جست‌وجوی استاد و پژوهشگر

Juan J. Manfrediمشاهده پروفایل

استاد

• Partial Differential Equations
• Nonlinear Analysis
• Subelliptic Equations
• +۴ مورد دیگر

Juan J. Manfredi is a Professor of Mathematics at the University of Pittsburgh's Department of Mathematics, part of the Dietrich School of Arts and Sciences. He holds a PhD from Washington University in St. Louis, focusing on quasiregular mappings and partial differential equations. His research emphasizes elliptic and parabolic PDEs of p-Laplacian type, sub-Riemannian manifolds, and game-theoretic interpretations of equations like the infinity Laplacian. He explores regularity properties of p-harmonic functions and their applications in stochastic processes and signal processing. His work spans nonlinear potential theory, subelliptic equations, and geometric analysis. Notable contributions include studies on Monge-Ampère equations, viscosity solutions, and the interplay between stochastic games (e.g., tug-of-war) and PDEs. He has collaborated on topics like Carnot groups, Heisenberg group geometry, and Riemannian approximations in sub-Riemannian settings. Recent publications highlight advancements in asymptotic mean-value formulas, BMO estimates for solutions, and convergence principles for dynamic programming. His research bridges pure analysis and applied problems, including mass transport and optimal control. While no formal awards are listed, his extensive bibliography and academic roles reflect significant scholarly impact. Manfredi maintains an active online presence with resources like the QuasiWorld page, offering lecture notes and computational tools. His work often intersects with probability, geometric analysis, and numerical methods, positioning him at the forefront of modern nonlinear PDE research.

Yi Liمشاهده پروفایل

مدرس

• Fluid Mechanics
• Turbulence
• Flow Optimization
• +۳ مورد دیگر

Dr. Yi Li is a Lecturer in Applied Mathematics at the School of Mathematical and Physical Sciences, University of Sheffield. His research focuses on fluid mechanics, particularly turbulence, with emphases on flow optimization, simulation, and stochastic modeling. He explores topics such as downscaling in multi-scale systems, data assimilation for turbulence modeling, and chaos synchronization in turbulent flows. Research Themes: Downscaling: Explores self-similarity properties in turbulent flows to improve subgrid-scale modeling. Flow Optimization: Combines machine learning and data assimilation to enhance turbulence predictions, addressing challenges like pollution control and weather forecasting. Stochastic Modelling: Investigates particle and bubble dynamics in turbulent flows to understand mixing and dispersion processes. Teaching: Dr. Li teaches advanced modules including Operations Research, Magnetohydrodynamics, and Topics in Advanced Fluid Mechanics. Publications: His work spans fluid dynamics, computational methods, and signal processing, with notable contributions to turbulence modeling, ultrasonic applications, and data-driven approaches. Recent publications focus on machine learning applications in bubbly flows and 4DVAR data assimilation techniques. PhD Supervision: Offers supervision in fluid mechanics, turbulence, and interdisciplinary projects combining data science with fluid dynamics. Prospective students can contact him via email .

• Composite Materials
• Additive Manufacturing
• Finite Element Analysis
• +۳ مورد دیگر

Joris J.C. Remmers is an Associate Professor of Composite Materials at the Department of Mechanical Engineering, Eindhoven University of Technology (TU/e). He is also affiliated with the EAISI High Tech Systems and leads the Mechanics of Materials research group. His academic journey includes a MSc in Aerospace Engineering (TU Delft, 1998) and a PhD in Computational Mechanics (TU Delft, 2006). Remmers' research focuses on composite materials and additive manufacturing, particularly the relationship between manufacturing processes, microstructure, and mechanical properties. He employs advanced numerical techniques to study multi-physics phenomena across scales. Research Themes: Composite materials and fiber-reinforced systems 3D printing and additive manufacturing processes Numerical methods (e.g., finite element analysis, model order reduction) Micromechanical modeling of material behavior Grants and Projects: Project Manager for Innovation test bed for development and production of nanomaterials for lightweight embedded electronics (2019–2023) Awards: Emerging DMD Based Systems and Applications Best Paper Award (2025) Teaching: Leads courses on advanced manufacturing, computational mechanics, and data-driven approaches in engineering, including Advanced and Additive Manufacturing and AI-assisted innovation in portable plasma technology . Labs/Teams: Active in the Mechanics of Materials group, collaborating on multi-scale mechanics, damage modeling, and material failure analysis.

• Nutritional Biology
• Entomology
• Obesity Research
• +۴ مورد دیگر

Professor Stephen Simpson AC FAA FRS is a leading academic in nutritional biology and entomology at the University of Sydney. As a Professor in the School of Life and Environmental Sciences, he holds adjunct roles including Executive Director of Obesity Australia and former Academic Director of the Charles Perkins Centre. His research focuses on the Geometric Framework of nutrition, swarming behaviors in locusts, and dietary impacts on human and animal health. Simpson earned his undergraduate degree from the University of Queensland and PhD from the University of London before a 22-year tenure at the University of Oxford. He has been honored with prestigious awards including Fellowship of the Royal Society and Companion of the Order of Australia. His work bridges ecological, physiological, and societal dimensions of nutrition, with over 300 publications and collaborations across disciplines. Research interests include integrative nutrition modeling, metabolic biology, and public health interventions. Current projects explore precision nutrition, macronutrient balance in aging, and dietary influences on chronic diseases. Simpson leads a multidisciplinary team at the Sydney Centre for Healthy Societies and Sydney Policy Lab, addressing obesity and sustainable diets. His work has been translated into bestselling books like The Nature of Nutrition and Eat Like the Animals , bridging scientific research with public education. Notable achievements include co-developing the protein leverage hypothesis, elucidating locust swarm neurochemistry, and serving as a scientific advisor for documentaries like Great Southern Land . Awards include the Eureka Prize, NSW Scientist of the Year, and Honorary Fellowship from the Royal Entomological Society. Grants and collaborations span national and international institutions, focusing on aging, metabolic health, and food systems. Current research students investigate topics like macronutrient signaling, dietary effects on neurological conditions, and heart health optimization. Simpson’s lab integrates animal models (mice, birds, fish) with human studies, employing techniques from neurophysiology to computational modeling. His work emphasizes translational impact, aiming to inform policy and clinical practice through rigorous, cross-scale biological inquiry.

David Ruleمشاهده پروفایل

دانشیار

• Harmonic Analysis
• Partial Differential Equations
• Pseudodifferential Operators
• +۷ مورد دیگر

David Rule is an Associate Professor (Docent) in the Department of Mathematics at Linköping University, affiliated with the Faculty of Science and Engineering. His research lies at the intersection of harmonic analysis and partial differential equations, with a focus on pseudodifferential, Fourier integral, and oscillatory integral operators. He also contributes significantly to mathematics education, both through teaching and pedagogical development at Didacticum. Education: PhD in Mathematics, University of Chicago, 2007 MSc in Mathematics, University of Chicago, 2003 MMath in Mathematical Physics, University of Sussex, 2001 His research interests center on the analytical properties of operators arising in PDEs, particularly their boundedness, regularity, and solvability in various function spaces. He investigates multilinear and degenerate forms of these operators, often under non-standard conditions such as Carleson measure control or non-symmetry. In mathematics education, he emphasizes reasoning, proof, and communication, challenging the notion that mathematics is inherently difficult by fostering intuitive development alongside logical rigor. The recent publications reflect a sustained focus on multilinear harmonic analysis, especially the boundedness of oscillatory and Fourier integral operators in both classical and weighted settings. His work spans pure analysis, with deep connections to operator theory and function spaces, and applied contexts such as fluid mechanics. The trend shows increasing collaboration and generalization beyond classical Calderón-Zygmund theory. Scientific Awards: No specific awards mentioned in the text. David Rule advises no listed students, but he teaches a range of courses from introductory calculus to advanced PDEs and graduate-level topics. He has received research support from institutions including the Simons Foundation. His work with Didacticum and academic unions like SULF and Saco-S highlights his commitment to improving teaching practices and defending academic autonomy. He is a member of the Division of Analysis and Mathematics Education (ANDI), where he contributes to interdisciplinary research in analysis and pedagogy. His union roles include service on the national and local SULF boards and Linköping's Saco-S council, emphasizing collegiality and democratic values in academia.

Pan Heمشاهده پروفایل

استادیار

• Deep Learning
• Computer Vision
• Artificial Intelligence
• +۱۲ مورد دیگر

Pan He is an Assistant Professor in the Department of Computer Science and Software Engineering at Auburn University, part of the Samuel Ginn College of Engineering. His research focuses on developing deep learning techniques for real-time AI applications in infrastructure systems, including computer vision, 3D point cloud processing, and intelligent transportation. Education: Ph.D. in Computer Science, University of Florida B.E. in Software Engineering, Sichuan University (2015) His research interests include deep learning, computer vision, LiDAR, 3D perception, and adversarial machine learning. He develops AI techniques to empower downstream applications such as traffic signal control, anomaly detection, and infrastructure monitoring. Much of his work involves unsupervised and self-supervised learning on spatiotemporal data. His recent publications span top venues like TPAMI, ICLR, NeurIPS, CVPR, and IEEE T-ITS, focusing on topics such as explainable video anomaly detection, backdoor attacks in 3D detection, and efficient LiDAR annotation. These works demonstrate a strong trend toward robust, real-time, and interpretable AI systems for real-world infrastructure. Scientific Awards: 2025 ORAU Ralph E. Powe Junior Faculty Enhancement Award CVPR'22 and ICCV'21 Doctoral Consortium Awards Multiple Gartner Group Graduate Fellowships (2020–2022) Dean’s Award for Innovation and Creativity (SIAT, 2016) Best Bachelor Thesis Award (Sichuan University, 2015) Pan He advises students who have earned recognitions such as the CRA Outstanding Undergraduate Researcher Honorable Mention and the Wolotsz Graduate Fellowship. He has secured research grants and is actively recruiting PhD, Master’s, and undergraduate students. He has served as an Associate Editor for IEEE TNNLS and has taught courses on deep learning and computer vision. He leads a research group focused on foundational AI for pervasive computing and infrastructure intelligence.

David Wai-lok Cheungمشاهده پروفایل

استاد

• Database Systems
• Data Mining
• E-commerce Technologies
• +۵ مورد دیگر

Professor David Wai-lok Cheung is a Professor in the Department of Computer Science at the University of Hong Kong (HKU) and Director of the Center for E-commerce Infrastructure Development (CECID). He holds a BSc in Mathematics from the Chinese University of Hong Kong and MSc/PhD in Computer Science from Simon Fraser University, Canada. His research focuses on database systems, data mining, e-commerce technologies, and secure computation. Key contributions include pioneering work on privacy-preserving data mining, XML schema design, and e-commerce infrastructure development. He has led numerous prestigious grants totaling over HK$60M and developed widely adopted open-source tools like the ebXML gateway. Professor Cheung has received awards such as the HKU Outstanding Researcher Award (1999) and the Distinguished Contribution Award (2009 PAKDD). He actively contributes to academia through leadership roles in conferences like PAKDD and CIKM. His research spans secure computation, data interoperability, and bioinformatics, with over 150 publications in top venues like SIGMOD, VLDB, and KDD. **Grants & Funding**: Highlighted grants include HK$6.6M for eLogistics Appliance (2007-2008) and HK$9.198M for a service-oriented e-transaction platform (2006-2008). **Publications**: Over 150 papers in areas like privacy-preserving data mining, XML query processing, and spatiotemporal data analysis. **Service**: Member of RGC Engineering Panel, Hong Kong Deposit Protection Scheme board, and Certification Board for IT Professional Certification.

Ingo Neumannمشاهده پروفایل

استاد

• Engineering Geodesy
• Geodetic Analysis Methods
• Sensor Technology
• +۵ مورد دیگر

Prof. Dr.-Ing. Ingo Neumann is a Professor of Engineering Geodesy and Geodetic Analysis Methods at Leibniz University Hannover's Faculty of Civil Engineering and Geodetic Science. He serves as Executive Director of the Geodetic Institute and leads research in geodetic sensor systems, structural monitoring, and multi-sensor fusion. His work focuses on advancing terrestrial laser scanning (TLS), UAV-based calibration, and machine learning applications in civil infrastructure analysis. Research interests include deformation monitoring, sensor calibration, and geospatial data processing. Notable projects involve fusion of SAR/InSAR data with TLS for ground movement analysis, and development of automated damage detection algorithms for port and marine structures. He teaches courses on sensor technology, geodetic measurement methods, and industrial surveying. Publications span 2006–2025, with recent emphasis on robust outlier detection, Kalman filter applications, and B-spline modeling for structural analysis. His work integrates geodesy with computer vision and machine learning to enhance infrastructure monitoring precision.

• Genomics
• Genome-Wide Association Study
• Medical Imaging
• +۸ مورد دیگر

Gennady Roshchupkin is an Assistant Professor at Erasmus MC, jointly affiliated with the Department of Radiology & Nuclear Medicine and the Department of Epidemiology. His research bridges medical imaging, genomics, and artificial intelligence to investigate complex diseases and developmental conditions. His primary research interests include: Genome-wide association studies (GWAS) Medical imaging analysis using AI and neural networks Craniofacial synostosis and pediatric craniofacial development Alzheimer's disease and neurodegenerative disorders Gut microbiome and metabolic health across the lifespan Population-based epidemiological studies The recent publications indicate a strong trend toward integrating AI with genetic and imaging data to uncover biological and clinical insights. His work frequently involves large-scale data analysis, latent-space modeling, and interdisciplinary collaboration across medicine, computer science, and public health. Although no specific awards are listed in the provided text, his publications in high-impact journals such as The Lancet Regional Health - Europe and Medical Image Analysis reflect significant scholarly contributions. He has also supervised at least two research trainees or doctoral students. Dr. Roshchupkin is actively engaged in clinical and population research, particularly in observational cohort studies and AI-driven medical image analysis. His work is supported by collaborations across departments and institutions, focusing on improving clinical outcomes through data science and precision medicine.

Sten Claessensمشاهده پروفایل

مدرس ارشد

• Gravity Field Modelling
• Geoid Determination
• Coordinate Reference Frames
• +۳ مورد دیگر

Dr. Sten Claessens is a Senior Lecturer at Curtin University's School of Earth and Planetary Sciences, within the Faculty of Science and Engineering. He holds a BSc and MSc in Geodesy from Delft University of Technology (Netherlands) and a PhD from Curtin University. His research focuses on gravity field modelling, geoid determination, and coordinate reference frames. He teaches courses on measurement adjustment analysis, control surveying, and applied geodetic surveying. Dr. Claessens has contributed extensively to global and regional geoid models, including the AUSGeoid2020 and Indian gravimetric geoid solutions. His work integrates satellite gravity data (GRACE, GOCE) and terrestrial observations to improve vertical datums and geodetic standards. He has authored/co-authored over 60 papers, with recent emphasis on hydrological loading studies and ultra-high-resolution gravity models. His ORCID profile (https://orcid.org/0000-0003-4935-6916) and Google Scholar page document his international collaborations and computational geodetic methodologies. Education: BSc/MSc (Delft University), PhD (Curtin University). Professional roles include membership in the International Association of Geodesy and editorial contributions to Journal of Geodesy . He leads Curtin's geoid computation research, collaborating with agencies like Australia's National Geospatial Intelligence Agency on vertical datum modernization. Research highlights include the Colorado geoid experiment (2020), development of layer-based gravity field models (2016), and Mars gravity validation studies (2012). Teaching responsibilities span advanced geodetic surveying units with practical field components.

Thomas Madsenمشاهده پروفایل

مدرس

• Differential Geometry
• Partial Differential Equations
• Mathematical Physics
• +۷ مورد دیگر

Dr Thomas Madsen is a Lecturer and Lead for Teaching and Quality in the School of Computing and Engineering at the University of West London. He previously served as a Lecturer at the University of Buckingham and held academic positions at Aarhus University (Denmark), Centro di Ricerca Matematica Ennio De Giorgi (Pisa), and King’s College London. His academic work bridges pure mathematics and applied computing disciplines. His research interests include Differential Geometry , Partial Differential Equations in geometric contexts , Special Holonomy Manifolds , and Toric Geometry , with recent expansion into Neuromorphic Robotics , Spiking Neural Networks , and Computing Education . He applies symmetry techniques to solve geometric PDEs such as Einstein’s equations and explores practical implementations of neuromorphic systems on low-power hardware. The trend in his recent publications (2020–2025) shows a dual focus: one on deep mathematical structures in differential geometry and theoretical physics, and another on innovative applications in artificial intelligence, robotics, and pedagogy in computing education. His collaborative work with researchers like Nicola Russo and Konstantin Nikolic emphasizes interdisciplinary innovation. Self-learning neuromorphic robot based on reward-driven Spiking Neural Network (2025) Enhancing Learning and Teaching Experience for International Students in Computing Subjects (2025) An Implementation of Communication, Computing and Control Tasks for Neuromorphic Robotics on Conventional Low-Power CPU Hardware (2024) Special holonomy manifolds with torus symmetry (2023) An interface platform for robotic neuromorphic systems (2023) Dr Madsen teaches across a broad portfolio of programs including BSc and MSc degrees in Data Science, Mathematics and Computing, Artificial Intelligence, Cyber Security, and Biomedical Engineering. He supervises PhD students and contributes to curriculum development, particularly in enhancing educational experiences for international students. He has collaborated with advisees such as Sama Aleshaiker and Wei Jie on pedagogical research. While no specific grants are detailed, his active research output and teaching leadership suggest sustained scholarly engagement. He is associated with research groups or labs focused on neuromorphic computing and mathematics for computing, contributing to both theoretical and applied advancements. His work on teaching resources and educational practice indicates a strong commitment to academic quality and innovation in STEM education.

• Structural Health Monitoring
• Wave Propagation
• Structural Dynamics
• +۹ مورد دیگر

Fabio Semperlotti is a Professor of Mechanical Engineering at Purdue University's School of Mechanical Engineering. His research focuses on advanced materials, structural health monitoring, wave propagation, and vibration control. He holds M.S. degrees in Aerospace and Astronautic Engineering from the University of Rome 'La Sapienza' (2000, 2002) and a Ph.D. from The Pennsylvania State University (2009). His work spans topics such as acoustic metamaterials, topological elastic systems, fractional-order elasticity, and machine learning applications in engineering. Recent contributions include studies on non-Abelian topological behavior in elastic waveguides and reinforcement learning frameworks for microelectronic component design. Semperlotti’s research also explores vibration attenuation via metastructures and deep learning-based inverse scattering solutions. Selected recent projects involve developing physics-informed neural networks for acoustic scattering, multimesh finite element methods for nonlocal elasticity, and geometric phase analysis in elastic systems. His work frequently bridges fundamental theory with practical applications in smart materials, structural optimization, and energy harvesting.

Alexandre Eremenkoمشاهده پروفایل

استاد

• Complex Analysis
• Value Distribution Theory
• Differential Equations
• +۳ مورد دیگر

Alexandre Eremenko is a Professor in the Department of Mathematics at Purdue University, USA. His research focuses on complex analysis, value distribution theory, differential equations, and their geometric applications. He has made significant contributions to Nevanlinna theory, meromorphic functions, and complex dynamics. Eremenko is known for his work on the geometric theory of meromorphic functions and applications to spectral theory, including studies of Sturm-Liouville operators and conic singularities in differential geometry. Education details are not explicitly listed in the source materials, but his academic trajectory is evident through his prolific research output and collaborations with prominent mathematicians such as Mikhail Lyubich and Andrei Gabrielov. His research interests span topics like conformal metrics, holomorphic dynamics, and spectral loci of differential operators. His articles explore advanced mathematical concepts, including the topology of conformal metrics, interactions between function theory and dynamics, and geometric aspects of meromorphic functions. He has collaborated on foundational papers in complex analysis and contributed to the understanding of historical figures like Lars Ahlfers and Pierre Fatou. Despite his extensive publication record and research impact, no awards or grants are explicitly mentioned in the provided texts. He maintains an active presence in academic discourse, co-authoring works on topics ranging from PT-symmetric quartic potentials to spherical polygons and combinatorial geometry.

Hans Waltherمشاهده پروفایل

استاد

• Algebra
• Commutative Algebra
• Algebraic Geometry
• +۳ مورد دیگر

Dr. Hans Walther is a Professor of Mathematics at Purdue University's Department of Mathematics within the College of Science. His research focuses on Algebra, Commutative Algebra, and Algebraic Geometry, with a particular emphasis on D-modules, cohomology, and algorithmic methods in algebraic geometry. His work integrates theoretical advancements with computational techniques, addressing topics such as hypergeometric families, Milnor fiber cohomology, and Gröbner bases. Notable contributions include studies on Segre products, algorithmic stratifications, and homological methods in algebraic structures. Walther has authored or co-authored over 16 publications in prestigious journals such as the Journal of the American Mathematical Society and Compositio Mathematica, reflecting his expertise in advanced algebraic and geometric theories. He maintains an active research agenda without currently listed advising roles or grants, though his work influences computational algebraic geometry and related fields.

• Mechanical Engineering
• Manufacturing
• Incremental Forming
• +۳ مورد دیگر

Marthe Vanhulst is a researcher affiliated with the Department of Mechanical Engineering at KU Leuven, specializing in incremental sheet metal forming and its applications in biomedical engineering. She works in the MaPS division (Manufacturing and Process Systems) and contributes to collaborative research initiatives like Flanders Make, the strategic research center for the manufacturing industry in Flanders. Research Interests Development of advanced manufacturing techniques for complex geometries Application of machine learning in optimizing sheet metal forming processes Biomedical applications of incremental forming, particularly cranial implants Knowledge management systems for industrial engineering workflows Integration of Digital Image Correlation for strain and thickness analysis Publication Trends Her research focuses on improving the geometric accuracy and thickness distribution in multi-stage incremental forming. Key themes include toolpath optimization, intermediate shape design, and digital compensation methods. Recent work integrates collaborative platforms for knowledge sharing in manufacturing, reflecting interdisciplinary efforts between mechanical engineering and computer science. Laboratory Affiliation Marthe is part of the Manufacturing and Process Systems (MaPS) research group at KU Leuven, which collaborates closely with Flanders Make. Her projects emphasize industrial partnerships and translating theoretical advancements into practical solutions for precision manufacturing.