contributions 2025: Keratin filament-melanin interactions 2025: Polygenic risk scoring for HS 2024: Aquaporin-3 dysregulation in HS 2023: NCSTN mutations in familial HS 2022: Holistic HS health records 2020: Photobiomodulation for HS

Delphine Josephمشاهده پروفایل

پژوهشگر

• Medicinal Chemistry
• Molecular Design
• Nicotinic Receptor Research
• +۴ مورد دیگر

Delphine Joseph is a prominent researcher in pharmacochemistry at the University of Paris-Saclay's Faculty of Pharmacy, serving as director of the Graduate School of Health & Drug Sciences and deputy director of the BioCIS laboratory (Biomolecules: Design, Isolation, Synthesis). Her leadership spans academic administration, research direction, and teaching innovation within the University Paris-Saclay ecosystem. Her research focuses on two major areas: tobacco addiction mechanisms through nicotinic receptor studies funded by ANR, and drug allergy research particularly regarding neuromuscular blocking agents funded by Anses. Joseph employs a multidisciplinary approach integrating chemistry, biology, and bioinformatics to develop therapeutic solutions and diagnostic strategies. Her work on tobacco addiction targets molecular-level understanding of receptor movements to design targeted molecules, while her allergy research investigates molecular mechanisms of reactions to curare-based medications. Joseph's leadership extends to directing the Graduate School of Health & Drug Sciences, which unites academic and research teams from multiple universities and research organizations (CNRS, Inserm, CEA, INRAE) around drug development and therapeutic innovation. She champions interdisciplinary collaboration through initiatives like mixed cohort events and research days designed to foster innovative projects. PEPS (Passion for Teaching and Pedagogy in Higher Education) Prize recipient ANR-funded research on nicotinic receptors for tobacco addiction treatment Anses-funded project on drug allergy mechanisms to neuromuscular blocking agents Leadership in reforming organic chemistry teaching curricula Her research demonstrates consistent thematic focus on molecular design for therapeutic applications, with increasing emphasis on computational approaches and interdisciplinary collaboration. Recent publications reflect growing integration of bioinformatics with experimental validation, particularly in fragment-based drug design and molecular dynamics studies targeting specific receptor interfaces. Joseph maintains strong industry connections through past collaborations with Novartis and Menarini, and current partnerships with UCB Pharma.

• R-loop Biology
• Epigenetics
• DNA Methylation
• +۴ مورد دیگر

Frédéric Chédin is a Professor in the Department of Molecular and Cellular Biology at the University of California Davis, College of Biological Sciences. He has held continuous faculty positions at UC Davis since 2004, progressing from Assistant Professor (2004-2010) to Associate Professor (2010-2015), and currently serving as full Professor (2015-present). His research focuses on R-loop biology, DNA methylation, and epigenetic regulation. Chédin's laboratory investigates how RNA:DNA hybrids form, persist, and impact genome stability, with particular emphasis on their roles in transcription, chromatin organization, and disease mechanisms. His work has established foundational methodologies for R-loop detection and mapping, including critical assessments of common techniques like the S9.6 antibody. Chédin's publication record demonstrates consistent leadership in R-loop research, with numerous high-impact papers in journals like PNAS , Nature Communications , and Molecular Cell . His recent work explores protein-mediated R-loop stabilization, R-loop classification systems, and connections between R-loops and topological stress management. Director of NIH T32 Predoctoral Training Program in MCB (2020-present) Co-Director of NIH T32 Program (2019-2020) Chair of Integrative Genetics and Genomics (2015-2019) His laboratory trains numerous graduate students and postdoctoral researchers, with frequent collaborators including Stella Hartono and Lionel Sanz appearing as first authors on key publications. Chédin maintains active service roles in graduate education and program leadership at UC Davis.

Violaine Saint-Andréمشاهده پروفایل

پژوهشگر

• Computational Biology
• Immunology
• Epigenetics
• +۳ مورد دیگر

Violaine Saint-André is a Researcher at the Institut Pasteur's Bioinformatics and Biostatistics Hub, where she leads computational biology research focused on immune response determinants through the Milieu Intérieur project. She holds a PhD in Molecular Biology/Genetics from Université Paris VI and an MSc in Bioinformatics from Université Paris VII. Her research investigates transcriptional regulatory networks, epigenetic mechanisms, and multivariate analysis of immune variability. Key interests include: Gene expression regulation and epigenetic memory of environmental exposures Determinants of human immune response heterogeneity Computational methods for multi-omics data integration Impact of smoking on long-term immune adaptation Her publications demonstrate strong focus on immunology and computational biology, with recent work uncovering smoking's persistent epigenetic effects on immunity and cytokine regulation. Research frequently involves high-dimensional data analysis across tuberculosis, COVID-19, and HIV contexts. She contributes significantly to academic training through courses at Institut Pasteur, Centrale-Supelec, and École Centrale de Nantes, covering ChIP-seq analysis, multivariate statistics, and health applications of AI. Actively participates in conference organization and student evaluation committees.

David Defourمشاهده پروفایل

استاد

• Computer Arithmetic
• High Performance Computing
• Computer Architecture
• +۱۱ مورد دیگر

David Defour is a Professor in Computer Science at the University of Perpignan, affiliated with the Faculty of Science and Engineering and the Mathematics and Computer Science Department. He conducts research at the Multidisciplinary Modeling and Simulation Laboratory (LAMPS) and serves as Scientific Coordinator of the MESO@LR Computing Center. His research focuses on the critical intersection of computer arithmetic and computer architecture, with emphasis on: Unconventional arithmetic systems (interval, fuzzy, high/reduced precision) Numerical reproducibility and error estimation in computational workflows Hardware-software co-design for GPUs, multicore systems, and embedded architectures Reverse engineering of computational units and power consumption optimization Defour actively mentors master's students through thesis proposals on numerical bug detection using LLMs, SAT solvers for numerical challenges, soft error resilience in floating-point units, and reverse execution debugging for HPC. He leads the ANR InterFlop project (2021-2025) and previously managed the BPS collaboration contract (2021-2022), while serving as IT expert for the High Court of Perpignan. The LAMPS laboratory under his research activities structures work around two core thematic axes: Characterization of Digital and Discrete Systems, and Mathematical and Numerical Modeling for Mechanics.