جست‌وجوی استاد و پژوهشگر

• Mining Rock Mechanics
• Rock Mass Properties
• Underground Support Systems
• +۲ مورد دیگر

Hakan Basarir is a Professor in the Department of Mining Engineering at the Norwegian University of Science and Technology (NTNU), Trondheim, Norway. His research and teaching focus on mining rock mechanics, rock mass characterization, underground support systems, and the application of soft computing methods in mining engineering. PhD in Mining Engineering (2002) 20+ years of research and teaching experience 60+ publications in journals and conferences Research Interests include rock mass property prediction using measurement while drilling (MWD) techniques, numerical modeling of mining structures, optimization of mine support systems, and sustainable material development. His work integrates machine learning and computational methods to address challenges in mining geomechanics and backfill design. Recent Publications highlight advancements in AI-driven lithology prediction, eco-concrete formulation, and backfill mixture optimization. He has also contributed to tunnel stability analysis and seismic rock slope modeling. Teaching includes advanced courses in mining engineering, mineral production modeling, and specialization projects in geotechnology.

• Experimental Mechanics
• Mechanical Engineering
• Optical Interferometry
• +۳ مورد دیگر

Luigi Bruno is an Associate Professor of Machine Design at the Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria. He has held this position since 2014, following 12 years as an Assistant Professor at the same institution and Visiting Professorships at IIT Gandhinagar (2012), University of Alabama at Birmingham (2013-2017), and Free University of Bozen-Bolzano (2021). 1999 : Master's in Mechanical Engineering, University of Calabria (110/110 cum laude) 2003 : PhD in Mechanical Engineering, University of Pisa His research interests span: Experimental Mechanics : Pioneering speckle interferometry for micro-displacement measurement and residual stress analysis. Materials Science : Elastic characterization of anisotropic materials, biomedical applications of soft substrates, and 3D-printed composites. Biomedical Engineering : Mechanical behavior of biological tissues, ocular biomechanics, and dental implant material testing. Recent research trends focus on: Integrating artificial muscles into rehabilitation devices Advancing full-field optical measurement via microCT/DVC Optimizing 3D printed polymer adhesion for industrial components Exploring neuronal biomechanics on soft surfaces Scientific contributions include: CS2007A00010 patent for dual-focus speckle interferometers Deputy Editor of Optics and Lasers in Engineering (2019-present) Guest Editor for special issues on optical methods in experimental mechanics and nanobiotechnology Academic leadership extends to coordinating Mechanical Engineering committees (2021-present), serving on editorial boards, and organizing international conferences like AIAS National Conference (2018). He has secured multiple MIUR research grants and industry collaborations with Alfagomma, 3DNA, and Ferrovie della Calabria. His laboratory, Mechanics of Materials and Structures , supports both research and teaching activities with advanced optical measurement systems and computational tools for mechanical design.

Stuart C. Althorpeمشاهده پروفایل

استاد

• Theoretical Chemistry
• Quantum Dynamics
• Quantum Mechanics
• +۴ مورد دیگر

Professor Stuart C. Althorpe is a Professor of Theoretical Chemistry at the Department of Chemistry, University of Cambridge, where he leads the Althorpe Research Group. His work focuses on quantum dynamics and the application of quantum mechanics to chemical reactions, particularly examining how quantum effects influence atomic and molecular motion in systems ranging from isolated reactions to liquid water and ice. Professor Althorpe's research interests center on quantum dynamics , with specific focus on quantum tunneling , conical intersections , and path-integral methods . His group develops computational techniques that bridge quantum statistics and classical dynamics, creating methods like Matsubara dynamics to model quantum effects in complex systems. Key research areas include visualizing complete wave functions of chemical reactions, calculating tunneling splittings in water clusters, and investigating quantum interference effects at electronic degeneracies. The group employs both pen-and-paper theoretical derivations and high-performance computational algorithms for parallel CPUs and GPUs to tackle these challenging problems. The trends in Professor Althorpe's recent publications (2018-2024) reveal an evolution from foundational quantum dynamics methods toward increasingly sophisticated applications in complex, dissipative environments. His work consistently bridges computational chemistry and quantum physics, with growing emphasis on connections between quantum dynamics, chaos theory, and quantum information concepts. The publications demonstrate methodological innovation in path-integral approaches, particularly in handling quantum effects in condensed-phase systems like water and ice, while maintaining strong connections to experimental observations. Professor Althorpe has mentored over two dozen PhD students and postdoctoral researchers who have secured positions at leading institutions including ETH Zürich, UCL, EPFL, and various industry roles. His research group maintains active international collaborations, most notably with Professor D.J. Wales at Cambridge (on water clusters) and Professor Richard N. Zare at Stanford University, where theoretical calculations interpret detailed experimental measurements of reaction dynamics. The Althorpe Group operates within the Department of Chemistry at the University of Cambridge as part of the Theoretical Research Interest Group. The group's work contributes significantly to understanding quantum mechanical phenomena in chemical processes, with implications for fields ranging from atmospheric chemistry to biochemistry. Professor Althorpe organized the 2019 Faraday Discussion on "Quantum effects in complex systems," demonstrating his leadership in advancing theoretical frameworks for quantum phenomena in chemistry.

Md Habibullah Bhuyanمشاهده پروفایل

مدرس

• Soil Mechanics
• Geotechnical Engineering
• Non-Destructive Testing
• +۷ مورد دیگر

Dr Md Habibullah Bhuyan is an Adjunct Lecturer at the School of Civil Engineering, The University of Queensland, Australia. His research focuses on geotechnical engineering with an emphasis on soil mechanics, electromagnetic measurement methods, and pavement material characterization. He can be contacted at h.bhuyan@uq.edu.au . PhD, Geotechnical Engineering, The University of Queensland (2018) Masters, Geotechnical Engineering, Saitama University (2013) Bachelor, Civil Engineering, BUET (2006) His expertise includes non-destructive testing of unbound granular materials, geo-hydraulic characterization of soft soils in saline environments, and electromagnetic monitoring of soil moisture, density, and deformation. He investigates drained/undrained shear strength, unsaturated soil mechanics, and phase transitions in granular media such as erosion and liquefaction. Recent publications highlight railway ballast deformation (2025), tailings consolidation (2023), TDR sensor challenges (2022), and applications of electromagnetic methods in pavement and coastal engineering. Key themes span unsaturated soil behavior, erosion processes, and advanced geotechnical instrumentation. His teaching spans 12 years across Australia, Japan, and Bangladesh, covering Soil Mechanics , Geotechnical Engineering , Advanced Soil Mechanics , and Transportation Engineering .

• Health Economics
• Economics of Education
• Development Economics
• +۳ مورد دیگر

Jinhu Li is a Senior Research Fellow at the Australian National University, holding positions in both the Department of Health Economics, Wellbeing and Society and the National Centre for Health Workforce Studies. She has previously held academic positions as a Senior Lecturer at Deakin University and a Senior Research Fellow at the University of Melbourne. Dr. Li completed her PhD in Economics from McMaster University in Canada, following an MA in Economics from the University of Victoria and a BA in Economics from Huazhong University of Science and Technology in China. She is also a Fellow of the UK Higher Education Academy (HEA). Her research focuses on health economics, economics of education, and development economics, with particular emphasis on social determinants of health, human capital formation, and health workforce economics. Dr. Li employs advanced methodologies including causal inference techniques and Discrete Choice Experiments to investigate critical issues in health, education, and development. Her recent publications span topics including the impacts of education on health outcomes, physician behavior and incentives, early-life health shocks, and child malnutrition. Her work appears in leading journals such as Journal of Health Economics, Journal of Development Economics, Health Economics, and Social Science and Medicine. Dr. Li has received significant recognition for her research, including an Australian Research Council (ARC) Discovery Early Career Researcher Award (DECRA) from 2017-2023. She has secured over $4.2 million in research funding, with $3.8 million from Category 1 national competitive grants. She currently leads multiple major research projects, including an ARC DECRA project, an ARC Discovery Project, and an MRFF Primary Health Care Research grant. Her current research examines the impacts of counter-COVID public policies like school closures on child development and optimal workforce mix for team-based care in managing chronic diseases.

John G. Kernsمشاهده پروفایل

استاد

• Translational Clinical Neuroscience
• Psychotic Disorders
• Cognitive and Emotional Control
• +۵ مورد دیگر

John G. Kerns is a Professor in the Department of Psychology at the University of Missouri, leading the Cognitive and Emotional Control Lab. His research integrates clinical psychology and neuroscience to understand psychotic disorders, with a focus on striatal functioning and aberrant salience. His primary research interests include: Translational clinical neuroscience of psychotic disorders Cognitive and emotional control mechanisms Striatal functioning and feedback-related learning Aberrant salience and positive schizotypy Openness to experience in psychopathology Analysis of Dr. Kerns' recent publications shows a strong emphasis on neuroimaging and behavioral studies of psychosis risk, particularly examining corticostriatal pathways and their relationship to cognitive deficits. His work consistently bridges personality factors with neural mechanisms. No scientific awards are mentioned in the provided text. Dr. Kerns mentors a vibrant team of graduate and undergraduate students. Current graduate students include Megan Liew and Tyler Rogers, and his alumni have secured prestigious positions in academia and clinical practice. He is accepting applications for graduate students starting in Fall 2026. The Cognitive and Emotional Control Lab provides a collaborative environment for research on psychotic disorders, utilizing behavioral, clinical, and neuroimaging methods to advance understanding and treatment.

Matthew J. Hallمشاهده پروفایل

استاد

• Engine Combustion Processes
• Thermal Fluids Systems
• Engine Controls
• +۱۱ مورد دیگر

Matthew J. Hall is a Professor in the Department of Mechanical Engineering at the University of Texas at Austin , where he also holds the Louis T. Yule Fellowship in Engineering . He has been a faculty member since 1991 and is affiliated with the Cockrell School of Engineering . His research spans engine combustion processes , thermal fluids systems , engine controls , optical diagnostics , battery safety , and alternative fuels . He is particularly known for his work on cold-start emissions , spark ignition , engine friction reduction , and thermoelectric energy recovery . He teaches courses in Thermodynamics , including modeling of power cycles and HVAC systems , and has published over 150 technical articles. His recent work includes innovations in ammonia combustion , biomass gasification , and advanced engine diagnostics . Scientific Awards & Honors: Fellow of the Society of Automotive Engineers (SAE) Louis T. Yule Fellowship in Engineering Associate Editor, SAE International Journal of Engines Research Impact & Leadership: Prof. Hall leads multidisciplinary efforts in combustion science , energy systems , and sustainable propulsion . His lab has contributed to reducing engine friction by up to 40%, improving fuel efficiency at idle, and advancing the use of ammonia as a low-carbon fuel. He also explores thermoelectric generators for extending drone flight range and improving vehicle energy recovery systems.

Witold Nazarewiczمشاهده پروفایل

استاد

• Theoretical Nuclear Physics
• Nuclear Structure
• Quantum Many-Body Problem
• +۷ مورد دیگر

Witold "Witek" Nazarewicz is a John A. Hannah Distinguished Professor in the Department of Physics & Astronomy at Michigan State University and serves as the Chief Scientist at the Facility for Rare Isotope Beams (FRIB). He is also a Corporate Fellow Emeritus at Oak Ridge National Laboratory (ORNL) and maintains a professorship at Warsaw University, Poland. Nazarewicz previously held positions as James McConnell Distinguished Professor at the University of Tennessee and served as Scientific Director of ORNL's Holifield Radioactive Ion Beam Facility from 1999-2012. His academic career spans multiple international institutions including Lund University, University of Cologne, Kyoto University, University of Liverpool, and Peking University. Nazarewicz's research focuses on theoretical nuclear physics with particular emphasis on exotic nuclei at the limits of nuclear existence. His work spans quantum many-body problems, physics of open quantum systems, superheavy elements, and nuclear fission. He has pioneered approaches to unify structure and reaction aspects of nuclei based on open quantum system many-body formalism, including the Gamow Shell Model. His research connects nuclear physics with high-performance computing, developing comprehensive descriptions of all nuclei through theoretical and experimental investigations of rare atomic nuclei. An analysis of Nazarewicz's recent publications reveals a strong focus on cutting-edge nuclear structure research, particularly concerning exotic nuclei near the driplines, charge radii measurements, superheavy elements, and the development of advanced computational methods. His work increasingly incorporates machine learning and Bayesian analysis techniques to address nuclear physics challenges. The publications demonstrate his leadership in connecting fundamental nuclear physics with applications in nuclear astrophysics, while also addressing foundational questions about the limits of nuclear existence and the nature of nuclear forces. Fellow of the American Physical Society Fellow of the U.K. Institute of Physics Fellow of the American Association for the Advancement of Science 2008 Carnegie Centenary Professor Honorary Doctorates from University of the West of Scotland (2009) and University of York (2019) 2012 Tom W. Bonner Prize in Nuclear Physics 2012 ORNL Distinguished Scientist 2013 UT-Battelle Corporate Fellow 2017 G.N. Flerov Prize 2025 Marian Smoluchowski Medal Nazarewicz has authored approximately 500 peer-reviewed publications with over 37,000 citations and an h-index of 103 (Web of Science). He has delivered over 220 invited talks at major international conferences and organized approximately 70 scientific meetings. His research has been supported by numerous grants from the Department of Energy, National Science Foundation, and international funding agencies. Nazarewicz plays a leadership role in major nuclear physics initiatives including the UNEDF, NUCLEI, and BAND collaborations, and has contributed to several National Academies reports on nuclear physics. As FRIB Chief Scientist, Nazarewicz leads theoretical efforts at one of the world's premier facilities for rare isotope research. His research group at MSU collaborates extensively with experimentalists worldwide, bridging theoretical predictions with cutting-edge measurements. He directs the FRIB Theory Alliance, fostering international collaboration in nuclear theory, and has established strong connections between nuclear physics and other disciplines including quantum information science and machine learning.

Carla Curadoمشاهده پروفایل

دانشیار

• Knowledge Management
• Human Resource Management
• Organizational Behavior
• +۳ مورد دیگر

Carla Curado is an Associate Professor with Habilitation in Organizational Behavior and Human Resource Management at ISEG – Lisbon School of Economics and Management, University of Lisbon. She serves as a founding researcher at the ADVANCE research center and holds leadership roles including Master's Program Coordinator for Human Resource Management and Business Sciences. She represents the University of Lisbon at the International Organization for Standardization and is an Associate Editor for the Journal of Organizational Effectiveness: People and Performance . Her research explores: Knowledge Management in healthcare, SMEs, and NGOs Digital leadership and workplace happiness HRM's role in innovation and sustainability Mixed-method approaches to organizational analysis Recent publications (2023-2025) emphasize digital transformation, healthcare efficiency, and methodological innovations in operations management. Key trends include configurational analysis of leadership and knowledge behaviors in hybrid work environments. Awards: Stanford's Top 2% World Scientist (2021, 2022, 2023) She supervises 65+ Master's students with theses on: Knowledge sharing mechanisms Leadership/organizational commitment Healthcare workplace dynamics Sustainability in HR practices At ADVANCE Research Center, she contributes to teams studying management innovation and organizational resilience, with active participation in EU research consortia.

Xuming Heمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۹ مورد دیگر

Xuming He is an Associate Professor at the School of Information Science and Technology (SIST), ShanghaiTech University, where he leads the PLUS Lab. His research spans computer vision and machine learning with a focus on developing algorithms that operate effectively under limited supervision and evolving data conditions. His core research interests include weakly-supervised and few-shot learning for scenarios with sparse annotations, continual learning frameworks for knowledge retention during sequential task acquisition, semantic segmentation techniques for scene understanding, and multimodal vision-language representations. He emphasizes interpretable machine learning to build transparent AI systems capable of human-understandable reasoning, addressing critical challenges in model trustworthiness and deployment reliability. Recent publications reveal strong trends toward novel class discovery in long-tailed recognition scenarios, physics-informed generative modeling for scientific applications, and robust segmentation under distribution shifts. His work increasingly integrates large language models for multimodal reasoning while maintaining focus on efficiency in resource-constrained environments like robotic grasping and medical imaging analysis. He actively mentors students, having supervised Qian He to PhD completion and Chuanyang Hu to Master's degree in 2023. He welcomes prospective graduate students through ShanghaiTech's Computer Science & Technology program and offers undergraduate research projects requiring minimum six-month commitments. The PLUS Lab under his direction drives innovation in learning under supervision constraints, with recent work spanning medical tumor analysis, cross-view geolocation, photonic computing, and semiconductor design verification. The lab's research bridges theoretical advances with practical applications across healthcare, robotics, and scientific discovery domains.

Tatjana Thelenمشاهده پروفایل

استاد

• Kinship and State Interactions
• Care and Social Security
• Post-Socialist Transformations
• +۶ مورد دیگر

Tatjana Thelen is a Full Professor of Social and Cultural Anthropology at the University of Vienna and holds fellowships at the Institute for Advanced Study (IAS) in Paris and the FMSH (Fondation Maison des Sciences de l'homme). She serves as Deputy Director of the Vienna Doctoral School of Social Sciences and co-directs the Research Platform for the Study of Transformations and Eastern Europe. Her work bridges kinship studies , care ethics , and state anthropology , with a focus on post-socialist Europe and interdisciplinary critique of Western epistemologies. Academic Leadership : Deputy Director of Vienna Doctoral School; Co-founder of CAST (Care and State) network; Director of Vienna Ethnography Laboratories Research Themes : Kinship-state interplay, care practices in political belonging, post-socialist transformation, relational theory, social security frameworks Her relational anthropology examines how care responsibilities shape state boundaries and generate inclusion/exclusion dynamics through kinship measurements. She critiques the Western assumption that modernity diminishes political kinship, analyzing its persistence in citizenship, property relations, and welfare systems. Current projects explore political atmospheres and their role in state boundary demarcation. Scientific Recognition : Distinguished Visiting Austrian Chair, Stanford University (2023) Fellow, Institute for Advanced Study (IAS), Paris (2020-21) Fellow, Center for Interdisciplinary Research (ZiF), Bielefeld (2016-17) She has supervised PhD projects on topics including: Ukrainian female labor migration and left-behind families Corporate Social Responsibility in Turkey Ecological villages in China Kinship-politics conceptual history State care in socialist Hungary Rural Hungarian state rescaling Serbian local state practices

Daniel Hlubinkaمشاهده پروفایل

دانشیار

• Statistics
• Theoretical Foundations
• Multivariate Functional Processes
• +۴ مورد دیگر

Daniel Hlubinka is an Associate Professor at the Department of Probability and Mathematical Statistics, Faculty of Mathematics and Physics, Charles University. He has been an academic staff member since 1999 and was promoted to associate professor in 2007. His teaching includes courses like Statistics for Financial Mathematicians 2 (NMFM332) and Proseminar in Probability and Mathematical Statistics (NMSA262). He supervises bachelor's, diploma, and doctoral theses, with over 30 bachelor's, 20 diploma, and 5 doctoral theses supervised to date, including former students now working as associate professors. Education: Mathematical Physics (1989-1994) at Charles University; Erasmus stay at Limburgs Universitaire Center (1994-1995); Doctorate (1995-1999) under Professor Josef Štěpán. Research Interests: Statistics, theoretical foundations, multivariate functional processes, nonparametric asymptotics, data depth, optimal transport, and mathematics of chance. Academic Affiliations: Member of the Union of Czech Mathematicians and Physicists, Czech Mathematical Society, Czech Statistical Society, European Mathematical Society, Bernoulli Society, and Institute of Mathematical Statistics. Hlubinka's recent research focuses on functional data analysis, multivariate quantiles, and nonparametric testing. His work applies optimal transport theory, empirical characteristic functionals, and permutation tests to functional statistical problems. He contributes to methodological advancements in depth-based classification, time reversibility testing, and regression models.

• Sensory Systems
• Social Behavior
• Neurogenomics
• +۴ مورد دیگر

Nora H Prior, PhD, is a Senior Research Associate in the Psychology Department at Cornell University, focusing on sensory systems, social behavior, and neurogenomics. Her research team explores avian behavioral neuroscience, with expertise in neuroendocrinology, bioacoustics, and comparative psychology. 2020-2021: Sessional Instructor & course designer, University of British Columbia 2018-2021: Postdoctoral Associate, Avian Behavioral Neuroscience Lab (University of Maryland) 2016-2018: Postdoctoral Fellow, Center for Comparative and Evolutionary Biology of Hearing (University of Maryland) 2015: Postdoctoral Fellow, Neuroethology & Bioacoustics Lab (University of Lyon) 2009-2014: PhD Candidate (University of British Columbia) Her research combines neuroendocrinology, bioacoustics, and behavioral ecology to study avian communication, pair bonding, and neurogenomic responses to environmental stressors. Key topics include: Acoustic fine structure in zebra finch communication Neuroendocrine regulation of monogamy and aggression Effects of water restriction on vocal behavior Differential gene expression in extreme physiological states Temporal processing of vocal sequences Perceptual limitations in avian cognition While her publications span from 2010-2025, recent work emphasizes methodological rigor in neuroscience research, environmental impacts on brain development, and neurogenomic resilience in wild birds. Her 2025 paper on Science Democratization addresses systemic challenges in behavioral neuroscience.

Hua Xuمشاهده پروفایل

استاد

• Clinical Natural Language Processing
• Biomedical Informatics
• Large Language Models for Biomedicine
• +۳ مورد دیگر

Dr. Hua Xu is the Robert T. McCluskey Professor of Biomedical Informatics and Data Science at Yale School of Medicine. He serves as Vice Chair for Research and Development in the Department of Biomedical Informatics and Data Science and as Assistant Dean for Biomedical Informatics at Yale School of Medicine. Dr. Xu leads the Clinical NLP Lab and is Chair of the NLP working group at the Observational Health Data Sciences and Informatics (OHDSI) program. Dr. Xu received his PhD in Biomedical Informatics from Columbia University, an MS in Computer Science from New Jersey Institute of Technology, and a BS in Biochemistry from Nanjing University. Dr. Xu is a renowned researcher in clinical natural language processing (NLP), having developed novel algorithms for important clinical NLP tasks such as entity recognition and relation extraction. His work has been top-ranked in over a dozen international biomedical NLP challenges. He has developed CLAMP, a comprehensive clinical NLP toolkit that has been successfully commercialized and adopted by hundreds of healthcare organizations worldwide. His research focuses on applying NLP technologies to diverse clinical and translational studies to accelerate clinical evidence generation using electronic health records data. Recently, he has been utilizing NLP to harmonize metadata of biomedical digital objects to promote FAIR principles in biomedicine, and his lab is actively working on developing large language models (LLMs) for diverse biomedical applications. Dr. Xu's recent publications demonstrate a clear trend toward leveraging large language models for biomedical applications. His work spans from benchmarking LLMs for clinical NLP tasks to developing specialized architectures like BiomedRAG (retrieval augmented LLMs for biomedicine). His research addresses critical healthcare challenges including adverse event extraction, oncology clinical trial analysis, and EHR-based association studies, showing how NLP can bridge the gap between unstructured clinical text and actionable medical insights. Dr. Xu's lab has achieved top rankings in numerous NLP challenges, including multiple #1 positions in i2b2 Temporal information extraction, SemEval Disease-modifier extraction, BioCREATIVE Chemical-induced disease extraction, and other prestigious competitions. His contributions to clinical NLP have significantly advanced the field's ability to extract meaningful information from complex medical texts. As the leader of the Clinical NLP Lab at Yale, Dr. Xu oversees research that forms a complete ecosystem: developing novel NLP methods, building robust software tools, and applying these technologies to clinical and translational research. His lab's work closes the loop between methodological innovation and practical healthcare applications, ensuring that advances in NLP directly benefit patient care and medical research.

• Probability Theory
• Stochastic Processes
• Graph Signal Processing
• +۴ مورد دیگر

Basile de Loynes is a Lecturer at the French National School of Statistics and Information Analysis (ENSAI), holding a permanent academic position since at least 2016. He maintains a dual affiliation as a CREST (Center for Research in Economics and Statistics) Affiliated Member, contributing to interdisciplinary economic-statistical research. His academic trajectory includes a postdoctoral position at the University of Neuchâtel (2012), followed by temporary lecturer roles at the University of Burgundy (2013-2014) and University of Strasbourg (2014-2016). His research centers on advanced probability theory with specific expertise in stochastic processes on non-Euclidean structures. Key areas include: Random walks on algebraic structures (groups, groupoids, tilings, graphs) Poisson-Martin boundary theory and potential analysis Long memory processes and invariance principles Graph signal processing with Fourier/wavelet methods His publication record shows consistent output in top-tier journals since 2012, with recent work (2021-2023) focusing on graph-based signal denoising and differential privacy applications. Analysis of his 10 most recent publications reveals a strong methodological thread connecting classical probability theory with modern graph-based signal processing. Approximately 60% of his work since 2016 involves graph-structured stochastic models, demonstrating an evolving research trajectory from theoretical random walk properties toward applied graph signal analysis. The recurring subfields across publications include Markov additive processes, spectral graph theory, and wavelet transforms on non-Euclidean domains. His academic service includes developing comprehensive teaching materials for core probability and measure theory courses at ENSAI, with publicly available lecture notes and examinations dating back to 2016.