جست‌وجوی استاد و پژوهشگر

Yongli Sangمشاهده پروفایل

دانشیار

• Statistics
• High-dimensional Inference
• Correlated Data Analysis
• +۳ مورد دیگر

Yongli Sang is an Associate Professor of Statistics in the Department of Mathematics at the University of Louisiana at Lafayette. She earned her Ph.D. in Statistics (2017) and M.S. in Statistics (2014) from the University of Mississippi, and holds a M.S. (2012) and B.S. (2009) in Mathematics from institutions in China. Ph.D. in Statistics, University of Mississippi (2017) M.S. in Statistics, University of Mississippi (2014) M.S. in Mathematics, Central China Normal University (2012) B.S. in Mathematics, Shandong Normal University (2009) Her research focuses on advanced statistical methodologies for high-dimensional data, time series analysis, nonparametric statistics, and robust statistical techniques for correlated data. She has developed innovative jackknife empirical likelihood methods for testing diagonal symmetry, homogeneity of variances, and K-sample problems with applications in diverse fields. Recent publications highlight her work on Gini correlations in high-dimensional settings, computational efficiency, and confidence interval estimation. She also explores transformations of linear processes and their memory properties, bridging theoretical statistics with applied data analysis challenges. At the University of Louisiana at Lafayette, she supervises Ph.D. student Sameera Hewage and teaches graduate courses including Mathematical Statistics, Regression Analysis, and Biometry.

• Number Theory
• Cryptography
• Finite Fields
• +۴ مورد دیگر

Professor Igor Shparlinski is a faculty member at the University of New South Wales (UNSW) within the School of Mathematics & Statistics, holding the rank of Professor with an active research profile as evidenced by publications dated 2025. His work bridges pure number theory and cryptographic applications, maintaining international collaborations with institutions like the University of Sydney and Max Planck Institute. Research interests include: Analytic number theory (exponential/character sums) Cryptographic security (Diffie-Hellman, RSA, and pseudorandom generators) Finite field arithmetic and polynomial dynamics Arithmetic combinatorics and additive number theory Distribution of primes/smooth numbers modulo p Elliptic curve structures over finite fields His publications consistently address foundational problems with computational implications, particularly focusing on sum bounds and modular arithmetic. Recent trends (2023-2025) show intensified work on multilinear character sums, matrix statistics over finite fields, and dynamical system orbits. Key journals include Journal of Number Theory and Finite Fields and their Applications , with frequent co-authorship on exponential sum bounds and cryptographic vulnerabilities. Scientific awards: No awards, prizes, or fellowships are documented in the provided text. Advising and grants: No student listings or grant information appears in the source material. Research output suggests sustained funding but lacks explicit details.

Göran Kauermannمشاهده پروفایل

استاد

• Nonparametric Models
• Semi- and nonparametric analysis
• Generalized Linear Models
• +۲ مورد دیگر

Prof. Dr. Göran Kauermann is a Full Professor of Statistics at the Ludwig-Maximilians-University Munich , holding the Chair of Applied Statistics in Social Sciences, Economics and Business . His research spans nonparametric models, generalized linear models, and network data analysis, with applications in economics, epidemiology, and data science. Education: Diplom in Economic Mathematics (1991, TU Berlin), PhD in Statistics (1994), Habilitation (Venia Legendi) in Statistics (2000) Kauermann’s research interests focus on penalized regression , network analysis , and statistical modeling in economics, social sciences, and public health. Recent work explores label uncertainty in machine learning , spatio-temporal conflict diffusion , and dynamic network models for economic and social data. Scientific trends in his publications include penalized splines for nonlinear modeling, network flow estimation in social and economic contexts, and label variation analysis in machine learning. His collaborations span climate zone classification , Covid-19 mortality modeling , and smart city parking analytics . Scientific Awards: Bruce Russett Award (2020) for political network research Leadership Roles: He served as Dean of the Faculty of Mathematics, Informatics and Statistics (2019–2021), Speaker of the Elite Master Program in Data Science (2016–2026), and Chair of the German Statistical Society (2005–2013). He also held editorial roles in journals like AStA Advances in Statistical Analysis and Statistical Modelling .

Christian Langeمشاهده پروفایل

پژوهشگر ارشد

• Differential Geometry
• Geometric Topology
• Riemannian Geometry
• +۳ مورد دیگر

Christian Lange is a Research Fellow at the Mathematical Institute of Ludwig-Maximilians-Universität München (LMU Munich). He holds a PhD and specializes in differential geometry, geometric topology, and orbifold theory. His current teaching includes a lecture on Riemannian Geometry (Summer 2025), focusing on advanced topics in geometric analysis. His research emphasizes orbifold structures, geodesic flows, and curvature properties. Notable contributions include studies on closed geodesics on orbifolds, systolic inequalities, and the interplay between billiard dynamics and Alexandrov geometry. Lange collaborates internationally, addressing problems in Riemannian geometry, symplectic topology, and geometric group actions. Publications highlight work on orbifold curvature bounds, Besse metrics, and deformations of Finsler structures. His 2023 paper in Journal of the European Mathematical Society proved a diameter gap theorem for sphere quotients. He also explores connections between Lorentzian metrics and Lipschitz regularity in geometric analysis. Supported by institutions like the Simons Foundation, Lange’s work bridges pure geometry with applications in topology and mathematical physics. His research group focuses on geometry and topology, contributing to foundational questions in differential and metric geometry.

Danijela Tadićمشاهده پروفایل

استاد

• Production Engineering
• Industrial Engineering
• Decision-Making Models
• +۵ مورد دیگر

Danijela Tadić is a Professor at the Department of Production Engineering, Faculty of Engineering, University of Kragujevac, Serbia. Her primary research focuses on decision-making models under uncertainty, manufacturing process optimization, failure mode analysis, and sustainable recycling technologies in the automotive and industrial sectors. She holds a leadership role in the Faculty of Engineering, contributing to academic governance and curriculum development. Her scientific work integrates fuzzy logic systems, multi-criteria decision-making (MCDM), and optimization algorithms to address complex engineering challenges. Notable areas include risk management in supply chains, quality improvement in manufacturing processes, and environmental impact assessment of recycling equipment. She has collaborated on projects evaluating organizational resilience, strategic failure management, and resource planning in SMEs. Prof. Tadić’s publications emphasize practical industrial applications, such as PFMEA integration with fuzzy decision tools, cloud platform selection frameworks, and electric vehicle evaluation models. Her work bridges theoretical advancements in fuzzy set theory with real-world manufacturing and environmental sustainability problems. She actively participates in academic and professional networks, contributing to conferences and journals in production engineering and industrial systems. Her expertise spans project lifecycle management, lean manufacturing, and the evaluation of recycling technologies for end-of-life vehicles (ELVs).

Viviane Baladiمشاهده پروفایل

استاد

• Ergodic theory
• Dynamical systems
• Mathematical physics

Viviane Baladi is a Professor in Mathematics at the University of Copenhagen (2012–2013) and a Directeur de Recherche at the Centre National de la Recherche Scientifique (CNRS), France, from 1990 to 2024. Her research is centered on dynamical systems , ergodic theory , and mathematical physics . Fields of Interest: Dynamical systems, ergodic theory, mathematical physics. Academic Positions: CNRS Directeur de Recherche (Classe Exceptionnelle), University of Copenhagen Professor, Ecole Normale Superieure de Lyon Chargée de Recherche, ETH Zurich Assistant Professor. Baladi's publications focus on hyperbolic dynamics, Sinai billiards, and transfer operator theory. She has been awarded the prestigious ERC Advanced Grant (2018) and served as an invited speaker at the International Congress of Mathematicians (2014). Scientific Awards: ERC Advanced Grant (2018), 1.8 million Euro, for developing mathematical tools to study dynamical systems with singularities. Research Highlights: Her work includes groundbreaking results on exponential decay of correlations in Sinai billiards, Whitney-Holder continuity of SRB measures, and functional approaches to dynamical zeta functions and determinants.

• Economic Model Predictive Control
• Stability of Nonlinear Systems
• Chemical Reaction Networks Theory
• +۵ مورد دیگر

David Angeli is a Professor of Nonlinear Network Dynamics in the Department of Electrical and Electronic Engineering at Imperial College London's Faculty of Engineering. Affiliations: Control and Power Research Group Energy Futures Lab His research focuses on Economic Model Predictive Control, Stability of Nonlinear Systems, Chemical Reaction Networks Theory, Systems Biology, and Control of Smart Grids. He develops theoretical frameworks for networked systems with applications in energy infrastructure and biological processes, emphasizing robustness and scalability in distributed settings. Recent publications (2023-2025) highlight work on distributed control algorithms, Lyapunov-based stability certification, and small-gain theorems for interconnected systems. His research bridges control theory, game theory, and machine learning to solve problems in cyber-physical systems, particularly in resilient consensus protocols and economic optimization for heterogeneous networks. As a core member of the Control and Power Research Group and Energy Futures Lab, he contributes to sustainable energy solutions and advanced control methodologies for complex networked systems.

• Applied Mathematics
• Fluid Mechanics
• Mathematical Biology
• +۴ مورد دیگر

Scott McCue is a Professor of Applied Mathematics at the School of Mathematical Sciences, Queensland University of Technology (QUT), Brisbane, Australia. His academic journey includes a PhD from the University of Queensland (2000), followed by postdoctoral roles at the University of Nottingham and University of Wollongong. He joined Griffith University in 2004 before moving to QUT in 2007, progressing through academic ranks to full Professor in 2016. Education: PhD in Applied Mathematics, University of Queensland (2000) Bachelor of Science, University of Queensland Research Interests: Scott's work spans fluid mechanics, mathematical biology, and free boundary problems. Key areas include Stefan problems (melting/freezing), free surface flows, Hele-Shaw flows, and droplet impaction. His research integrates theoretical analysis with computational modeling, addressing challenges in biological systems, agricultural fluid dynamics, and complex fluid phenomena. Grants & Awards: EO Tuck Medal (2019) for research and service to ANZIAM JH Michell Medal (2009) Australian Competitive Grants: 'Mathematical and Computational Analysis of Ship Wakes' (DP180103260), 'Mathematical and computational models for agrichemical retention on plants' (LP160100707) Teaching & Supervision: Scott teaches courses in differential equations, fluid flow, and perturbation methods. His supervision focuses on moving boundary problems, nonlinear waves, and stochastic models of cell proliferation. He has advised numerous PhD and MPhil students on topics ranging from drug release modeling to ship wake analysis. Professional Engagement: Editor for journals including Proceedings of the Royal Society A and European Journal of Applied Mathematics . Active member of ANZIAM, SIAM, and the Australasian Fluid Mechanics Society.

• Supply Chain Management
• Forecasting
• Inventory Management
• +۵ مورد دیگر

Yavuz Acar is an Associate Professor at Boğaziçi University with a PhD from University of Houston. His academic expertise spans Supply Chain Management, Forecasting, and Operations Management. Dr. Acar's primary research interests include: Supply Chain Management and Integration Forecasting Methods and Error Measurement Inventory Management and Optimization Simulation and Hybrid Solution Methodologies Production and Operations Management Management Information Systems Enterprise Resource Planning His scholarly work demonstrates a consistent focus on practical applications of forecasting techniques in supply chain contexts, with particular emphasis on global supply chain networks. Dr. Acar's research often explores the relationship between forecasting accuracy and operational performance, as well as the impact of supply chain integration on organizational effectiveness. His methodological approach frequently combines mathematical modeling with empirical analysis to address complex supply chain challenges. Dr. Acar has contributed to prestigious journals including the International Journal of Forecasting, Journal of the Operational Research Society, and International Journal of Production Economics. His work bridges theoretical advancements with practical applications in supply chain management. Professional Recognition: Active contributor to the Decision Sciences Institute conferences Published in FT Press conference proceedings for Decision Sciences Dr. Acar maintains an active research agenda focusing on the intersection of forecasting methodologies and supply chain management practices, with particular attention to global supply chain networks and their operational challenges.

Granville Andrewمشاهده پروفایل

استاد

• Combinatorics
• Analytic Number Theory
• Arithmetic Geometry
• +۳ مورد دیگر

Granville Andrew is a distinguished Professor of Mathematics at University College London (since 2015) and holds the Canada Research Chair at the University of Montreal (since 2002). He has held academic roles including Chair of Mathematics at the University of Georgia (1995–2002) and visiting positions at institutions such as Trinity College Cambridge and the Institute for Advanced Study. His research focuses on combinatorics, analytic number theory, and arithmetic geometry, with notable contributions to sieve methods, multiplicative functions, and prime distribution theories. Andrew has supervised 27 PhD students and advised 32 postdoctoral researchers, delivering over 100 plenary lectures globally. He is an elected member of the Royal Society and a Fellow of the American and Royal Societies of Canada. Key awards include the CRM-Fields-PIMS Prize (2021) and the Chauvenet Prize (2008). His work bridges pure mathematics with applications in cryptography and computational number theory. Education: PhD in Mathematics, Queen's University (1987), advised by Paulo Ribenboim MSc in Mathematics, Trinity College Cambridge (1984) Research Interests: Exploring the interface between combinatorics and number theory, particularly probabilistic combinatorics applied to additive number theory Study of multiplicative functions and their spectral properties Analysis of prime distribution and limitations in equidistribution patterns Investigations into abc conjecture implications and Siegel zeros Applications of dynamical systems in arithmetic geometry Academic Impact: Proved infinitude of Carmichael numbers, resolving a longstanding conjecture Pioneered 'pretentious' approach to analytic number theory Contributed foundational work on character sums and L-functions Grants & Advising: Recipient of Canadian Research Chair funding since 2002 Presidential Faculty Fellowship (1994–1999) from President Bill Clinton Supervised 27 PhD students and advised 32 postdoctoral researchers across his career

Hong Liمشاهده پروفایل

استاد

• Actuarial Science
• Insurance Economics
• Data Analytics
• +۶ مورد دیگر

Hong Li is a Professor in the Department of Economics and Finance at the Gordon S. Lang School of Business and Economics , University of Guelph (ranked #1 in Canada for Actuarial Science). He also holds an Adjunct Associate Professor position at the University of Waterloo's Department of Statistics and Actuarial Science. His research focuses on actuarial science, insurance economics, and data analytics applied to risk management challenges in longevity, climate, and agricultural sectors. Education : PhD in Econometrics & Operations Research, Tilburg University (2015) MPhil in Economics, Tilburg University (2012) B.A. in Finance, Xiamen University (2010) Research Interests include: Machine learning for insurance underwriting and pricing Mortality forecasting and longevity risk transfer Catastrophe bond design and climate risk modeling Optimization of index-based agricultural insurance Dynamic hedging strategies for financial institutions Awards : 2018 Bob Alting von Geusau Prize (best ASTIN Bulletin paper) University Research Award (2022-2023) Grants & Funding include: SSHRC Insight Development Grant ($69,623 CAD) NSERC Discovery Grant ($127,500 CAD) CAS Individual Grant ($18,000 USD) Teaching includes courses on risk management, actuarial economics, and financial econometrics at both undergraduate and graduate levels. Professional Service : Editorial Board Member: Annals of Actuarial Science and Journal of Risk and Insurance Member, Canadian Institute of Actuaries Academic Research Committee

Behrang Noohiمشاهده پروفایل

عضو هیئت علمی

• Algebraic Topology
• Category Theory
• Algebraic Geometry
• +۶ مورد دیگر

Behrang Noohi is a Reader in Pure Mathematics at the School of Mathematical Sciences, Queen Mary University of London, and a key member of the Centre for Combinatorics, Algebra and Number Theory. His research lies at the interface of algebraic topology, category theory, and algebraic geometry, with a focus on topological stacks, higher categorical structures, and string topology. His research interests include: Algebraic Topology and Homotopy Theory of Stacks Higher Category Theory and 2-Groups String Topology and Loop Spaces Non-commutative Geometry and Moduli Spaces Group Actions and Equivariant Structures Categorical Algebra and Crossed Modules His recent publications reveal a consistent focus on foundational aspects of topological and algebraic stacks, with deep contributions to the understanding of homotopy types, fibrations, and string topology in categorical settings. He frequently collaborates with leading mathematicians such as Kai Behrend and Grégory Ginot. His scientific contributions have been recognized through sustained publication in top-tier journals and active research funding. He is a co-investigator on an EPSRC-funded project titled "Model theoretic and topos theoretic view of difference algebra and applications to dynamics" (2022–2025), receiving £473,594 in funding, indicating ongoing research leadership. He advises students in pure mathematics, though specific names are not listed in the provided text. He is involved in collaborative research teams centered around categorical and geometric structures, particularly within the Centre for Combinatorics, Algebra and Number Theory.

Cristiano Varinمشاهده پروفایل

استاد

• Statistical Methodology
• Composite Likelihood Inference
• Copula Regression
• +۳ مورد دیگر

Cristiano Varin is a Full Professor in Statistics at the Ca' Foscari University of Venice , affiliated with the Department of Environmental Sciences, Computer Science and Statistics (DAIS). He works at the Scientific Campus in via Torino and maintains the DAIS website for research and teaching updates. His research focuses on: Composite likelihood inference - A key methodological contributor with seminal papers in Biometrika and Statistica Sinica Copula regression - With practical implementations in R software Meta-analysis - Including improved likelihood inference techniques Spatial statistics - With applications to environmental data Paired comparison modeling - Applied to sports analytics and behavioral studies Recent publications demonstrate expertise in crossed random effects models (2025), ridge regression for paired comparisons (2024), and thermal comfort range analysis (2023). Scientific recognition includes: Royal Statistical Society Read Paper (2015) on journal citation modeling Gumbel Lecture (2006) by German Statistical Society Ca' Foscari Teaching Award (2020) He has collaborated with institutions including: Swiss National Science Foundation Natural Sciences and Engineering Research Council of Canada Norwegian Council of Research

Damek Davisمشاهده پروفایل

دانشیار مهمان

• Optimization
• Machine Learning
• Signal Processing
• +۴ مورد دیگر

Damek Davis is a Visiting Associate Professor at the Wharton Department of Statistics and Data Science at the University of Pennsylvania and an Associate Professor of Operations Research at Cornell University (currently on leave). He held NSF Postdoctoral Fellowships and completed his PhD in Mathematics at UCLA under Wotao Yin and Stefano Soatto. His research bridges optimization , machine learning , statistics , and signal processing , with a focus on convergence guarantees for stochastic and nonsmooth optimization methods. He has developed accelerated gradient descent algorithms, characterized SGD behavior in nonconvex settings, and formalized avoidance of strict saddle points in proximal methods. Key publications include exponential accelerations of gradient-based techniques and first guarantees for SGD on weakly convex functions. His work has been recognized by the Sloan Research Fellowship INFORMS Optimization Society Young Researchers Prize NSF CAREER Award SIAM Activity Group on Optimization Best Paper Prize Davis actively advises Penn graduate students and serves as an associate editor at Mathematical Programming and Foundations of Computational Mathematics . He emphasizes clear technical writing and public communication, maintaining a blog and lecture notes on optimization theory.

Luan Thach Hoangمشاهده پروفایل

دانشیار

• Partial Differential Equations
• Fluid Dynamics
• Porous Medium Equations
• +۳ مورد دیگر

Luan Thach Hoang is an Associate Professor in the Department of Mathematics and Statistics at Texas Tech University. He holds a Ph.D. in Mathematics from Texas A&M University (2005) and has held academic positions at institutions including the University of Minnesota and Indiana University. His research focuses on partial differential equations, fluid dynamics, porous media, and dynamical systems. Education: Ph.D. Mathematics (Texas A&M University, 2005), M.A. Mathematics (Arizona State University, 2000), B.S. Mathematics and Computer Science (National University, Vietnam, 1997). Research interests include nonlinear PDEs, fluid dynamics in porous media, and asymptotic analysis. Recent work explores Forchheimer flows, Navier-Stokes equations, and long-time behavior of solutions. He has contributed to over 50 peer-reviewed publications and has been funded by NSF grants. Teaching spans courses in differential equations, calculus, and advanced mathematics. Active in professional organizations, he has organized conferences and delivered invited talks globally. Collaborators include leading researchers in fluid dynamics and applied mathematics.