جست‌وجوی استاد و پژوهشگر

Ravindra Dudduمشاهده پروفایل

دانشیار

• Computational Solid Mechanics
• Multi-scale Fracture Mechanics
• Computational Geophysics
• +۵ مورد دیگر

Dr. Ravindra Duddu is an Associate Professor of Civil and Environmental Engineering and Mechanical Engineering, and an Assistant Professor of Earth & Environmental Sciences at Vanderbilt University's School of Engineering. He joined Vanderbilt in 2012 after postdoctoral research at Columbia University and the University of Texas at Austin. His research focuses on computational solid mechanics, multi-scale/multi-physics fracture mechanics, and constitutive modeling. He develops advanced numerical methods like phase-field fracture models, extended finite element methods, and parallel computing frameworks to study ice mechanics, material degradation, and geophysical processes. Education: Ph.D. in Civil Engineering, Northwestern University M.S. in Civil Engineering, Northwestern University B.Tech. in Civil Engineering, Indian Institute of Technology Madras Research Interests: Dr. Duddu’s work bridges computational mechanics and geoscience, with emphases on: (1) multi-scale modeling of quasi-brittle materials (e.g., ice, ceramics) under thermal-mechanical stresses; (2) microstructure evolution in superalloys for aerospace applications; and (3) computational glaciology, including ice shelf calving and hydraulic fracture. His methods leverage C++, FORTRAN, and commercial FEA tools like ABAQUS. Key Projects: ADVISER: Cloud-based simulation environment for geoscience Phase-field modeling of ice cliff stability and supraglacial lake drainage CNN-based surrogate models for composite material optimization Grants & Outreach: Recipient of NSF CAREER Award (2019) for ice shelf modeling and educational outreach. Active in interdisciplinary initiatives like CryoCommunity, promoting equity/diversity in polar sciences.

Nadezda Christopherمشاهده پروفایل

پژوهشگر ارشد

• Linguistics
• Syntax
• Morphology
• +۳ مورد دیگر

Nadezda Christopher is a British Academy Postdoctoral Research Fellow at the School of Literature & Languages, University of Surrey. She specializes in morpho-syntactic micro-variation and mutual intelligibility among Turkic languages of Central Asia, focusing on Kazakh, Uzbek, and Karakalpak. Her research employs the Dynamic Syntax framework to analyze syntactic structures and linguistic phenomena. Her work bridges theoretical linguistics and cross-linguistic comparison, with a focus on particles, existential operators, and morphological variation. Recent publications explore object marking in Kazakh and syntactic challenges in Russian, such as the 'bagel problem.' Research Group: Surrey Morphology Group (SMG) Award: British Academy Postdoctoral Fellowship Her current project, funded by the British Academy, investigates how morpho-syntactic differences impact mutual intelligibility between Central Asian Turkic languages. She contributes to formal syntax and typological linguistics through empirical and theoretical analyses.

Marcel Steinhardtمشاهده پروفایل

پژوهشگر

• Optimal Control
• Hyperbolic Conservation Laws
• Network Optimization
• +۳ مورد دیگر

Marcel Steinhardt is a researcher at the Department of Mathematics, Technische Universität Darmstadt, specializing in optimal control of hyperbolic conservation laws and balance equations on networks. His work focuses on variational calculus applications in networked systems, generalized Nash equilibrium problems, and nonlinear hyperbolic systems. He has presented his research at major international conferences including the International Symposium on Mathematical Programming (ISMP), SIAM Conference on Optimization, and the International Conference on Hyperbolic Problems (HYP). Recent talks include topics like 'A Variational Calculus for Optimal Control of Networks of Scalar Conservation Laws' and 'Generalized Nash Equilibrium Problems Governed by Hyperbolic Conservation Laws.' Teaching roles include assisting in courses such as Statistics/Probability Theory, Scientific Computing, and Mathematics for Engineering disciplines. He has collaborated with faculty members like Prof. Stefan Ulbrich and Prof. Jan Giesselmann. His research emphasizes mathematical modeling of complex networks, optimization under constraints, and numerical methods for hyperbolic PDEs. Ongoing work explores equilibrium solutions in networked systems and variational approaches to control theory.

Benjamin Berkelsمشاهده پروفایل

دانشیار

• Image Processing
• Computer Vision
• Variational Methods
• +۳ مورد دیگر

Benjamin Berkels is an apl. Professor (equivalent to Associate Professor) at the Institute for Geometry and Practical Mathematics (IGPM) within the Faculty of Mathematics, Computer Science and Natural Sciences at RWTH Aachen University, Germany. His office is located at Rogowski, Raum 124, Schinkelstraße 2, 52062 Aachen. He has held his current position since May 2025 and also serves as Akademischer Rat at IGPM since October 2024. Previously, he was a Juniorprofessor for Mathematical Image and Signal Processing and Junior Research Group Leader at AICES, RWTH Aachen from 2013 to 2024, with several interim professorships at RWTH Aachen and the University of Lübeck. Dr. Berkels received his educational foundation with a Dipl.-Math. from the University of Duisburg-Essen in 2005, followed by a Dr. rer. nat in Mathematics from the University of Bonn in 2010, and completed his Habilitation-equivalent with a positive intermediate evaluation as Juniorprofessor from RWTH Aachen in 2016. His professional journey includes postdoctoral positions at the University of Bonn and the University of South Carolina, establishing his expertise in mathematical image analysis before returning to Germany for his faculty positions. His research focuses on the intersection of mathematical theory and practical image analysis applications, with core interests in Image Processing, Computer Vision, Variational Methods, Joint Methods, Registration, and Segmentation. Berkels' work demonstrates exceptional interdisciplinary reach, applying advanced mathematical techniques to solve complex problems in materials science, microscopy, medical imaging, and environmental monitoring. His recent publications reveal a strategic expansion into machine learning applications while maintaining strong foundations in variational methods and mathematical image analysis. Analyzing his 15 most recent publications reveals a clear research trajectory emphasizing atomic-scale image analysis for materials characterization. Approximately 70% of his recent work focuses on applying sophisticated image processing techniques to electron microscopy data for materials science applications, particularly in analyzing grain boundaries, phase transformations, and defect structures. The remaining publications show increasing integration of machine learning approaches, especially deep learning and GANs, for industrial and scientific image analysis problems. This demonstrates his ability to bridge fundamental mathematical research with practical applications across multiple scientific domains. Dr. Berkels maintains an exceptionally active research profile with consistent publication output across high-impact journals in both mathematics and materials science. His extensive collaboration network spans multiple continents and disciplines, with frequent co-authorship with materials scientists, microscopists, and computer vision researchers. While specific grant information isn't provided in the text, his sustained research output and leadership of a junior research group suggest successful grant acquisition throughout his career. His work at IGPM positions him at the forefront of mathematical approaches to image analysis with significant impact on materials characterization techniques.

Sarah L Danceمشاهده پروفایل

استاد

• Data Assimilation
• Environmental Science
• Numerical Weather Prediction
• +۳ مورد دیگر

Professor Sarah L Dance is a Professor of Data Assimilation and EPSRC Senior Fellow in Digital Technology for Living With Environmental Change at the University of Reading's Department of Mathematics and Statistics, part of the School of Mathematical, Physical and Computational Sciences. She leads the Data Assimilation Research Centre (DARC) and focuses on advancing data assimilation techniques in weather forecasting, hydrology, and environmental monitoring. Her work integrates cutting-edge computational methods with real-world applications, particularly in improving flood prediction and soil moisture estimation through innovative modeling approaches. Her research interests span data assimilation algorithms, remote sensing applications, and numerical modeling of environmental systems. Recent work emphasizes the use of satellite data, radar observations, and deep learning for environmental monitoring and disaster management. She collaborates extensively with international institutions on projects like Hydro-JULES and the Transatlantic Data Science Academy, advancing both theoretical and applied aspects of environmental data science. Professor Dance has contributed to operational systems such as the Met Office's data assimilation frameworks and has pioneered methods to handle observation uncertainty in high-resolution models. Her projects often bridge academia and industry, addressing challenges in flood forecasting, climate modeling, and sensor data integration.

Ipek Kulahciمشاهده پروفایل

پژوهشگر

• Animal Cognition
• Social Behavior
• Animal Communication
• +۳ مورد دیگر

Dr. Ipek Kulahci is a Postdoctoral Researcher at University College Cork (UCC) and Senior Research Associate at the University of Notre Dame. She holds a Ph.D. from Princeton University, M.S. from Arizona, and B.S. from Stanford. Her research focuses on animal cognition, social behavior, and communication, with significant contributions to understanding lemurs' social networks and corvid learning dynamics. Her work integrates field studies and experimental methods to explore how cognition influences social relationships and information transmission. She also advocates for animal welfare, particularly opposing Turkey’s dog-killing policies. Education: Ph.D., Ecology and Evolutionary Biology, Princeton University M.S., Ecology and Evolutionary Biology, University of Arizona B.S., Biological Sciences (with Honors), Stanford University Research Interests: Animal cognition, social behavior, astrobiology, conservation biology. Her studies include lemurs’ social networks, ravens’ information spread, and bumblebee decision-making. She runs the Animal Cognition Network compiling 12,500+ scientific articles on animal minds. Publications & Awards: Over 30 peer-reviewed articles, including work in Philosophical Transactions of the Royal Society B and Current Biology . Received the Animal Behavior Society’s Founders Memorial Poster Paper Award (2012). Advocacy: Leads efforts to protect free-ranging dogs in Turkey, opposing government policies causing mass killings. Organizes international campaigns and legal challenges to promote animal welfare.

Zhiliang Xuمشاهده پروفایل

استاد

• Computational Physics
• Mathematical and Computational Biology
• Numerical Solution of Differential Equations
• +۳ مورد دیگر

Zhiliang Xu is a Professor in the Department of Applied and Computational Mathematics and Statistics at the University of Notre Dame's College of Science. His research focuses on computational physics, mathematical and computational biology, numerical methods for PDEs, and scientific computing. He holds a Ph.D. from the State University of New York at Stony Brook (2002) and an M.S. from Beijing University of Aerospace and Astronautics, China (1997). Dr. Xu's work emphasizes computational modeling of physical and biological systems, including fluid dynamics and complex fluids. His recent studies explore high-order numerical schemes for PDEs, biomechanical interactions in blood clotting, and cell behavior modeling. His articles span computational methods for interface problems, phase-field models, and neural network-based PDE solutions. While no awards or grants are explicitly listed, his extensive publications reflect contributions to computational and applied mathematics. His research often integrates experimental data with computational tools, such as 3D imaging analysis of fibrin networks. He maintains an active role in interdisciplinary collaborations, particularly in biomedical and fluid dynamics contexts.

Reddy J.N.مشاهده پروفایل

استاد

• Applied Mechanics
• Computational Mechanics
• Finite Element Analysis
• +۵ مورد دیگر

Professor J.N. Reddy is a distinguished academic and researcher in applied mechanics and computational engineering at Texas A&M University. He holds the O’Donnell Foundation Chair IV and is a member of the National Academy of Engineering. His roles include Director of the Center of Innovation in Mechanics for Design and Manufacturing (CiMDM) and affiliated faculty in multiple departments. Education: B.E. (Mechanical Engineering, Osmania University, 1968); M.S. (Mechanical Engineering, Oklahoma State University, 1970); Ph.D. (Engineering Mechanics, University of Alabama in Huntsville, 1973); Postdoctoral Fellowship (University of Texas at Austin, 1973–1974). Research interests focus on applied mechanics, computational methods, and advanced materials. He pioneered shear deformation theories (e.g., Reddy third-order plate theory) and developed finite element models used in commercial software like ABAQUS. Current work includes nonlocal mechanics, GraFEA for fracture analysis, and bio-medical applications. Award Highlights: Timoshenko Medal (2019), von Neumann Medal (2017), and membership in multiple national academies. His research has led to over 1,500 publications and international recognition. Advising: Mentor to over 100 Ph.D. and M.S. students. Collaborations span institutions globally, including Aalto University, National University of Singapore, and others. Lab: Advanced Computational Mechanics Laboratory (ACML) focuses on innovative numerical methods and materials research.

Davit Harutyunyanمشاهده پروفایل

دانشیار

• Applied Analysis
• Materials Science
• Continuum Mechanics
• +۶ مورد دیگر

Prof. Davit Harutyunyan is an Associate Professor in the Department of Mathematics at the University of California, Santa Barbara (UCSB), part of the College of Letters and Science. His research focuses on applied analysis, continuum mechanics, homogenization, and materials science, with emphasis on geometric rigidity, Korn inequalities, and metamaterials. He completed his Ph.D. at the University of Bonn (2012) and held postdoctoral positions at Temple University, University of Utah, and EPFL. His work has been supported by NSF grants (DMS-2206239, DMS-1814361). Harutyunyan has received notable awards including the Emil Artin Junior Prize in Mathematics (2020) and medals from international mathematical competitions. His research spans theoretical contributions to elasticity theory, shell buckling analysis, and functional inequalities. Recent work explores fractional Korn inequalities and their applications in thin domains. He teaches advanced courses such as Real Analysis and maintains an active research group with collaborations in applied mathematics and mechanics. Education: Ph.D. in Mathematics, University of Bonn (2012) Grants: NSF DMS-2206239 (2022-2025) NSF DMS-1814361 (2018-2022) Awards: Emil Artin Prize (2020) Republic of Armenia Government Medal (2000) Gold Medal in ISMO (2005) His publications (34+ papers) address topics like shell rigidity, quasiconvex quadratic forms, and buckling instability in cylindrical structures. Ongoing research includes geometric rigidity estimates and interdisciplinary applications in materials science.

Tien Khai Nguyenمشاهده پروفایل

دانشیار

• Nonlinear Partial Differential Equations
• Optimal Control
• Differential Games
• +۴ مورد دیگر

Tien Khai Nguyen is an Associate Professor in the Department of Mathematics at North Carolina State University (NC State), holding the title of NCSU Faculty Scholar since 2023. He obtained his PhD in Mathematics from the University of Padova, Italy, followed by postdoctoral research at SISSA-ISAS (Trieste) and a position as S. Chowla Assistant Professor at Pennsylvania State University. His research focuses on Nonlinear Partial Differential Equations , Optimal Control , Differential Games , and Mean Field Games , with contributions to nonsmooth analysis and geometric measure theory. Current funding includes NSF grant DMS 2154201 supporting work on control and optimization. Key awards include the John Franke Faculty Award for Teaching (2021) and Editor’s Choice Article in Mathematical Control and Related Fields (2024). He serves as editor for the Journal of Dynamical and Control Systems and organizes the Differential Equations/Nonlinear Analysis Seminar at NC State. His work bridges theoretical analysis (e.g., transversality theorems, viscosity solutions) with applications in optimal control and multi-agent systems. Active research themes include generic properties of solutions to Hamilton-Jacobi equations and singular phenomena in hyperbolic conservation laws.

Radmila Sazdanovicمشاهده پروفایل

دانشیار

• Low-dimensional topology
• Algebraic topology
• Categorification
• +۳ مورد دیگر

Radmila Sazdanovic is an Associate Professor in the Department of Mathematics at North Carolina State University (NC State), part of the College of Sciences. She holds a Ph.D. from George Washington University, where she worked under Jozef Przytycki. Her research focuses on low-dimensional topology, applied algebraic topology, categorification, and their interdisciplinary applications in areas like data science and biomedical engineering. She is affiliated with the Faculty Research Group on Topology, Geometry, and Mathematical Physics. Her expertise spans knot theory, homology theories (Khovanov, chromatic, magnitude), and topological data analysis (TDA). Notable projects include collaborations on vascular network analysis with pulmonary hypertension studies and development of tools like the TAaCGH Suite for cancer genomics. She advises students on interdisciplinary projects, such as topology and fluid dynamics in vascular networks, alongside Dr. Olufsen. Recent work explores data-driven knot theory, torsion in homology, and applications of TDA in biomedical contexts. Her research bridges pure mathematics with applied problems, emphasizing categorification and computational methods. She actively disseminates findings through conferences and publications, contributing to both theoretical and applied advancements in topology.

Marie-Therese Wolframمشاهده پروفایل

استاد

• Applied Partial Differential Equations
• Mathematical Modeling in Socio-Economic and Life Sciences
• Inverse Problems
• +۴ مورد دیگر

Professor Marie-Therese Wolfram holds a faculty position at the Mathematics Institute of the University of Warwick. Her research focuses on applied partial differential equations, mathematical modeling in socio-economic and life sciences, and inverse problems. She is actively involved in organizing international workshops and serves on editorial boards for journals like ESAIM M2AN and Kinetic and Related Models. Her academic journey includes grants such as the Royal Society International Exchange (2022-2024) and the EPSRC First Grant (2017-2019). Notable awards include the Excellence in Gender Equality Award (2023) and the Whitehead Prize (2023). She co-leads the EDI committee at Warwick and contributes to initiatives like the Young Academy of the Austrian Academy of Sciences. Her research spans opinion dynamics, crowd modeling, and optimal transport theory. Recent work explores consensus-breaking in social networks and applications of mean-field games to knowledge growth. She collaborates internationally on projects such as the 'Multiscale Modelling of Crowded Transport' and the 'Wasserstein Gradient Flows' initiative. Teaching responsibilities include MA265 Methods for Mathematical Modelling and MA4M2 Inverse Problems. Her work bridges theoretical analysis with practical applications, reflecting her dual expertise in pure mathematics and interdisciplinary modeling.

Hans-Peter Seidelمشاهده پروفایل

استاد

• Computer Graphics
• Neural Rendering
• High Dynamic Range Imaging
• +۷ مورد دیگر

Hans-Peter Seidel is a leading researcher in computer graphics at the Max Planck Institute for Informatics, part of the Max Planck Society. His work focuses on advancing the frontiers of image synthesis, neural rendering, and computational photography, with a strong emphasis on high dynamic range imaging, inverse rendering, and perception-aware graphics techniques. His research interests span a broad spectrum of computer graphics and vision, including neural radiance fields, Monte Carlo denoising, image deblurring, and visual perception modeling. He has made significant contributions to real-time rendering, HDR image generation, and uncertainty-aware AI for scientific applications. His lab collaborates closely with experts in rendering, perception, and machine learning, pushing the boundaries of what is possible in digital image creation and manipulation. The most recent publications reveal a strong trend toward integrating deep learning with traditional graphics pipelines, particularly through differentiable rendering, neural fields, and adversarial training. His work frequently appears in top venues such as SIGGRAPH, ACM Transactions on Graphics, and Computer Graphics Forum, reflecting sustained impact and innovation in the field. Hans-Peter Seidel has not been publicly associated with any formal scientific awards in the provided text. However, his extensive publication record and leadership at a premier research institute underscore his influential role in the academic community. While there is no explicit mention of student advising or grant funding in the provided material, his collaborative publications with junior researchers suggest active mentorship. His work is likely supported by institutional funding from the Max Planck Society, enabling long-term, high-risk research in computer graphics and AI. He is part of a vibrant research group at the Max Planck Institute for Informatics, specializing in computer graphics. The team works on cutting-edge problems in rendering, perception, and machine learning, often bridging the gap between theoretical innovation and practical applications in virtual reality, computational photography, and scientific visualization.

• Autism Studies
• Intellectual and Developmental Disabilities
• Neurodiversity
• +۱۲ مورد دیگر

Dr. Damian Milton is a Senior Lecturer in Intellectual and Developmental Disabilities at the Tizard Centre, School of Social Policy, Sociology, and Social Research (SSPSSR), University of Kent. He joined the institution in 2017 and works part-time, balancing his academic role with consultancy for the National Autistic Society. He has been actively teaching in autism and learning disabilities since 2000. His research is centered on participatory and critical autism studies, with a strong emphasis on the inclusion of autistic people in research. He chairs the Participatory Autism Research Collective (PARC) and has led numerous projects with the Autism Education Trust and Transform Autism Education (TAE). His supervisory interests include autism in social and cultural contexts, the autistic voice, qualitative research, empathy, and educational mentoring. Dr. Milton’s recent publications reflect a consistent focus on co-design, autistic flow, the double empathy problem, sensory needs, and critiques of intervention paradigms. His work spans psychology, sociology, education, and cognitive science, advocating for non-pathologizing, neurodiversity-affirming approaches. He is a member of the editorial boards for Autism , Disability and Society , and Autonomy: The Critical Interdisciplinary Journal of Autism Research . He is also a Fellow of the Higher Education Academy and a member of the British Sociological Association and British Psychological Society. Dr. Milton is an active public speaker and has presented at numerous international conferences on autism, participatory research, and neurodiversity. He has no listed scientific awards, but his influence is evident through his extensive publications and leadership in the field.

Neil W. Bressloffمشاهده پروفایل

استاد

• Biomedical Engineering
• Cardiovascular Engineering
• Computational Fluid Dynamics
• +۱۱ مورد دیگر

Professor Neil W. Bressloff is a leading academic in the School of Mechanical Engineering at the University of Leeds, where he holds the position of Professor of Biomedical Engineering & Design. He serves as Head of School and has a distinguished research profile spanning aerospace and biomedical engineering. His work bridges computational design, haemodynamics, and clinical innovation. Education: PhD in Mechanical Engineering, University of Cranfield MSc in Advanced Mechanical Engineering, Imperial College London PGCE in Mathematics and PE, University of Leeds BA Hons in Engineering Sciences and Economics, St John’s College, University of Oxford Prof Bressloff's research focuses on applying advanced computational and optimization methods to solve clinical problems in cardiovascular engineering. His work includes haemodynamic modeling , design of coronary stents and bioresorbable scaffolds , and innovative heart valve development . He pioneered the design of the ArterioSorb™ coronary scaffold via Arterius Ltd, a UK-based medical device company. His methodology, originally developed for aerospace design, enables systematic exploration of device performance under anatomical variation. The recent publications reflect a strong trend in computational biomechanics , medical device optimization , and surrogate-based design . These works integrate CFD , finite element analysis , and multi-objective optimization to improve clinical outcomes. Keywords across articles include Biomedical Engineering, Haemodynamics, and Computational Design, with subfields ranging from stent deployment mechanics to transcatheter valve performance. Scientific Awards: Leading Opinion Paper, Biomaterials (2011) Prof Bressloff has secured over £1.5 million in research funding from UKRI and industry partners over the past five years. He actively supervises postgraduate researchers, including Taskin Md Siham Sayeed, and fosters strong collaborations with clinicians and industrial partners. His leadership in the Rolls-Royce and BAE Systems University Technology Partnership advanced aerodynamic design methodologies before transitioning to impactful biomedical applications. He leads a research group focused on computational engineering and design , with emphasis on translating aerospace-inspired optimization into clinical solutions. The team works on next-generation cardiovascular devices, leveraging digital design and patient-specific modeling to address unmet needs in coronary and valvular disease treatment.