Aurélie Chapron is an Associate Professor at the University of Rouen Normandy, affiliated with the Faculty of Science and Technology. Her research focuses on Probability, Random Geometry, and Point Processes, particularly on Voronoi Mosaics in Riemannian Manifolds. Doctorate in Mathematics (2018) from University of Rouen and Paris Nanterre Specialized in Probability during her Master's (2012–2014) and earned Mathematics Aggregation (2016) Her work explores geometric properties of Poisson processes, with publications in International Mathematics Research Notices and Lecture Notes in Mathematics . She has presented at conferences including the Stochastic Geometry Conference (Nantes) and Saint-Flour Probability Summer School. Chapron teaches Mathematics and Statistics courses across multiple disciplines, including Linear Algebra, Calculus, and Inferential Statistics with R, at both the University of Rouen and Paris Nanterre (2015–2018).
Jamila HATTOUTI is a Lecturer and teacher-researcher at the NeuroPsychoLinguistics Laboratory (LNPL), affiliated with Toulouse Jean Jaurès University. She is actively involved in research and teaching in psychology and neuroscience, with a focus on social cognition, communication, and language processing. She holds key roles including Head of Master 1 COGEDUC and TMBI (Toulouse Mind Brain Institute) correspondent. Her research interests include: Social cognition and communication Inferential processes in language Understanding figurative language Autism spectrum disorder Deafness Fetal alcohol spectrum disorder Development of digital tools for assessment Her recent publications (2016–2025) reflect a strong focus on idiom comprehension, pragmatic abilities in neurodevelopmental disorders, and the development of assessment tools like "IDIOME." Her work bridges experimental research with educational and clinical applications, particularly in autism and developmental disorders. She frequently presents at international conferences such as ICAP, ISCL, and EARLI. Scientific contributions include: Development of assessment tools for inferential language skills Analysis of implicit attitudes toward disability in school settings Neuropsychological study of fetal alcohol spectrum disorders Exploration of emotional prosody and crossmodal integration in children Jamila HATTOUTI advises on educational programs and integrates research into teaching practices. She is involved in interdisciplinary collaborations through the Toulouse Mind Brain Institute and contributes to both academic and applied psychology. No information is available about formal grants or student supervision.
Dr. Priyanka Majumder serves as Assistant Professor Grade I in Data Science at the Indian Institute of Science Education and Research (IISER) Thiruvananthapuram since August 2022, following a Post-Doctoral Fellowship at IIT Bombay (2020-2022). She is affiliated with the School of Data Science and teaches core courses including Survival Analysis and Mathematical Statistics. Her academic credentials include: PhD in Mathematics (2020) from Indian Institute of Engineering Science and Technology, Shibpur, with thesis "Some Contributions to Probabilistic and Inferential Aspects of Reliability Theory" M.Sc. in Applied Mathematics (2012-2014) from same institution B.Sc. (Hons.) in Mathematics (2009-2012) from Scottish Church College, Kolkata Majumder's research integrates Applied Statistics and Probability Theory , specializing in Statistical Inference for Cluster Randomized Trials , Longitudinal Study Design , and Reliability Theory . Her work develops novel methodologies for Survival Analysis, Maintenance Policies, and Stochastic Orderings with applications in clinical trial optimization and healthcare analytics. Current projects focus on sample size determination in multilevel clustered studies. Her 14 publications (2018-2025) demonstrate evolving expertise from foundational stochastic orders to cutting-edge cluster trial methodology. Recent work emphasizes longitudinal cluster randomized trials (2022-2025), while earlier research established contributions to reliability theory and mixture distributions. Key journals include Statistics in Medicine , Naval Research Logistics , and Statistical Papers . Major recognitions: SERB Start-up Research Grant (2023) for cluster trial methodology Consecutive teaching awards at IISER TVM (2022-2024) DST-INSPIRE Fellowship (2015-2020) and Scholarship (2009-2014) CSIR-JRF qualification She mentors 3 PhD candidates and 5 Master's students in statistical methodology, with current projects on clinical trial design and reliability systems. Her SERB-funded project supports a JRF position for sample size determination research. She actively recruits graduate students through IISER TVM's PhD program and direct fellowship routes. Majumder leads a research group within IISER TVM's School of Data Science focused on statistical methods for healthcare applications. Her team collaborates with biostatisticians on clinical trial design and participates in international networks including the International Indian Statistical Association.
Mikael Cozic is a Professor at the Faculty of Philosophy of Jean Moulin University, Lyon. His research spans philosophy of science, epistemology, philosophy of mind, and philosophy of economics, with a focus on rationality, decision-making, and interdisciplinary methodologies. He serves as the Director of the Doctoral School of Philosophy and manages training programs related to ecological transition ethics. Director of Doctoral School of Philosophy Manager of DU/Master's in Ecological Transition: Ethics and Environment (TREE) Teaches in CNU Section 17 (Philosophy) Associated with the Institute of Philosophical Research of Lyon His work bridges evolutionary biology, economics, and formal epistemology, particularly in weighted averaging and inductive reasoning. Recent publications include interdisciplinary studies on rationality and a 2023 co-edited volume exploring intersections between evolutionary biology and economics. Cozic holds authorization to direct research and contributes to courses on philosophical debates, ethics, public health, and history of economic sciences. No scientific awards are explicitly mentioned in the provided data.
Aurélie Gauchet is a Professor of Health Psychology at Université Savoie Mont Blanc. Her work focuses on understanding and improving health behaviors, particularly in the context of chronic diseases and vaccination. She is actively involved in research on therapeutic adherence, vaccine hesitancy, stress management, and behavior change interventions. Research Interests Professor Gauchet's research spans several key areas in health psychology. Her primary focus is on therapeutic adherence for chronic conditions including HIV, hepatitis C, and cancer. She investigates the psychological factors influencing patients' ability to follow treatment regimens and maintain health behaviors. A significant portion of her recent work addresses vaccine hesitancy , particularly regarding HPV and influenza vaccines, examining emotional processes, knowledge gaps, and communication strategies that affect vaccination decisions. Her methodological approach combines qualitative and quantitative research methods, employing descriptive and inferential statistics, multiple regressions, modeling, pathway analysis, and mediation analyses. She has developed expertise in the Cognitive Behavioral Stress Management (CBSM) approach for stress management, which she has applied to various populations including parents experiencing burnout. Research Trends Recent analysis of Professor Gauchet's publications reveals a strong emphasis on HPV vaccination research, with numerous studies examining barriers and facilitators to vaccine uptake among adolescents, parents, and healthcare providers. Her work increasingly employs mixed-methods approaches and implementation science frameworks to develop and test interventions that improve vaccination coverage. There is also a growing focus on family dynamics in vaccine decision-making and the development of digital tools to support shared decision-making in clinical settings. Advising and Professional Activities Professor Gauchet appears to be actively involved in collaborative research projects, particularly the PrevHPV Study Group, which focuses on improving HPV vaccination coverage through school- and primary care-based interventions. While specific details about her advisees aren't provided in the available information, her extensive publication record suggests she likely mentors students and early-career researchers in health psychology and public health research methods.
Dr. Shyamal Ghosh is an Assistant Professor Grade I in Data Science at the Indian Institute of Science Education and Research Thiruvananthapuram (IISER TVM). Previously, he served as an Assistant Professor at the Indian Institute of Information Technology Guwahati (2021-2023), a Post-Doctoral Fellow at the University of the Free State, South Africa (2020-2021), and a Visiting Scientist at the Indian Statistical Institute, Kolkata (2019-2020). His educational background includes: M.Sc. in Applied Mathematics from Indian Institute of Engineering Science and Technology, Shibpur (2019), with thesis on "On Certain Probabilistic and Inferential Issues in Nonparametric Ageing Models". B.Sc. (Hons.) in Mathematics from Indian Institute of Engineering Science and Technology, Shibpur (2014). Studies at Vidyasagar University (2009-2012). Dr. Ghosh's research focuses on Dependence Modelling using Copula , Stochastic Degradation Modelling , Statistical Inference , Stochastic Ordering , Shock Model Theory , and Mathematical Theory of Reliability . His work bridges theoretical statistics with applications in reliability engineering, environmental science, and computer systems. He has developed novel statistical tests for ageing classes and methods for stochastic comparisons in heterogeneous systems. His recent publications (2020-2025) span journals in statistics, reliability engineering, and computer science, showing a trend towards interdisciplinary applications. Key areas include nonparametric testing for reliability classes, copula-based dependence modeling, and resource optimization in fog computing. His work often involves moment inequalities, stochastic orders, and lifetime distributions. Dr. Ghosh is actively seeking PhD students with fellowships (e.g., CSIR-JRF, INSPIRE) in Applied Probability and Statistics. He has taught courses such as Statistical Modeling, Survival Analysis, and Mathematical Statistics at IISER TVM and IIIT Guwahati.
Julie Scholler serves as an Associate Professor of Mathematics at the University of Tours, working within the Economic Sciences Section of the UFR of Law, Economics and Social Sciences. She holds the position of Head of the first year of the MÉcEn (Master's in Business Economist) program and has been actively teaching since at least 2013 across various levels of the economics curriculum. Her research interests focus on advanced statistical methodologies and data science applications, particularly in exploratory data analysis, factor analysis, unsupervised classification, and machine learning techniques. She specializes in applying these methods using R programming, with expertise in RMarkdown, RShiny, and data visualization techniques. Her work spans from fundamental statistical theory to practical Big Data solutions with R optimization. Analysis of her recent publications reveals a strong emphasis on classification methods, particularly boosting algorithms, random forests, and ensemble methods. Her work demonstrates expertise in prediction error estimation, with applications across various domains including economics, social sciences, and business analytics. She maintains a consistent focus on practical implementation of statistical methods using R, with particular attention to reproducible research practices through RMarkdown. Professor Scholler has developed extensive teaching materials covering statistics, data analysis, and R programming across multiple academic levels. Her courses include Descriptive Statistics, Inferential Statistics, Bayesian Statistics, Dynamical Systems, and specialized topics in Data Mining and Big Data. She appears to be actively involved in student projects and practical applications of statistical methods, as evidenced by student-produced dashboards on topics ranging from world happiness to Covid vaccination data.
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