جستجوی استاد راهنمای دانشگاهی

• Applied Mathematics
• Nonlinear Waves
• Integrable Systems
• +۵ مورد دیگر

Peter Miller is a Professor in the Department of Mathematics at the University of Michigan, Ann Arbor. He holds a Ph.D. in Applied Mathematics from the University of Arizona (1994) and has held academic positions at institutions such as Monash University (Australia) and SAMSI (USA). His research focuses on applied analysis, integrable systems, nonlinear waves, and asymptotic methods. Key areas include the study of Painlevé equations, dispersive shock waves, and Riemann-Hilbert problems. Miller has led the Applied and Interdisciplinary Mathematics graduate program and is an active mentor, overseeing numerous Ph.D. students and postdoctoral researchers. Education: Ph.D., University of Arizona (1994); M.S., University of Arizona (1991); B.S. (Summa Cum Laude), Southern Methodist University (Mathematical Sciences and Computer Science, 1989). Research interests span asymptotics of nonlinear waves, random matrix theory, and special functions. His work emphasizes multiscale phenomena and modulation theory in integrable systems. Notable contributions include studies on the semiclassical limit of the nonlinear Schrödinger equation and universality in dispersive hydrodynamics. Awards include NSF grants (2022, 2018, 2015), a Simons Fellowship (2013), and a Sloan Fellowship (2002). He has delivered plenary lectures at international conferences and authored the textbook Applied Asymptotic Analysis (AMS, 2006). Teaching responsibilities include graduate courses in applied analysis, integrable systems, and partial differential equations. He has coordinated large undergraduate programs and mentored over 30 students and postdocs. Miller serves on editorial boards for journals like Journal of Nonlinear Science and organizes conferences on dispersive equations and inverse scattering.

Indranil Chowdhuryمشاهده پروفایل

استادیار

• Theory and Numerical Analysis of PDEs
• Nonlocal/Fractional order Problems
• Fully Nonlinear Equations

Indranil Chowdhury is an Assistant Professor in the Department of Mathematics and Statistics at the Indian Institute of Technology Kanpur. He holds a Ph.D. from Tata Institute of Fundamental Research, Centre for Applicable Mathematics in Bengaluru (2017) and has previously served as a Postdoctoral Researcher at University of Zagreb, Croatia (2020-2022) and Norwegian University of Science and Technology, Trondheim, Norway (2018-2020). Ph.D: Tata Institute of Fundamental Research, Centre for Applicable Mathematics, Bengaluru, India (2017) PG: Tata Institute of Fundamental Research, Centre for Applicable Mathematics, Bengaluru, India (2012) UG: St. Xavier's College, Kolkata, India (2010) Dr. Chowdhury's research focuses on the theory and numerical analysis of partial differential equations, with particular expertise in nonlocal and fractional order problems and fully nonlinear equations. His work bridges theoretical mathematics with practical applications in areas such as mean field games, optimal control, and mathematical modeling. His research program demonstrates a consistent trajectory of advancing the mathematical understanding of complex nonlocal phenomena through rigorous analytical techniques and innovative numerical methods. His publication record reveals a strong focus on fractional calculus, nonlocal diffusion processes, and mean field games. The research shows progression from foundational work on fractional Poincaré inequalities to increasingly sophisticated studies of fully nonlinear mean field games with both local and nonlocal diffusions. His recent work (2023-2025) demonstrates continued innovation in the field, particularly in addressing strongly degenerate cases and establishing precise error bounds for numerical approximations. Dr. Chowdhury maintains an active research program with consistent publication output in high-impact journals such as Foundations of Computational Mathematics, SIAM Journal on Numerical Analysis, and Discrete and Continuous Dynamical Systems. His collaborative work with researchers across international institutions reflects the global significance of his contributions to the field of nonlocal partial differential equations.

Wang Li-Lianمشاهده پروفایل

استاد

• Applied Mathematics
• Numerical Analysis
• Spectral Methods
• +۵ مورد دیگر

Professor Wang Li-Lian is a faculty member in the Division of Mathematical Sciences at Nanyang Technological University (NTU), Singapore. He holds the rank of Professor of Applied Mathematics and has been affiliated with NTU since 2006, progressing through roles including Assistant and Associate Professor before his current position. His research focuses on spectral methods, computational acoustics/electromagnetics, and PDE-based image processing. He has supervised multiple PhD and Master's students, including Zhang Jing, Gu Ying, Yang Zhiguo, and others. Education and career highlights include a Postdoctoral Research Associate at Purdue University (2002-2003), followed by a Visiting Assistant Professorship (2003-2005). His academic work spans spectral element methods, fractional differential equations, and high-order numerical techniques for wave scattering problems. Notable contributions include advancements in spectral-Galerkin methods for nonlocal operators and exact nonreflecting boundary conditions for Maxwell's equations. Research interests emphasize high-accuracy numerical schemes, with applications to fractional PDEs, metamaterial simulations, and image processing. His publications (over 100+ articles) reflect expertise in spectral methods, computational physics, and mathematical modeling. Teaching responsibilities include courses on partial differential equations, numerical analysis, and scientific computing.

• Biological mathematics
• Financial mathematics
• Numerical solution of differential and integral equations
• +۳ مورد دیگر

Assoc. Professor Mariano Rodrigo is affiliated with the University of Wollongong. His primary research focuses on Biological mathematics , Financial mathematics , Numerical solution of differential and integral equations , and Dynamical systems in applications . His work bridges applied mathematics with real-world problems in tourism economics and physical sciences. Research Funding: Weather, climate & geological risks: derivative pricing & risk management (2024–2026, ARC Discovery Project) Modelling the post-stagnation stage of a tourism area life cycle (2023, UOW Internal Grant) Teaching & Supervision: Current PhD supervision topics include Derivative Pricing for Geological Risks , Mathematical Models for Time of Death Estimation , and Weather/Climate Risk Modelling .

Tim Rogersمشاهده پروفایل

استاد

• Stochastic Processes
• Random Matrix Theory
• Collective Behavior
• +۴ مورد دیگر

Professor Tim Rogers is affiliated with the University of Bath as a faculty member in the Department of Mathematical Sciences . He is actively involved in research spanning complex systems, network theory, and stochastic processes. PhD in Random Matrix Theory from King's College London (2010) His research focuses on emergent behavior in random systems , including: Collective Behavior : Crowd dynamics, lane formation, and noise-enhanced synchronization Epidemics & Networks : Spread prediction, node risk assessment, and misinformation impacts Ecology & Evolution : Trait emergence, species boundaries, and demographic noise effects Random Matrix Theory : Spectral analysis and applications to complex systems Publication trends reflect interdisciplinary work bridging Physics, Biology, and Mathematics , with a focus on network structures , stochastic modeling , and emergence phenomena . Scientific awards include: 2015 : Editor's Choice for Europhys. Lett. 109, 28005 2016 : Highlight of Journal of Physics A 2017 : Editor's Suggestion for Phys. Rev. E 92, 032708 He has supervised numerous PhD students and postdocs on projects related to stochastic dynamics , network modeling , and mathematical biology , with ongoing grants from agencies like EPSRC and The Leverhulme Trust .

• Applied Probability
• Operations Research
• Computational Biology
• +۴ مورد دیگر

Hiroshi Toyoizumi is a Professor at Waseda University's Faculty of Commerce and Graduate School of Accountancy, with a Ph.D. in Mathematical Physics from Waseda University. His work bridges Applied Probability , Operations Research , and Computational Biology , focusing on stochastic modeling across biological and network systems. Research Interests Stochastic Models in Biology : Analyzing social queues in hover wasps and meiotic DSB regulation using quasi-birth-death processes and survival analysis. Network Security : Modeling computer virus spread on scale-free networks and proposing active defense strategies. Queueing Theory : Developing analytical frameworks for on-demand streaming, quantum merging, and blockchain-based systems. Article Trends Recent work (2020-2024) explores nonlocal diffusion , quantum queueing , and swarm behavior in financial markets . Mid-2010s studies focus on cooperative breeding and DNA recombination dynamics . Early papers (pre-2010) examine computer virus ecology , secure group communication , and deterministic queue analysis . Scientific Awards Biotechno 2013 Best Paper Award IEICE Switching Workshop SSE Research Award (1999) IEICE Young Research Engineer Award (1997) Teaching Activities Graduate-level courses in Operations Research and Financial Engineering . Undergraduate and graduate seminars in Applied Mathematics and Probabilistic Models .

Shulei Zhangمشاهده پروفایل

استادیار

• Theoretical Condensed Matter Physics
• Magnetism
• Topological Quantum Materials
• +۵ مورد دیگر

Shulei Zhang is an Assistant Professor in the Department of Physics at Case Western Reserve University's College of Arts and Sciences. He earned his Ph.D. from the University of Arizona in 2014 and specializes in theoretical condensed matter physics. His research investigates spin-charge transport in topological materials, magnetization dynamics, and quantum phenomena in magnetic systems. Research Focus Professor Zhang's group studies: Coupled spin/charge transport in topological quantum materials (e.g., insulators/semimetals) Magnetotransport in hybrid magnetic-organic-oxide structures Skyrmion dynamics and topological Hall effects Chiral magnetoplasmons arising from Berry phase phenomena Magnon transport in ferromagnetic/antiferromagnetic heterostructures This work aims to enable advances in spin-based electronics and quantum computation. Collaborations and Group He maintains active partnerships with the CATS Center (DOE Energy Frontier Research Center), Argonne National Laboratory, National University of Singapore, University of Tokyo, Fudan University, and other global institutions. His laboratory welcomes undergraduate/graduate students and postdoctoral researchers interested in condensed matter theory.

Hong Wangمشاهده پروفایل

استاد

• Numerical Analysis
• Differential Equations
• Fractional Calculus
• +۳ مورد دیگر

Hong Wang is a Professor in the Department of Mathematics at the University of South Carolina, part of the McCausland College of Arts and Sciences. He specializes in numerical analysis and differential equations, with a focus on numerical methods for fractional and variable-order equations. His work addresses complex boundary conditions, optimal control, and scientific computing challenges in advection-diffusion systems. Education Ph.D. in Mathematics, University of Wyoming (1992) Research Interests His research emphasizes numerical approximation techniques for differential/integral equations, particularly fractional diffusion-wave equations, variable-order models, and stochastic systems. Key areas include finite element methods, spectral methods, and fast algorithms for solving high-dimensional and time-dependent problems. He explores applications in optimal control, viscoelasticity, and multi-scale modeling. Recent Work Trends Recent publications highlight advancements in fractional calculus applications, including variable-exponent diffusion, distributed-order equations, and stochastic fractional differential equations. His work often combines theoretical analysis with computational efficiency, addressing challenges like nonsmooth parameters and singular density functions. Grants and Advising No specific grants or advisees are listed, but his research collaborations span computational mathematics, applied physics, and engineering systems. Labs/Teams No dedicated lab or team is explicitly mentioned, though his research aligns with computational and applied mathematics groups at the University of South Carolina.

Alex Kiselevمشاهده پروفایل

استاد

• Fluid Mechanics
• Partial Differential Equations (PDEs)
• Mathematical Biology
• +۳ مورد دیگر

Alex Kiselev is the William T. Laprade Professor of Mathematics at Duke University, part of the Trinity College of Arts & Sciences. He holds a B.S. in Physics from St. Petersburg State University (1992) and a Ph.D. in Mathematics from Caltech (1996). His research focuses on partial differential equations, fluid mechanics, mathematical biology, combustion, and Schrödinger operators. He has held positions at the University of Chicago, University of Wisconsin-Madison, Rice University, and Duke University since 2018. Kiselev's work explores fluid dynamics, singularity formation in PDEs, and mathematical biology, with notable contributions to chemotaxis and turbulence. He has been honored with the Alfred P. Sloan Research Fellowship and the Guggenheim Fellowship. Education: B.S., Physics, St. Petersburg State University, 1992 Ph.D., Mathematics, California Institute of Technology, 1996 Awards: Alfred P. Sloan Research Fellowship Guggenheim Fellowship Editorial Roles: Managing Editor, Duke Mathematical Journal Associate Editor, Communications in Mathematical Sciences

Margaret Beckمشاهده پروفایل

استاد

• Partial Differential Equations
• Dynamical Systems
• Nonlinear Waves
• +۴ مورد دیگر

Margaret Beck is a Professor and former Director of Undergraduate Studies in the Department of Mathematics and Statistics at Boston University. She holds a PhD from Boston University and has held postdoctoral positions at the University of Surrey, MSRI, and Brown University. Her research focuses on partial differential equations and dynamical systems, particularly analyzing the long-time behavior of solutions and stability of nonlinear waves. She has received prestigious awards including the 2019 SIAM J.D. Crawford Prize and the 2018 AMS Birman Fellowship. Education: Bachelor's degree from Colorado College PhD in Mathematics from Boston University Research Interests: Nonlinear waves and coherent structures Spectral and nonlinear stability analysis Pattern formation in dissipative systems Applications to fluid dynamics and mathematical physics Awards: 2019 SIAM J.D. Crawford Prize 2018 AMS Birman Fellowship 2012 Sloan Research Fellowship Advising: Supervised 11 graduate students and postdocs, including Montie Avery and Jonathan Jaquette. Actively mentors through the AWM Mentor Network. Current advising handled by Prof. Matt Szczesny during her 2025 sabbatical. Labs/Community: Co-organizes the GeMs group supporting gender minorities in mathematics at BU and co-founded the GeMsGetMath@BU summer math camp for high school students. Engages in initiatives promoting diversity in STEM, including presentations at EDGE and WISE@Warren programs.

• Nonlinear Partial Differential Equations
• Mathematical Physics
• Semiconductor Theory
• +۷ مورد دیگر

Ansgar Jüngel is a Full Professor for Analysis of Nonlinear Partial Differential Equations (PDEs) at the Technische Universität Wien (TU Vienna), affiliated with the E101-Institute for Analysis and Scientific Computing. His academic journey includes roles at universities in Berlin, Konstanz, Mainz, and Vienna since 1991. He specializes in mathematical analysis of cross-diffusion systems, entropy methods, semiconductor models, and quantum fluid dynamics. Notable achievements include an ERC Advanced Grant (2021) and the Tsungming-Tu Award (2011). Research focuses on nonlinear PDEs with applications in physics, engineering, and biology, emphasizing rigorous existence theory, numerical methods, and entropy-based approaches. Recent projects include 'Emerging network structures and neuromorphic applications' and 'Taming complexity in partial differential systems.' His teaching includes courses on partial differential equations, calculus of variations, and computational finance. Publications span over 200 works, with key contributions on cross-diffusion models, quantum hydrodynamics, and energy-transport systems. He has supervised numerous PhD students and collaborates internationally on topics like semiconductor simulations and stochastic interacting particle systems. Grants include an FWF Special Research Programme and ERC funding.

Fan Lamمشاهده پروفایل

دانشیار

• Biomedical Imaging
• MRI
• Molecular Imaging
• +۵ مورد دیگر

Fan Lam is an Associate Professor in the Department of Bioengineering at the University of Illinois Urbana-Champaign (UIUC), affiliated with the Grainger College of Engineering. He also directs the MS in Biomedical Image Computing (MS-BIC) program. His primary research focuses on developing advanced imaging techniques such as biomedical imaging, MRI, molecular imaging, and image reconstruction to study brain function and diseases. Lam holds a Ph.D. in Electrical and Computer Engineering from UIUC (2015), an M.S. in the same field from UIUC (2011), and a B.S. in Biomedical Engineering from Tsinghua University (2008). He is affiliated with multiple institutes, including the Carle-Illinois College of Medicine, the Carl R. Woese Institute for Genomic Biology, and the Beckman Institute for Advanced Science and Technology. Lam serves as a journal editor for Frontiers in Physics , Medical Physics , and IEEE Transactions on Medical Imaging . His work bridges engineering and neuroscience, with grants from NIH and other agencies supporting Alzheimer’s research and imaging innovations. Research highlights include epigenetic MRI, high-resolution volumetric MRI, and integrating AI with imaging methods. Lam’s team collaborates across disciplines to address challenges in medical imaging and brain mapping. His lab, the Quantitative Multiscale Imaging Group, develops tools for molecular and biochemical analysis of the brain.

Nikos Kavallarisمشاهده پروفایل

دانشیار

• Applied Mathematics
• Mathematical Biology
• Nonlinear Partial Differential Equations
• +۳ مورد دیگر

Nikos Kavallaris is an Associate Professor at Karlstad University, specializing in Applied Mathematical Analysis. His research focuses on deterministic and stochastic modeling of biological, ecological, and industrial systems, including chemotaxis, tumor growth, MEMS technology, and uncertainty quantification. He collaborates with institutions like Osaka University and Brown University. He teaches modules such as Optimization and Applied Mathematics for Engineers. Kavallaris holds a PhD from the National Technical University of Athens (2000) and has held academic positions at Aegean University and the University of Chester. He co-organizes the 2024 Equadiff conference’s minisymposium on Nonlocal PDEs. His work bridges theoretical mathematics with applications in biology, engineering, and environmental science. Education: PhD in Applied Mathematics, National Technical University of Athens (2000) Postdoctoral Research: University of Wrocław (EU HYKE project), Osaka University (COE program) Collaborations: Osaka University, Heriot-Watt University, Sorbonne Paris Nord, Brown University Research Interests: Nonlinear PDEs, stochastic modeling in biology/ecology, MEMS device dynamics, and topological data analysis. His work addresses phenomena like tumor growth, DNA methylation, and industrial processes such as ohmic heating and metal welding. He explores quenching dynamics, blow-up solutions, and bifurcation theory in nonlocal models. Publications: Over 50 articles on topics ranging from stochastic MEMS models to cancer immunology, emphasizing nonlinear dynamics and uncertainty quantification. Recent work examines flood exposure in Sweden and immune infiltration patterns in breast cancer. Grants/Awards: Involved in EU Marie-Curie projects and collaborative research initiatives. His contributions span theoretical analysis and application-driven research in interdisciplinary fields. Labs/Teams: Active in international research networks, leading projects on nonlocal PDE applications and mathematical biology.

Junping Shiمشاهده پروفایل

استاد

• Partial Differential Equations
• Dynamical Systems
• Mathematical Biology
• +۴ مورد دیگر

Junping Shi is a Professor in the Department of Mathematics at the College of William & Mary, where he has held academic positions since 2000, including serving as Department Chair from 2018 to 2022. He earned his undergraduate degree from Nankai University (1990–1993) and a Ph.D. from Brigham Young University (1998). His research focuses on partial differential equations, dynamical systems, and mathematical biology, with applications in pattern formation, population dynamics, and ecological modeling. Shi's academic work emphasizes the analysis of reaction-diffusion equations, bifurcation theory, and nonlocal models in biological systems. His recent studies include tumor growth modeling, spatial movement with memory effects, and phytoplankton-virus interactions. He has contributed to understanding pattern formation in aquatic and terrestrial ecosystems, including marsh vegetation dynamics and predator-prey interactions. His research spans theoretical analysis (e.g., stability, bifurcation, and well-posedness) and applied models in ecology and epidemiology. Notable applications include modeling blue crab population dynamics in Chesapeake Bay and the biodegradation of organic matter influenced by bacterivorous grazing. Shi frequently explores the interplay between spatial heterogeneity, temporal delays, and nonlinear interactions in biological systems.

Andrew Stewartمشاهده پروفایل

استاد

• Oceanography
• Dynamical Oceanography
• Antarctic Ocean Dynamics
• +۲ مورد دیگر

Andrew Stewart serves as Professor in the Department of Atmospheric and Oceanic Sciences at the University of California, Los Angeles (UCLA), directing the Dynamical Oceanography Group. His research centers on high-latitude ocean circulation physics with specialized focus on Antarctic margin dynamics and climate system interactions. Research interests span dynamical oceanography, Antarctic ice-ocean-atmosphere coupling, and submesoscale processes in polar regions. The group employs advanced simulation methodologies to investigate ocean circulation behavior and its responses to environmental forcing, particularly emphasizing Southern Ocean dynamics and ice sheet interactions. Recent publication trends reveal concentrated investigation into Southern Ocean energy cascades, Antarctic meltwater feedbacks, and global ocean eddy dynamics. Work integrates satellite observations, numerical modeling, and experimental approaches to address climate-relevant oceanographic phenomena. Scientific Awards: No awards documented in provided materials Advising and Grants: Professor Stewart supervises eight graduate researchers including Garrett Finucane, Kaylie Cohanim, and Cheng-Yang (Sunny) Yeh as evidenced by the 2025 group roster. External funding sources remain unspecified in available documentation though research scope implies National Science Foundation and climate-focused grant support. Labs and Teams: The UCLA Dynamical Oceanography Group maintains experimental facilities including rotating tank systems for dynamical studies. Current team composition reflects interdisciplinary collaboration across ocean modeling, satellite data analysis, and polar field research domains.