جست‌وجوی استاد و پژوهشگر

Yuk Ka Chungمشاهده پروفایل

مدرس ارشد

• Forensic Statistics
• Bioinformatics
• Protein Modelling

Dr. Yuk Ka Chung is a Senior Lecturer in Statistics and Probability at the Department of Mathematics, University of Manchester (since March 2024). Previously, they held roles as Teaching Fellow at the same department (2022–2024) and Lecturer at the University of Hong Kong's Department of Statistics and Actuarial Science (2013–2022). They hold a PhD in Statistics from the University of Hong Kong (2011), an MPhil from Chinese University of Hong Kong (1993), and a BSc in Statistics (1991). Education Highlights: PhD in Statistics: University of Hong Kong (2006–2011) MPhil in Statistics: Chinese University of Hong Kong (1991–1993) BSc in Statistics: Chinese University of Hong Kong (1987–1991) Research focuses on Forensic Statistics, Bioinformatics, and Protein Modelling. Key contributions include methodologies for DNA mixture analysis, database search applications in forensics, and Bayesian frameworks for evidence evaluation. Their work bridges statistical theory with practical legal contexts, emphasizing likelihood ratios and missing data handling in DNA evidence. Advising and grants details are not explicitly provided in the text. Teaching includes courses like Multivariate Statistics and Mortality Modelling in Insurance.

Jonas Latzمشاهده پروفایل

مدرس

• Bayesian Inference
• Uncertainty Quantification
• Stochastic Processes
• +۵ مورد دیگر

Jonas Latz is a Lecturer in Applied Mathematics at The University of Manchester. His research focuses on Bayesian inference, uncertainty quantification, stochastic processes, and their applications in computational mathematics and inverse problems. He has contributed to areas such as physics-informed neural networks, stochastic gradient methods, and medical imaging modeling. Key research interests include developing robust algorithms for Bayesian inverse problems, analyzing stochastic dynamical systems, and advancing numerical methods for partial differential equations. His work bridges theoretical foundations with practical applications in fields like tumor growth modeling and medical image reconstruction. Recent Achievements : Recipient of the SIAM Activity Group Uncertainty Quantification Early Career Prize (2024) SIAM Student Paper Prize (2020) SIGEST Award (2023) Dr. Latz collaborates internationally on topics such as adversarial machine learning, deep learning methods for PDEs, and stochastic sampling techniques. His research emphasizes rigorous mathematical analysis alongside computational innovation.

Pearson Millerمشاهده پروفایل

استاد

• Mathematical Biology
• Nonlinear Dynamics
• Biophysics
• +۳ مورد دیگر

Professor Pearson Miller is a faculty member in the Department of Physics at the University of California San Diego (UCSD). He holds a PhD in Physics from MIT (2020) and previously served as a Flatiron Research Fellow at the Center for Computational Biology at the Flatiron Institute (2020–2024). His research focuses on nonlinear dynamics applied to biological systems, including cell polarization, tissue morphogenesis, and pattern formation in developmental biology. Teaching responsibilities include advanced courses on numerical methods. His work bridges physics and biology, with a particular emphasis on mathematical modeling of biological systems. Key research areas include: Cellular mechanics and actomyosin networks Biophysical mechanisms of morphogenesis Evolution of stripe patterns in rodents Topological phenomena in cell membranes His interdisciplinary approach integrates computational modeling with experimental insights to study complex biological processes. While no awards are explicitly listed, his research has been published in top journals across physics and biology. He currently holds no listed lab affiliations or collaborative teams, though his prior fellowship at the Flatiron Institute indicates strong ties to computational biology research networks.

• Fuzzy systems
• Computational mathematics
• Numerical optimization
• +۵ مورد دیگر

Professor Gleb Beliakov is a faculty member at Deakin University's School of Information Technology within the Faculty of Science Engineering and Built Environment. He has held roles including Associate Head of School (Research) from 2009–2012 and currently leads the Computational Intelligence and Data Analytics Research cluster and the Data to Intelligence research centre. His expertise spans fuzzy systems, computational mathematics, numerical optimization, and high-performance computation. Education: PhD and MSc from the Russian Peoples Friendship University. Research Interests: Focuses on fuzzy systems, aggregation functions, parallel programming, and their applications in decision-making and data analysis. Grants: Includes projects on Trusted Autonomy (CRC), Satellite Communication Systems (Defence), and Explainable AI (ARC). His research emphasizes fuzzy measures, Choquet integrals, and their use in addressing complex problems like resource optimization and multimedia piracy. He has supervised numerous PhD and master's students, contributing to advancements in preference mining, image processing, and watermarking techniques.

Lisa Feigensonمشاهده پروفایل

استاد

• Cognitive Development
• Numerical Cognition
• Child Development
• +۳ مورد دیگر

Lisa Feigenson is a Professor and Chair in the Department of Psychological & Brain Sciences at Johns Hopkins University, affiliated with the Krieger School of Arts & Sciences. She co-directs the Johns Hopkins University Laboratory for Child Development. Her research focuses on cognitive development, particularly numerical cognition and working memory, using behavioral methods to study infants, children, and adults. Feigenson holds a PhD from New York University. Her work explores how cognitive primitives develop across lifespan, including intuitive physics understanding, numerical abilities, and memory systems. Notable awards include the Troland Award (National Academy of Sciences), Boyd McCandless Award (APA), and McDonnell Scholar Award. Her lab investigates how infants and children process numerical information, working memory limits, and learning mechanisms triggered by expectation violations. Recent studies highlight resilience of numerical cognition in congenital blindness and links between approximate number systems and formal math skills. Feigenson has published extensively in top journals like Science, Nature, and PNAS. Her research bridges developmental psychology, cognitive neuroscience, and educational applications, emphasizing foundational cognitive capacities and their development.

Roxana Smarandacheمشاهده پروفایل

استاد

• Applied Algebra
• Coding Theory
• Discrete Mathematics
• +۴ مورد دیگر

Roxana Smarandache is a Professor of Mathematics and Electrical Engineering at the University of Notre Dame, affiliated with the College of Science. She holds a B.S. from the University of Bucharest (1996), and M.S. and Ph.D. from the University of Notre Dame (1997, 2001). Her research focuses on applied discrete mathematics, particularly error control coding theory, including algebraic and combinatorial problems in code construction and analysis. She has dual appointments in the Department of Mathematics and the Department of Electrical Engineering. Education: B.S., Mathematics, University of Bucharest, 1996 M.S., Mathematics, University of Notre Dame, 1997 Ph.D., Mathematics, University of Notre Dame, 2001 Her research interests span coding theory, including LDPC codes, convolutional codes, and their applications in reliable communication systems. She has authored over 50 refereed publications and secured multiple NSF grants, such as the 2013–2017 grant on pseudocodeword analysis and the 2012–2016 collaborative grant on spatially coupled sparse codes. She has advised numerous students, including Ph.D. candidates and undergraduates in mathematics and engineering. Notable awards include the 2014 IEEE Senior Member distinction, the 2007 SDSU Most Influential Teacher Award, and the 1997 Richard Sady Graduate Student Award. She has held visiting positions at institutions like the Swiss Federal Institute of Technology (EPFL) and the University of Zurich. Her teaching spans courses in coding theory, linear algebra, and random phenomena in electrical engineering. Roxana’s work emphasizes interdisciplinary collaboration between mathematics and engineering, with contributions to code design, performance analysis, and algorithmic improvements for modern communication systems.

Weiran Sunمشاهده پروفایل

استاد

• Applied Mathematics
• Partial Differential Equations (PDE)
• Kinetic Theory
• +۴ مورد دیگر

Weiran Sun is a Professor in the Department of Mathematics at Simon Fraser University (SFU), part of the Faculty of Science. His research focuses on partial differential equations (PDEs), kinetic theory, and applied analysis, with recent interests expanding into AI applications in mathematics. He holds a Ph.D. in Applied Mathematics and Scientific Computation from the University of Maryland (2008). Research interests include: Analysis and numerical methods for kinetic equations Inverse problems related to kinetic theory Mathematical collaboration with computer scientists (e.g., DeLTA Lab at SFU for LLMs in applied math) Recent work highlights: Development of PDE-Controller using LLMs for formalization/reasoning of PDEs Studies on crossover transport phenomena and diffusion limits Contributions to numerical analysis of nonlocal equations (e.g., Lévy-Fokker-Planck) Upcoming activities include organizing the 5th SIAM Pacific Northwest Section Meeting (2025) and participating in kinetic theory programs at SLMath (Berkeley). His research spans interdisciplinary collaborations, blending traditional applied mathematics with emerging AI tools.

• Mathematics
• Optimal Control
• Number Theory
• +۴ مورد دیگر

Joshua Siktar is a Visiting Assistant Professor at Texas A&M University’s College of Arts & Sciences. His research focuses on optimal control theory, number theory, and numerical analysis, with a particular emphasis on nonlocal equations, composite numbers in arithmetic progressions, and Fibonacci compositions. He contributes to both theoretical and applied mathematics, addressing problems in peridynamics modeling, fractional optimal control, and combinatorial configurations. His work spans topics such as asymptotic compatibility in optimal design problems, Lavrentiev gap phenomena in finite element methods, and Zeckendorf’s theorem applications. He has explored central limit theorems for lattice paths and combinatorial enumeration, often integrating analytical techniques with computational methods. Siktar’s articles reflect a diverse yet cohesive research agenda, balancing foundational mathematics with interdisciplinary applications. He frequently publishes in peer-reviewed journals and maintains a website showcasing his work at people.tamu.edu .

Richard Spadyمشاهده پروفایل

استاد پژوهشی

• Econometrics
• Industrial Organization
• Empirical Political Science
• +۳ مورد دیگر

Richard Spady is a Research Professor of Economics at Johns Hopkins University's Krieger School of Arts & Sciences, a position he has held since 2010. He is also a Senior Research Fellow at Nuffield College, Oxford (since 1999) and has held academic roles at institutions such as the European University Institute and Northwestern University. Spady earned his B.A. in Economics and Philosophy from Haverford College (1973) and his Ph.D. in Economics from MIT (1978). His research focuses on econometrics, particularly methods for incorporating latent variables in structural models to analyze attitudes, skills, and their effects on behavior. Key areas include the impact of cultural/economic attitudes on voting, cognitive skills on life outcomes, and immigrant integration. He has contributed extensively to semiparametric methods and empirical likelihood techniques. Spady has advised numerous graduate students, including seven Ph.D. recipients at Johns Hopkins and three D.Phil. students at Oxford. His work has been supported by grants such as the ESRC, and he has presented at global conferences including the European Meeting of the Econometric Society. His teaching spans advanced econometrics, financial economics, and quantitative methods.

• Enumerative combinatorics
• permutations
• bijections
• +۷ مورد دیگر

Sergi Elizalde is a Professor of Mathematics at Dartmouth College, affiliated with the Department of Mathematics within the Arts & Sciences school. He holds the position of Faculty Advisor for the Byrne Scholars Program. Education: B.A., Universitat Politècnica de Catalunya Ph.D., Massachusetts Institute of Technology Research Interests: Elizalde specializes in enumerative and algebraic combinatorics, with a focus on permutations, pattern avoidance, lattice paths, bijections, generating functions, and applications to computational biology and dynamical systems. His work bridges combinatorial theory with interdisciplinary fields like cancer modeling through Markov chain models of chromosomal instability. Teaching & Mentoring: Elizalde has taught courses in graph theory, algebraic combinatorics, and calculus. He currently mentors several Ph.D. students and has advised numerous former students who have completed their doctoral degrees under his supervision. Professional Contributions: He maintains a personal research website and collaborates on projects such as the implementation of Markov chain models for studying tumor evolution. His research has been featured in high-impact journals like Nature and Advances in Applied Mathematics .

Alen Alexanderianمشاهده پروفایل

دانشیار

• Numerical Analysis
• Scientific Computing
• Inverse Problems
• +۳ مورد دیگر

Alen Alexanderian is an Associate Professor in the Department of Mathematics at North Carolina State University (NC State), serving since 2022. Previously, he was an Assistant Professor at NC State (2015-2022), a Research Associate and Postdoctoral Fellow at The University of Texas at Austin’s ICES (2012-2015), and a Postdoctoral Fellow at Johns Hopkins University (2010-2012). He earned his PhD in Applied Mathematics from the University of Maryland, Baltimore County (2010), with prior degrees including an MS (2007) and BA in Mathematics (2005) from Hood College. His research focuses on numerical analysis, scientific computing, and uncertainty quantification. Key areas include numerical methods for inverse problems, optimization under uncertainty, Bayesian inversion, and sensitivity analysis. He develops algorithms for optimal experimental design and applies these to large-scale inverse problems in engineering and science. His recent work emphasizes hyper-differential sensitivity analysis, robust optimal design under model uncertainty, and applications in PDE-constrained optimization. His studies often bridge theoretical developments with practical implementations in fields like porous media flow, biotransport, and epidemiological models. Notable contributions include frameworks for Bayesian optimal sensor placement, variance-based sensitivity analysis techniques, and scalable computational methods for high-dimensional inverse problems. His research integrates mathematical rigor with computational efficiency, addressing challenges in data assimilation, model reduction, and risk-aware decision-making.

Iain Souttarمشاهده پروفایل

پژوهشگر

• Stochastic Processes
• Probability Theory
• Numerical Analysis
• +۵ مورد دیگر

Iain Souttar is a Researcher at the Centre for Applications of Mathematical & Computing Sciences (CAMaCS) at the University of Warwick. His work focuses on interdisciplinary mathematics, particularly stochastic processes, probability, and multiscale methods applied to biological, physical, and chemical systems. Prior to this role, he completed his PhD at the MAC-MIGS Centre for Doctoral Training under supervisors Michela Ottobre and Ben Goddard, where he specialized in stochastic analysis and applied probability. His research interests include mathematical modeling, applied probability, stochastic analysis, and mathematical biology. He has contributed to studies on slow-fast dynamics, invariant measures in multiscale systems, and ergodic theory. His work bridges pure mathematics with applications in decision-making and science policy, reflected in his side projects exploring the philosophy of science and science communication. Iain holds a PhD from the Maxwell Institute Graduate School (Heriot-Watt University) and has published in journals such as AIHP and the Royal Society Proceedings A. He occasionally blogs on topics like averages in decision-making and has documented adventures in bikepacking, including a 22-day Edinburgh-London walk.

Van Vuمشاهده پروفایل

استاد

• Additive Number Theory
• Combinatorics
• Probability
• +۳ مورد دیگر

Van Vu is the Percey F. Smith Professor of Mathematics and Professor of Statistics & Data Science at Yale University. He holds a Ph.D. from Yale University (1998). His research focuses on additive number theory, combinatorics, probability, and random matrices, with significant contributions to probabilistic combinatorics and random matrix theory. He co-leads the combinatorics group at Yale, which hosts regular seminars and explores topics like random graphs, hypergraphs, and additive combinatorics. Dr. Vu has been recognized with prestigious awards, including the Polya Prize (2008) and Fulkerson Prize (2012). His work bridges theoretical mathematics and applied domains, addressing challenges in spectral analysis, network consensus dynamics, and statistical inference. He actively participates in academic service, including grant-funded research projects and collaborations on interdisciplinary topics like biocontrol agents derived from plant extracts. Education: Ph.D., Yale University, 1998 Affiliations: Department of Mathematics, Yale University Key Research Themes: Random matrix perturbation, sparse network dynamics, additive combinatorics, and applications in data science His research group emphasizes collaborative efforts, with ongoing projects on eigenvalue distribution universality, matrix completion algorithms, and probabilistic methods in combinatorics. Dr. Vu also maintains an active blog and contributes to academic conferences, reflecting his commitment to advancing both theoretical and applied mathematical research.

Jacob Birk Jensenمشاهده پروفایل

دانشیار

• Hydrology
• Groundwater Modeling
• Urban Hydrology
• +۷ مورد دیگر

Jacob Birk Jensen is an External Associate Professor in the Department of Construction, Urban and Environmental Engineering at Aalborg University, Faculty of Engineering and Science, Denmark. His work bridges hydrology, environmental engineering, and stochastic modeling, with a focus on groundwater systems and urban hydrology. Department: Department of Construction, Urban and Environmental Engineering School: Faculty of Engineering and Science University: Aalborg University Position: External Associate Professor His research interests include groundwater modeling, inverse modeling, stochastic methods, eco-hydrology, and urban drainage systems. He applies reliability theory and probabilistic modeling to assess hydrological risks and environmental impacts, particularly in groundwater-dependent ecosystems and agricultural landscapes. The recent publications show a strong trend in integrated modeling approaches, such as coupling SWAT and MODFLOW to evaluate streamflow responses to groundwater abstraction. His work spans environmental sustainability, agricultural hydrology, and coastal engineering, reflecting a multidisciplinary approach to water resource challenges. Keywords across his research include hydrology, groundwater abstraction, eco-hydrology, reliability methods, and urban drainage. He has contributed to significant research projects including: Application of Reliability Theoretical Methods in Hydrological Simulations Eco-hydrological Modeling of Stream Valleys Impact of Rising Groundwater Tables on Agricultural Land Use Rotating Wave Energy Absorber Development Jacob Birk Jensen has advised PhD students such as O. Johansen and M. L. Fejerskov. While no formal scientific awards are listed, his publications are well-cited, particularly in the areas of groundwater abstraction and fen ecosystem responses. He has also delivered lectures at international conferences, including the International Multidisciplinary Conference on Hydrology and Ecology. His research group, the Urban Hydrology section, focuses on infrastructure, hydraulic engineering, and environmental technology, contributing to sustainable urban water management and climate resilience.

Oscar Bandtlowمشاهده پروفایل

استاد

• Functional Analysis
• Dynamical Systems
• Statistical Mechanics
• +۳ مورد دیگر

Dr. Oscar Bandtlow is a Professor and Reader in Mathematics at the School of Mathematical Sciences, Queen Mary University of London, where he also serves as Director of Postgraduate Studies. His research focuses on functional analysis, operator theory, and their applications to dynamical systems, statistical mechanics, and chaotic systems. He obtained his PhD in theoretical physics from the University of Cambridge and has held academic positions at Glasgow, London, and Nottingham before joining Queen Mary in 2006. He has been a Visiting Professor at Paris-Sud, Nice Sophia Antipolis, and Cergy-Pontoise Universities. His work bridges pure mathematics and computational methods, addressing topics like transfer operators, spectral perturbation theory, and numerical techniques for dynamical systems analysis. Education: PhD in Theoretical Physics, University of Cambridge His research interests include operator-theoretic approaches to chaotic systems, spectral properties of dynamical systems, and applications of functional analysis to statistical mechanics. Notable areas of focus are the study of resonances in Anosov maps, numerical methods for analyzing billiard systems, and the interplay between symmetry and ergodic properties. His recent publications highlight advancements in dynamic mode decomposition (DMD), analysis of triangular billiards, and spectral studies of expanding circle maps. These contributions underscore his expertise in both theoretical and computational aspects of nonlinear dynamics. Dr. Bandtlow has no listed scientific awards but maintains active collaborations across Europe and contributes to academic leadership through his role in postgraduate training.