جستجوی استاد راهنمای دانشگاهی

Jérémie Bourdonمشاهده پروفایل

استاد

• Bioinformatics
• Probabilistic modeling
• Systems biology
• +۵ مورد دیگر

Professor Jérémie Bourdon is a Full Professor of Computer Science at the University of Nantes, Faculty of Science and Technology, where he serves as Vice-Dean in charge of Research, Innovation and International Relations since 2018. He is affiliated with LS2N (Laboratory of Digital Sciences of Nantes, UMR 6004) and heads the ComBi research group (Combinatorics and Bioinformatics) since January 2014. His research focuses on the application of probabilistic methods in bioinformatics, particularly in systems biology. Professor Bourdon's work spans from Number Theory to Systems Biology with a common thread of developing and using probabilistic tools. His main research activities include dynamical analysis of algorithms and systems biology modeling, where he has developed the transition event graph model to integrate quantitative and qualitative biological data. Professor Bourdon's recent publications demonstrate consistent output in high-impact journals including Nature Communications, PLOS Computational Biology, and BMC Systems Biology, with research trends showing increasing focus on metabolic network analysis, multi-omics data integration, and constraint-based modeling approaches. Academic Editor for PLOS One Co-chair of CMSB 2015 international conference Member of Biogenouest scientific council (2004-2017) Co-scientific responsible for BiRD bioinformatics platform Professor Bourdon has secured significant research funding including the 1.4M€ GRIOTE project and participation in multiple ANR/CNRS projects. He has supervised 9 PhD students, typically through co-direction arrangements, reflecting his collaborative research approach. His ComBi group consists of 12 members including professors, assistant professors, PhD students, post-docs, and engineers, working on diverse topics in bioinformatics and computational biology. The ComBi research group, led by Professor Bourdon since 2014, focuses on combinatorics and bioinformatics with activities centered around comparative genomics and systems biology. The group provides a collaborative environment for interdisciplinary research at the intersection of computer science and biology, with strong connections to biological research teams and access to computational resources through the BiRD platform.

Dagfinn Rimeمشاهده پروفایل

استاد

• International Finance
• Foreign Exchange Markets
• Financial Economics
• +۳ مورد دیگر

Professor Dagfinn Rime is a distinguished scholar in international finance at BI Norwegian Business School, where he serves as Professor in the Department of Finance. With a PhD from BI Norwegian Business School (2001), his career spans significant roles at Norges Bank (Central Bank of Norway) and academic appointments at Norwegian University of Science and Technology (NTNU) and Stockholm Institute for Financial Research. His academic journey includes: 2014-Present: Professor, Department of Finance, BI Norwegian Business School 2001-2014: Researcher and Manager, Norges Bank (Central Bank of Norway) 2006-2012: Adjunct Professor, Norwegian University of Science and Technology 2001-2006: Visiting Research Fellow, Stockholm Institute for Financial Research Professor Rime's research primarily focuses on the microstructure of foreign exchange markets, examining how market participants interact, how prices are formed, and how information flows through currency markets. His work bridges theoretical finance with practical market observations, often utilizing high-frequency transaction data to uncover patterns that traditional macroeconomic approaches might miss. He has made significant contributions to understanding the relationship between order flow and exchange rate movements, the volume-volatility relation in FX markets, and the mechanics of covered interest parity deviations. His research has evolved from examining basic dealer behavior in the early 2000s to more complex analyses of market fragmentation, high-frequency trading effects, and the role of different market participants in price discovery. Recent work has addressed contemporary issues such as the offshore renminbi market and the effectiveness of central bank communication policies. Professor Rime's scientific contributions have been recognized through publications in top-tier finance journals: Journal of Financial Economics Review of Financial Studies Journal of Monetary Economics Journal of International Economics International Journal of Finance and Economics His research methodology typically involves detailed empirical analysis of transaction-level data, allowing him to observe market dynamics at a granular level. This microstructure approach has provided valuable insights into how foreign exchange markets actually function, as opposed to how they are often modeled in traditional macroeconomic frameworks. Professor Rime is also engaged in public discourse, having contributed opinion pieces on topics such as cryptocurrency markets and the value of international researchers in Norwegian academia. His commentary on Bitcoin as a financial bubble demonstrated his ability to translate complex financial concepts for broader audiences.

Conrado da Costaمشاهده پروفایل

استادیار

• Probability Theory
• Random Walks
• Scaling Limits
• +۵ مورد دیگر

Conrado da Costa is an Assistant Professor (Research) in Probability at Durham University's Department of Mathematical Sciences. His academic profile centers on advanced research in probability theory, with particular expertise in Non-Homogeneous Random Walks and Scaling Limits of Interacting Particle Systems. His research portfolio spans several interconnected domains: Diffusion on Networks and Infinite graphs Fluid limits and hydrodynamic limits Random walks in random environments Law of Large Numbers and long-term behaviors Local convergence of random graphs Professor da Costa employs a sophisticated mathematical toolkit including scaling limits, generators, semigroups, martingale problems, concentration inequalities, and coupling methods. His research methodology bridges theoretical probability with applications in statistical mechanics and mathematical physics, revealing how microscopic stochastic processes give rise to macroscopic deterministic behavior. His publication record shows consistent development from foundational work on reaction-diffusion models (2019) to more recent investigations of random walks in cooling random environments and stochastic billiards (2022-2023). His work demonstrates increasing sophistication in handling complex correlation structures and boundary effects in stochastic systems. Professor da Costa has secured research funding for projects including 'Anomalous diffusion via self-interaction and reflection' and actively supervises undergraduate and graduate students through annual project offerings since 2019. His research collaborations extend to institutions including Leiden University, IMPA, and the University of Manchester, reflecting his growing international recognition in the probability community.

Ange Adrienne Nyamen Tatoمشاهده پروفایل

استادیار

• Artificial Intelligence in Education
• Generative AI for Education
• Machine Learning Algorithms
• +۷ مورد دیگر

Ange Adrienne Nyamen Tato serves as an Assistant Professor in the Department of Teaching and Learning Studies at Laval University's Faculty of Education. Her academic journey spans multiple institutions across Canada and Morocco, with a strong interdisciplinary background combining computer science, artificial intelligence, and educational theory. PhD in Computer Science (Artificial Intelligence) from University of Quebec at Montreal (UQAM), 2020 Master's degree in Computer Science from University of Quebec at Montreal (UQAM), 2015 Engineering degree in Information Systems from Mohammedia School of Engineers in Morocco, 2014 DEUST in Mathematics, Computer Science and Physics from Hassan II University, Morocco, 2011 Professor Tato's research focuses on the intersection of artificial intelligence and education, with particular expertise in generative AI applications for educational contexts, machine learning algorithms, intelligent tutoring systems, educational data mining, and serious game design. Her work addresses critical challenges in educational technology including transparency, assessment practices, and engagement issues that have limited the adoption of AI-powered learning tools. She is particularly interested in the ethical implications, environmental impact, and potential biases of AI in educational settings. Her recent publications demonstrate a consistent focus on developing sophisticated models for user behavior prediction, adaptive learning systems, and integrating pedagogical knowledge into AI frameworks. The research spans multiple domains including logical reasoning development, socio-moral reasoning, piloting training, and general educational applications of deep learning and knowledge tracing techniques. Professor Tato has secured significant research funding, including a $192,500 NSERC Discovery Grant for her project 'Optimizing Generative Artificial Intelligence for Education: Towards a Holistic Approach Integrating Teachers and Learners.' This five-year project aims to develop pedagogically aware large language models (PA-LLMs) that better serve educational purposes by integrating educational theories, human learning factors, and bias correction mechanisms. Principal Investigator for NSERC Discovery Grant ($192,500 over 5 years) PC Member for ICCE 2023 and 2024 conferences PC Member for EDM 2024 conference PC Member for AIED 2024 conference Professor Tato teaches graduate courses including TEN-7028 Games and Learning and TEN-7030 Digital Intelligence in Education: Opportunities and Challenges. She is currently accepting Master's students interested in AI applied to education. Her previous professional experience includes work as an Artificial Intelligence Specialist at Beam Me Up Augmented Intelligence (2018-2022) and a postdoctoral fellowship in Deep Learning applied to aeronautics in partnership with Bombardier and CAE (2020-2022).

• Markov processes
• Ruin theory
• Extreme value theory
• +۵ مورد دیگر

Romain Biard is a Senior Lecturer in Mathematics at the University of Franche-Comté, holding dual research affiliations with the Besançon Mathematics Laboratory (UMR 6623, LMB) and the Research Center on Economic Strategies (UR 3190, CRESE). His career bridges theoretical mathematics with practical applications in economics and healthcare systems. His primary research interests span Markov processes, Ruin theory, Extreme value theory, Optimal allocations, and Game theory. These areas converge in his work on modeling complex systems with random elements, particularly focusing on risk assessment and resource allocation problems. His research demonstrates how mathematical frameworks can address real-world challenges in healthcare management and economic competition. Analysis of his recent publications reveals a strong trend toward applied research with immediate societal relevance. His 2023-2024 work on healthcare resource allocation (nursing shortages, ventilator availability) applies sophisticated Markov process modeling to critical hospital management problems. Earlier work on economic competition models demonstrates how random entry of firms affects market equilibrium, with specific applications to the taxi industry facing competition from ride-hailing services. Active researcher with publications spanning 2008-2024 Primary collaborator network includes Marc Deschamps, Mostapha Diss, Alexis Roussel, and Stéphane Loisel Publications appear in high-quality journals across mathematics, statistics, economics, and actuarial science Biard's research approach consistently combines rigorous mathematical theory with practical applications, making significant contributions to both theoretical developments and real-world problem solving. His current work suggests continued focus on applying stochastic modeling to healthcare resource challenges and economic competition dynamics.

• Probability Theory
• Random Processes
• Large Deviations
• +۲ مورد دیگر

Evgeny Igorevich Prokopenko is a Senior Research Fellow at the Faculty of Computer Science, National Research University Higher School of Economics (HSE), specifically within the Institute of Artificial Intelligence and Digital Sciences and the Laboratory of Theoretical Foundations of Artificial Intelligence Models. He joined HSE in 2024 and concurrently serves as a Senior Researcher at the Sobolev Institute of Mathematics, Siberian Branch of the Russian Academy of Sciences since January 2019. His educational background includes: 2018: Candidate of Physical and Mathematical Sciences 2014: Master's degree in Mathematics from Novosibirsk National Research State University Prokopenko specializes in probability theory and random processes, with particular focus on large deviations. His research bridges theoretical mathematics with applications in artificial intelligence and complex systems. His work demonstrates a strong foundation in mathematical theory while addressing contemporary challenges in data science and stochastic modeling. His scientific contributions primarily focus on limit theorems, branching processes, and large deviation principles. His publications reveal a consistent research trajectory in probability theory with applications to various domains including polymer physics and random environments. The temporal pattern of his publications shows ongoing productivity with recent work published in top probability journals. His notable achievements include: Multiple publications in high-impact journals including Probability Theory and Its Applications, Extremes, Statistics and Probability Letters, and Problems of Information Transmission Collaborations with prominent researchers in probability theory across international institutions Prokopenko maintains active research affiliations with both HSE University in Moscow and the Sobolev Institute of Mathematics in Novosibirsk, reflecting a strong connection between Russia's leading mathematical centers. His current position at HSE's Faculty of Computer Science suggests an integration of his theoretical expertise with modern computational approaches.

François Bolleyمشاهده پروفایل

استاد

• Interacting particle systems
• Mean-field limits
• Kinetic equations
• +۵ مورد دیگر

François Bolley is a Professor in the Department of Mathematics at École normale supérieure de Rennes and a researcher at IRMAR (Institut de Recherche Mathématique de Rennes), UMR CNRS 6625. His academic career includes a doctoral thesis completed at École Normale Supérieure de Lyon in 2005 under Cédric Villani's supervision and a Habilitation from Université Paris-Dauphine in 2012. Professor Bolley's research spans interacting particle systems , mean-field limits , kinetic equations , optimal transport , and functional inequalities . His work establishes deep connections between geometric properties (curvature-dimension conditions) and analytic properties (transportation inequalities and functional inequalities). He has made significant contributions to dimensional improvements of classical inequalities and the understanding of convergence to equilibrium for various particle systems and PDEs. His publication record shows consistent productivity since 2005, with recent work (2017-2018) focusing on dimensional improvements of functional inequalities, equivalence between dimensional contractions and curvature conditions, and applications of the Li-Yau inequality. His research appears in top mathematics journals including Annals of Probability, Journal of Functional Analysis, and Annales de l'Institut Fourier. Professor Bolley has demonstrated leadership in the mathematical community through organizing conferences such as the 2011 Boltzmann equation conference at Institut Henri Poincaré in memory of Carlo Cercignani. His work bridges probability theory, partial differential equations, and mathematical physics, with applications to statistical mechanics and mathematical biology. Students and collaborators would find opportunities to work on challenging problems at the intersection of multiple mathematical disciplines, with connections to physical applications. His research group provides access to the broader mathematical community through IRMAR and potential collaborations with international researchers.