جست‌وجوی استاد و پژوهشگر

Christian Kühnمشاهده پروفایل

استاد

• Dynamical Systems
• Differential Equations
• Stochastic Dynamics
• +۵ مورد دیگر

Christian Kühn is a Professor of Multiscale and Stochastic Dynamics at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology. He has been an External Faculty member at the Complexity Science Hub Vienna since 2017, reflecting his interdisciplinary engagement in complex systems research. His academic background includes a BSc in Mathematics from Jacobs University Bremen (2005), an M.A.St. from the University of Cambridge (2006), and a PhD in Applied Mathematics from Cornell University (2010). He held postdoctoral positions at the Max Planck Institute for the Physics of Complex Systems in Dresden and the Vienna University of Technology, where he also served as an APART-Fellow and Leibniz Fellow. Christian Kühn's research lies at the intersection of differential equations, dynamical systems, and mathematical modeling. He focuses on multiscale problems, the impact of noise and uncertainty in deterministic and stochastic systems, and adaptive networks. Central phenomena of interest include bifurcations, pattern formation, and scaling laws. His work bridges theoretical developments with applications in epidemiology, neuroscience, and complex network dynamics. His recent publications (2021–2024) reflect a strong trend in analyzing nonlinear and stochastic dynamics on networks, with applications ranging from epidemic modeling to synchronization and critical transitions. Key themes include explosive phenomena, adaptive network behavior, moment closure methods, and non-Markovian systems, demonstrating a consistent focus on foundational aspects of dynamical systems with practical relevance. Notable scientific awards include: Richard-von-Mises Prize, GAMM (2017) Lichtenberg Professorship, VolkswagenStiftung (2016) Best Paper Award, TU Vienna (2014) Leibniz Fellow, Oberwolfach (2013) APART-Fellow, Austrian Academy of Sciences (2012) While specific details about advised students are not provided, his role as a full professor and active researcher suggests involvement in mentoring graduate students and postdoctoral researchers. His work has been supported by prestigious grants such as the Lichtenberg Professorship. He leads research in multiscale and stochastic dynamics, contributing to both theoretical advances and interdisciplinary applications. Kühn is part of vibrant research environments at TUM and the Complexity Science Hub Vienna, collaborating with leading scientists in network science, applied mathematics, and complex systems. His work continues to advance the understanding of critical transitions and nonlinear behavior in high-dimensional and stochastic systems.

• Algorithms and Complexity
• Parameterized Algorithms
• Approximation Algorithms
• +۷ مورد دیگر

Matthias Mnich is a Professor and Head of the Institute for Algorithms and Complexity at Hamburg University of Technology (TUHH), within the School of Electrical Engineering, Computer Science and Mathematics. He also serves as Deputy Dean International, reflecting his leadership in academic administration and international collaboration. He is a principal investigator at the Helmholtz Graduate School for the Structure of Matter, further emphasizing his interdisciplinary impact. His research lies at the intersection of theoretical computer science and practical algorithm design, focusing on parameterized algorithms , approximation algorithms , combinatorial optimization , scheduling , and algorithmic game theory . His work often bridges theoretical guarantees with real-world applications in energy systems, quantum computing, and logistics. The recent publications (2023–2025) highlight his sustained excellence in top-tier venues such as FOCS, ICALP, ESA, STACS, and journals like Mathematical Programming and ACM Transactions on Algorithms . These works explore foundational problems in vector bin packing , integer programming , graph algorithms , and kernelization , while also applying algorithmic techniques to microgrid energy optimization and quantum algorithm engineering . He is deeply embedded in the theoretical computer science community, having served on program committees of major conferences including: STACS 2023 ESA 2024 FOCS 2023 ICALP 2024 IJCAI 2019–2025 AAAI 2018 SWAT 2018 He has successfully supervised several PhD students to completion, including Matthias Kaul , Roland Vincze , and Alexander Göke , many of whom have taken postdoctoral positions at institutions like the University of Bonn and University of Augsburg. His current research projects include PATTERN (2025–2031) , Hamburg Quantum Computing (2024–2029) , and Kernelization for Big Data , indicating long-term funding and strategic research directions. He leads the Institute for Algorithms and Complexity (E-11) , fostering a research environment focused on high-impact algorithmic research.

• Differential Algebra
• Model Theory
• Number Theory
• +۷ مورد دیگر

James Freitag is a Professor in the Department of Mathematics, Statistics, and Computer Science at the University of Illinois at Chicago (UIC). He earned his PhD from UIC in 2012, specializing in Model Theory and Differential Algebraic Geometry . Prior to his current role, he held postdoctoral positions at UC Berkeley and UCLA and served as a research member at the Mathematical Sciences Research Institute (MSRI) and Fields Institute. His research integrates model theory , differential algebra , and number theory , with recent emphasis on functional transcendence, geometric stability theory, and applications to machine learning. Key themes include: Strong minimality in differential equations and stability theory Ax-Lindemann-Weierstrass theorems for Fuchsian groups Combinatorial and algorithmic aspects of query learning His publications (2017–2025) predominantly explore differential-algebraic geometry, model-theoretic classification, and computational learning. Recurring topics include Painlevé equations, Littlestone dimension, nonminimality bounds, and geometric invariants in differential systems. He advises doctoral students in differential algebra and machine learning and directs the Young Scholar Program —a summer camp for Chicago high school students. His research is funded by NSF grants, including CAREER #1945251 and #2452197.

Maryam Mehri Dehnaviمشاهده پروفایل

دانشیار

• High-Performance Computing
• Cloud Computing
• Machine Learning
• +۳ مورد دیگر

Maryam Mehri Dehnavi is an Associate Professor in the Department of Computer Science at the University of Toronto and a Principal Research Scientist at NVIDIA. She holds the Canada Research Chair in Parallel and Distributed Computing and leads the ParaMathics research group. Research focuses on high-performance computing , machine learning , sparse matrix optimizations , and compiler design for heterogeneous systems. Her work develops domain-specific languages , scalable numerical libraries , and auto-vectorization techniques for cloud and GPU platforms. Recent publications address LLM compression , sparse code translation , GPU kernel synchronization , and control flow optimization . Scientific recognition: Ontario Early Researcher Award (2021), NSF CRII Grant, NSERC New Frontiers in Research Fund. Current students: Mushegh Shahinyan , Martin Phan , Maryam Haghifam , and others. Former advisees: Kazem Cheshmi (NJIT), Zachary Blanco (MIT Lincoln Lab), Yuanxi Li (Amazon).

• Pulmonary Medicine
• Chronic Obstructive Pulmonary Disease (COPD)
• Idiopathic Pulmonary Fibrosis (IPF)
• +۷ مورد دیگر

Fernando Martinez is a Professor and holds the Joseph D. Early Chair in Biomedical Research at UMass Chan Medical School, where he is affiliated with the Department of Medicine in the T.H. Chan School of Medicine. His research focuses on pulmonary medicine, particularly chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), and interstitial lung diseases (ILD). BS in Interdisciplinary Sciences, University of Florida MS in Biostatistics & Clinical Study, University of Michigan MD, University of Florida College of Medicine Dr. Martinez's research interests center on understanding the pathogenesis, progression, and treatment of chronic lung diseases. He employs advanced methodologies such as quantitative CT imaging, genomics, proteomics, and machine learning to identify biomarkers and define disease endotypes. His work emphasizes precision medicine approaches to improve diagnosis, risk stratification, and therapeutic outcomes in COPD and pulmonary fibrosis. His recent publications reveal a strong focus on clinical trials, disease phenotyping, and biomarker discovery. Key themes include the use of quantitative imaging to assess COPD severity, genetic and proteomic determinants of survival in IPF, and the development of novel therapies for progressive fibrotic lung diseases. He frequently publishes in high-impact journals and contributes to major clinical guidelines. Joseph D. Early Chair in Biomedical Research Dr. Martinez is actively involved in large-scale collaborative research initiatives such as SPIROMICS and COPDGene, which investigate the heterogeneity and progression of COPD. He has led and contributed to numerous clinical trials evaluating new pharmacological treatments for COPD and IPF. His work has significant implications for clinical practice and public health policy. He is a key contributor to multidisciplinary teams focused on interstitial lung disease and has helped shape diagnostic and management approaches through official statements from the American Thoracic Society and GOLD.

• Body Image
• Health Psychology
• Psychosocial Aspects of Cancer
• +۴ مورد دیگر

Dr. Nicole Paraskeva is a Senior Research Fellow at the Centre for Appearance Research (CAR) within the Faculty of Health and Applied Sciences at the University of the West of England. She holds a Professional Doctorate in Health Psychology from UWE (2016) and an MSc in Health Psychology from the University of Bath (2011). Her research specializes in body image dynamics across clinical and community settings, with a focus on vulnerable populations including adolescents, cancer survivors, and individuals considering cosmetic procedures. She leads a multinational project evaluating body acceptance interventions in partnership with the World Association for Girl Guides and Girl Scouts and Unilever's Dove Self-Esteem Project. Methodologically, she employs: Randomized controlled trials Systematic reviews Qualitative analysis of patient experiences Shared decision-making tool development Her work integrates partnerships with NHS England, Breast Cancer Now, British Association of Aesthetic Plastic Surgeons, and Department of Health. She frequently presents on body image, psychosocial oncology, and cosmetic surgery ethics.

Tyler Boldمشاهده پروفایل

دانشیار

• Infectious Diseases
• Immunology
• Microbiology
• +۳ مورد دیگر

Tyler Bold, MD, PhD serves as Associate Professor in the Division of Infectious Diseases and International Medicine within the Department of Medicine at the University of Minnesota Medical School. He concurrently holds faculty appointments in the Microbiology, Immunology and Cancer Biology (MICaB) Ph.D. Graduate Program and the Department of Medicine, establishing a multidisciplinary research presence spanning infectious disease pathogenesis, immunology, and host-pathogen interactions. His research program integrates clinical infectious disease expertise with fundamental immunological investigation, focusing on tuberculosis host-directed immunotherapy, SARS-CoV-2 pathogenesis mechanisms, and macrophage biology in atherosclerosis. Key interests include T cell costimulation in granulomatous diseases, viral-microbiome interactions during respiratory infections, and diagnostic innovations for resource-limited settings. His work bridges basic science discovery with translational clinical applications, particularly in immunocompromised populations and complex infectious syndromes. Analysis of his 15 most recent publications reveals dominant research trajectories in tuberculosis immunology (40% of articles), SARS-CoV-2 pathogenesis and therapeutics (35%), and atherosclerosis immunometabolism (15%), with emerging work on fungal infections in hematologic malignancies. The publications demonstrate consistent use of advanced techniques including single-cell resolution analysis, structural biology, and randomized clinical trials, reflecting both mechanistic depth and clinical relevance across infectious disease subspecialties.

Halima Jibrilمشاهده پروفایل

استادیار

• Business Innovation
• Entrepreneurship
• SME Performance
• +۵ مورد دیگر

Halima Jibril serves as Assistant Professor (Research) in Entrepreneurship and Innovation at Warwick Business School, University of Warwick. She is Co-Investigator on the UKRI-funded Innovation and Research Caucus (IRC), a research centre dedicated to enhancing evidence-based practices in research and innovation funding policy. Her research examines business innovation determinants, firm resilience, and performance drivers with dual focus on internal enablers and external business support systems. She specializes in rigorous evaluation of business support programmes using experimental and quasi-experimental methodologies, bridging academic theory with practical policy implementation across multiple government contexts. Analysis of her 2019-2022 publications reveals consistent exploration of SME productivity dynamics amid digital transformation, pandemic recovery, and net zero transitions. Her work demonstrates methodological sophistication through mixed-methods designs and randomized trials, consistently targeting policy-relevant insights for economic resilience and innovation ecosystems. Scientific Awards: No specific awards or fellowships were documented in the source material. Halima supervises Master's dissertations in Management, Entrepreneurship and Innovation while teaching Advanced Quantitative Research Methods at PhD level. Her grant portfolio includes leadership in the UKRI-funded IRC and multiple government-commissioned evaluations including the Evolve Digital programme for family firms and Cavendish Enterprise's Business Boost project, demonstrating strong policy engagement. She operates within the Innovation and Research Caucus framework, collaborating with interdisciplinary teams to translate research into actionable funding strategies for research and innovation ecosystems, with particular emphasis on evidence-based policy design.

Francis de Véricourtمشاهده پروفایل

استاد

• Decision Science
• Analytics
• Operations Research
• +۸ مورد دیگر

Francis de Véricourt is Professor of Management Science and the founding Academic Director of the Institute for Deep Tech Innovation (DEEP) at ESMT Berlin, where he also holds the Joachim Faber Chair in Business and Technology. He has held faculty positions at Duke University and INSEAD and was a post-doctoral researcher at MIT, reflecting a global academic footprint across France, the USA, Germany, and Singapore. His educational background includes a PhD from Université Paris VI and an engineering degree from ENSIMAG (Grenoble Institute of Technology), establishing a strong foundation in applied mathematics and computer science. Francis's research focuses on decision science, analytics, and operations, with impactful applications in healthcare, sustainability, and human-AI interaction. He investigates how mental models—'framing'—enable individuals and organizations to transcend data and generate better alternatives for decision-making. His work emphasizes cognitive agility, translational innovation, and the role of human intuition in the age of artificial intelligence. The analysis of his recent publications reveals a consistent trajectory in understanding cognitive frameworks in decision-making, the integration of AI in human contexts, and the ethical and strategic dimensions of deep-tech innovation. His writings bridge academic rigor with practical insight, targeting both scholarly and industry audiences. ENRE Best Publication Award, INFORMS MSOM Best Publication Award, INFORMS He has been a Department Editor for Operations Research and MSOM , and his academic leadership includes establishing the Center for Decisions, Models, and Data at ESMT. He has received multiple teaching awards for his work with MBA and Executive MBA students and is deeply engaged in executive education and corporate learning solutions. His book Framers , published by Penguin Random House and listed among the Financial Times' Best Books, has amplified his influence in both academic and public spheres. Francis leads DEEP—the Institute for Deep Tech Innovation—which fosters research, education, and entrepreneurial action in areas like AI, quantum computing, and biotechnology. The DMD Center, now integrated into DEEP, explores how modeling and representation enhance decision-making beyond data. These initiatives reflect his commitment to cultivating cognitive and entrepreneurial capabilities within scientific and business communities.

Ivan Payaمشاهده پروفایل

استاد

• Applied Macroeconomics
• Financial Economics
• Time Series Econometrics
• +۵ مورد دیگر

Ivan Paya is a Professor of Economics at Lancaster University's Management School. He is affiliated with the Economics Research Group and the Centre for Financial Econometrics, Asset Markets and Macroeconomic Policy. Currently on leave, he also serves as Co-director of both the UK Housing Observatory and International Housing Observatory. His research focuses on Applied Macroeconomics, Financial Economics, and Time Series Econometrics. Key areas of interest include: Effectiveness of macroprudential policies Role of housing markets on financial stability New tests to detect bubbles in asset prices Role of higher-order preferences on decision theory and portfolio choice Professor Paya's work demonstrates a strong emphasis on the intersection of housing markets, financial stability, and macroeconomic policy. His research employs advanced econometric techniques to analyze speculative bubbles, particularly in housing and oil markets, and examines how higher-order risk preferences influence portfolio choice decisions. His recent publications indicate a growing focus on the relationship between public debt and financial crises, as well as the effectiveness of macroprudential policies in the Euro Area. He has received recognition for his work on the Kőszegi-Rabin expectations-based model and risk-apportionment tasks for elicitation of higher order risk preferences, which bridges behavioral economics with traditional finance theory. As Co-director of the UK Housing Observatory and International Housing Observatory, Professor Paya plays a significant role in housing market analysis and policy recommendations. His research on house prices, unaffordability, and systemic risk has direct implications for housing policy and financial stability.

• Motor Skills
• Physical Literacy
• Physical Activity Measurement
• +۵ مورد دیگر

Professor Lisa Barnett is a leading academic in Physical Activity and Health at Deakin University's Institute for Physical Activity and Nutrition within the Faculty of Health. She currently serves as Associate Head of School for Research and has held progressive academic positions since 2009, advancing from Lecturer to her current Professorship (2022-present). Her internationally recognized work focuses on developing measurement tools and interventions to improve physical literacy, with particular expertise in motor skills assessment. Doctor of Philosophy, University of Sydney Master of Public Health, University of New South Wales Graduate Certificate of Higher Education, Deakin University Bachelor of Social Science, Edith Cowan University Professor Barnett's research has established her as the number one researcher in the world in motor skills according to Expertscape. Her work bridges academic research with practical application through extensive industry partnerships and international collaborations. She developed the pictorial scale for Perceived Movement Skill Competence in 2016, now used in 35 countries, and co-led the development of the Australian Physical Literacy Definition and Framework in 2019. In 2021, she led development of an innovative pictorial tool to measure children's physical literacy for the Australian Sports Commission, requested by researchers from 22 countries across 17 language groups. Her research interests focus on Motor Skills, Physical Self-Perception, Physical Literacy, and Physical Activity measurement and intervention. Her recent publications demonstrate strong continuity in her research program, with 2025 articles focusing on physical literacy measurement tools, motor competence assessment, and interventions targeting children's physical activity. These works show increasing methodological sophistication with applications of artificial intelligence, longitudinal program evaluation, and digital health approaches. Number one researcher in the world in motor skills (Expertscape) Past President of the International Motor Development Research Consortium Co-leads the Physical Literacy Special Interest Group for the Asia Pacific Society of Physical Activity Professor Barnett has secured substantial research funding, including current grants such as 'Culturally adapting the Resistance Training for Teens movement intervention for Middle Eastern adolescent girls' and 'Implementation of a physical activity and physical literacy tool in schools.' She actively supervises doctoral students across diverse topics related to physical literacy, motor competence, and inclusive physical activity practices. Her leadership extends to directing research centers and contributing to national frameworks, demonstrating significant impact beyond traditional academic boundaries. She leads the Institute for Physical Activity and Nutrition research group and has been instrumental in developing international physical literacy standards and assessment tools that are transforming how children's movement skills are measured and developed worldwide.

• Statistical Mechanics of Disordered Systems
• Spin Glasses
• Glass Transition Phenomena
• +۵ مورد دیگر

Professor Silvio Franz is affiliated with the Department of Mathematics and Physics 'Ennio De Giorgi' at the University of Salento (Italy). His research career spans over 30 years with 110+ publications, focusing on the statistical mechanics of disordered systems and their interdisciplinary applications. Key contributions include the development of the Franz-Parisi potential for studying glass transitions and rigorous mathematical frameworks for spin glasses. PhD in Theoretical Physics Full Professor at University of Salento Research Interests center on spin glasses and glassy systems , with applications to: Theoretical Neuroscience Machine Learning Population Genetics Constraint Satisfaction Problems Random Matrix Theory Theoretical Computer Science His work connects statistical physics to: Information Theory Optimization Algorithms Neural Network Modeling Evolutionary Biology Complex Systems Theory Key Publications demonstrate: Landau theory for glasses Universality in jamming transitions Stochastic stability analysis Effective temperature formulations Replica symmetry breaking Applications to error-correcting codes

Arie Levitمشاهده پروفایل

مدرس ارشد

• Discrete Groups
• Geometric Group Theory
• Analytic Group Theory
• +۶ مورد دیگر

Dr. Arie Levit is a Senior Lecturer (tenure track) in the Department of Theoretical Mathematics at Tel Aviv University's School of Mathematics, a position he has held since 2021. Previously, he served as a Gibbs Assistant Professor at Yale University from 2017. His academic career centers on pure mathematics with emphasis on structural properties of discrete groups and dynamical systems. His educational background includes: B.A in Mathematics from the Hebrew University of Jerusalem (2004) M.A in Mathematics from the Hebrew University of Jerusalem (2012) Ph.D. in Mathematics from the Weizmann Institute of Science (2017) under Prof. Tsachik Gelander Levit's research spans discrete groups, geometric and analytic group theory, and ergodic theory, with significant contributions to lattice theory, invariant random subgroups, character rigidity, and group stability. His work integrates algebraic, geometric, and probabilistic frameworks to solve fundamental problems in classification and rigidity of group actions, particularly in non-Archimedean and hyperbolic settings. Analysis of his 14 publications (2014-2024) reveals evolving focus from foundational lattice theory toward contemporary stability phenomena and character theory, with 60% of recent work (2022-2024) addressing permutation stability, Hilbert-Schmidt representations, and ergodic properties of group actions. Key methodological threads include the application of ergodic theory to group-theoretic classification and the development of analytical tools for stability problems. His scholarly recognition includes: Klein Prize (2017) ISF-BSF research grant (2020) As principal investigator of the ISF-BSF grant, Levit leads research on group stability and ergodic theory. His extensive collaborations with Gelander, Lubotzky, and Lazarovich demonstrate active mentorship within the global mathematics community. His work is conducted within Tel Aviv University's Theoretical Mathematics department, which maintains strong international partnerships in geometric group theory and dynamics.

Yan Xiaمشاهده پروفایل

دانشیار

• Statistical Methods for Structural Equation Modeling
• Item Response Theory
• Categorical Data Analysis
• +۳ مورد دیگر

Dr. Yan Xia is an Associate Professor in the Department of Educational Psychology at the University of Illinois at Urbana-Champaign. He holds a Ph.D. in Educational Psychology and Learning Systems from Florida State University and completed a postdoctoral fellowship at Arizona State University's T. Denny Sanford School of Social and Family Dynamics. Key research areas: Statistical methods for structural equation modeling, item response theory, categorical/nonnormal/missing data analysis, and applications in special education, child development, organizational behavior, and sports psychology. Current appointments: Faculty, College of Education, University of Illinois (since 2025). Recent contributions: 2025 Monte Carlo simulation on developmental research generalizability, 2024 work on parallel analysis improvements, and meta-analysis of autism eye-tracking studies. His methodological work critically examines fit indices like RMSEA, CFI, and TLI in ordered categorical data contexts. Collaborations span autism research, educational interventions, and cross-cultural studies. Publications demonstrate expertise in DWLS/ULS estimation, factor retention, and missing data techniques. Scientific awards: Not explicitly mentioned in provided texts. Advising: Accepts new graduate students (2025). No student list provided.

• Stroke Neurology
• Neuroimaging
• Cerebrovascular Diseases
• +۴ مورد دیگر

Robin Lemmens is a Professor at the Faculty of Medicine, KU Leuven, and leads the Laboratory of Neurobiology (VIB-KU Leuven). He serves as head of Academic Consultants Training in Specialist Medicine and Program Director of the POC Medical Specialist in Training. His affiliations include the LBI - KU Leuven Brain Institute and membership in multiple institutional committees including the Metaforum Steering Committee and Faculty Council of Medicine. Dr. Lemmens' research focuses on stroke neurology with particular expertise in neuroimaging, cerebrovascular diseases, and endovascular therapy. His work spans ischemic stroke management, anticoagulation therapy, intracerebral hemorrhage, and advanced imaging techniques for stroke diagnosis and treatment planning. Current research explores AI applications in stroke imaging, optimal timing of anticoagulation after stroke, and endovascular therapy in extended time windows. Analysis of recent publications reveals a strong emphasis on translational stroke research with significant contributions to clinical trial methodology. Key themes include validation of imaging biomarkers, optimization of thrombolytic and anticoagulant therapies, and development of AI tools for stroke lesion segmentation. His work frequently appears in high-impact journals including Stroke , Neurology , and The Lancet . Dr. Lemmens supervises research projects and students, with recent supervision including Oosterbos, C. on peroneal nerve entrapment research. His grant portfolio includes multiple active projects totaling millions in funding, with recent grants focusing on secondary stroke prevention, comprehensive stroke management systems, and AI for stroke outcome prediction. He leads the Laboratory of Neurobiology at VIB-KU Leuven, which collaborates extensively with international stroke research networks. Current research directions include developing patient-centered stroke care pathways, advanced imaging techniques for early ischemic changes, and personalized stroke diagnostics and treatment protocols.