جست‌وجوی استاد و پژوهشگر

• Harmonic Analysis
• Fourier Restriction Theory
• Sharp Inequalities
• +۴ مورد دیگر

Diogo Oliveira e Silva is an Associate Professor in the Department of Mathematics at Instituto Superior Técnico, Lisbon, and holds an Honorary Senior Research Fellow position at the University of Birmingham. His academic journey includes a PhD from UC Berkeley under Michael Christ (2012), a Habilitation at Universität Bonn (2017), and prior roles at Bonn and Berkeley. His research focuses on harmonic analysis, particularly sharp inequalities, oscillatory integrals, Fourier restriction theory, uncertainty principles, and nonlinear Fourier analysis. Education: PhD in Mathematics (2012, UC Berkeley), Habilitation (2017, Universität Bonn) Affiliations: Instituto Superior Técnico (current), University of Birmingham (honorary), former positions at Bonn and Berkeley His work explores Fourier restriction theory , symmetry breaking phenomena , spherical packings , and sharp inequalities across geometric and analytic contexts. Recent publications address dimension-free estimates , stability of extremizers , and sign uncertainty principles , often leveraging collaborations with researchers like R. Mandel, G. Negro, and R. Quilodrán. Grants from EPSRC , DFG , NSF , AIM , and FCT have supported his work. He has been actively involved in international conferences and lecture series , including events in Rwanda, Germany, Brazil, and Japan. Teaching roles span complex analysis, Fourier analysis, and PDE courses at IST and Birmingham.

Salvatore Ivan Trapassoمشاهده پروفایل

استادیار

• Applied harmonic analysis
• Fourier analysis
• Machine learning
• +۵ مورد دیگر

Salvatore Ivan Trapasso is a Fixed-term Assistant Professor at the Department of Mathematical Sciences "GL Lagrange" (DISMA) , Polytechnic University of Turin , and a member of the SmartData@PoliTO - Big Data and Data Science Laboratory . His research focuses on Applied Harmonic Analysis , Fourier Analysis , Machine Learning , and Quantum Theory , with expertise in Mathematical Analysis (MATH-03/A) and Theoretical PDEs (PE1_11). Education : Implied PhD in Mathematics. Research Areas : Phase Space Analysis, Time-Frequency Methods, and Applications to Quantum Mechanics. His recent publications investigate phase space techniques for Feynman Path Integrals , Twisted Laplacian , Compressed Sensing , and Stability of Scattering Transforms . His work bridges Harmonic Analysis with Machine Learning and Quantum Dynamics . Notable scientific awards include the Axioms Young Investigator Award (2022) , Best Paper Award (ICGF 2020) , and the Quality Award 2019 from Polytechnic University of Turin. He serves on the Editorial Board of Advances in Operator Theory and as Associate Editor for University Texts in the Mathematical Sciences . Teaching roles include Lecturer for Mathematical Principles in the College of Architecture and Design , Collaborator for Mathematical Analysis I/II in Biomedical and Aerospace Engineering, and Contributor to advanced mathematical methods in Computer Science Engineering.

Ioannis Havoutisمشاهده پروفایل

دانشیار

• Robotics
• Machine Learning
• Dynamic Motion Planning
• +۵ مورد دیگر

Ioannis Havoutis is an Associate Professor in Engineering Science at the Oxford Robotics Institute , University of Oxford. His research integrates dynamic whole-body motion planning , control systems , and machine learning for robotics with arms and legs . He holds a PhD (2011) and MSc with distinction (2007) from the University of Edinburgh, focusing on machine learning for motion planning of articulated robots. University of Edinburgh: PhD in Robotics (2011), MSc in Machine Learning (2007) His work spans dynamic legged locomotion , learning from demonstration , and terrain-adaptive control , with applications in quadruped robots and teleoperation . Key contributions include symplectic meta-learning , skill switching criteria , and flow-based trajectory optimization . Recent publications focus on 2025 advancements in adaptive manipulation , generalist parkour policies , and diffusion models for locomotion. He has received awards such as the Frontiers in Robotics & AI Best Paper Award (2019) and CLAWAR 2015 Best Technical Paper Award . Teaching roles include B16 Operating Systems courses at Oxford and Advanced Robotics lectures at IIT. Contact: havoutis@robots.ox.ac.uk | ioannis@robots.ox.ac.uk | Address: Oxford Robotics Institute, 17 Parks Road, Oxford, OX1 3PJ, UK

Yen Doمشاهده پروفایل

دانشیار

• Analysis
• Probability
• Time-Frequency Analysis
• +۲ مورد دیگر

Yen Do is an Associate Professor in the Department of Mathematics at the University of Virginia . His research lies at the intersection of Analysis , Probability , and Partial Differential Equations , with a focus on problems involving random polynomials , time-frequency analysis , and nonlinear integrable equations . Research Interests include: Time-Frequency Analysis : Multilinear estimates for operators with modulation invariance, inspired by Carleson's work on Fourier series convergence. Random Polynomials and Functions : Studies on the distribution of real roots, expectation, variance, asymptotic normality, and law of large numbers for root counts. Nonlinear Integrable Equations : Long-time asymptotics for solutions of nonlinear PDEs, extending oscillatory integral techniques to nonlinear settings. Publications reflect a consistent exploration of harmonic analysis, probabilistic root distribution, and operator theory. His work spans topics like random orthogonal polynomials , Carleson embeddings , and variations in bilinear operators , often addressing fundamental questions in probability and analysis . Advising and Grants : Yen Do has advised Nhan Nguyen (2019-2023) Mark Lewers (2017-2020) His research is supported by multiple NSF grants ( DMS-1800855 , DMS-1521293 , DMS-1201456 ).

Máté Wierdlمشاهده پروفایل

استاد

• Ergodic Theory
• Almost Everywhere Convergence
• Number Theory
• +۳ مورد دیگر

Máté Wierdl is a Professor in the Department of Mathematical Sciences at the University of Memphis. He holds a Ph.D. from The Ohio State University (1989) and a B.S. from Eötvös Lóránd University (1985). His research focuses on ergodic theory, almost everywhere convergence, number theory, and the foundations of thermodynamics, particularly thermokinetics. He has held visiting positions at institutions like the University of Tours (France) and the University of Maryland. Research Interests : Wierdl explores ergodic theory’s applications to physical systems, addressing time-average convergence challenges. His work on thermokinetics redefines thermodynamics by modeling evaporation and condensation processes using differential equations. He collaborates internationally, emphasizing interdisciplinary connections with Fourier analysis, probability, and number theory. Publications : His recent work includes studies on ergodic averages’ fluctuations, stochastic processes, and sublacunary sequences. He has contributed to prestigious journals like the Transactions of AMS and Indiana J. of Math. Awards : Honors include the Erdos Professorship (2020–2022) and a 2008 membership at the Mathematical Sciences Research Institute. He was also a recipient of the Presidential Fellowship (1988). Teaching & Service : Teaches advanced courses in analysis, complex analysis, and ergodic theory. Served on University committees, including the Faculty Senate, and chairs the Undergraduate Committee. Actively mentors students and advises on research projects. Outreach : Engages in public education advocacy and has presented mathematics to high school students. Served as President of the Tennessee chapter of the American Association of University Professors.

Pascal Del'Hayeمشاهده پروفایل

پژوهشگر

• Microphotonics
• Optical Frequency Combs
• Microresonators
• +۷ مورد دیگر

Pascal Del'Haye is a Group Leader at the Max Planck Institute for the Science of Light (MPL) in Erlangen, Germany, where he heads the Microphotonics research group. His work focuses on advancing integrated photonics through innovative approaches to microresonator design, nonlinear optical phenomena, and frequency comb generation. With a strong publication record in high-impact journals, Del'Haye has established himself as a leading researcher in the field of microphotonics and nonlinear optics. Dr. Del'Haye's research spans several key areas in modern photonics: Microresonator-based optical frequency combs and soliton physics Nonlinear optical phenomena including symmetry breaking and Kerr effects Advanced materials for integrated photonics, particularly silicon nitride platforms Novel designs for photonic integrated circuits using inverse design techniques Hybrid photonic systems combining multiple materials and nonlinear effects His recent work (2023-2025) demonstrates a clear trend toward increasingly sophisticated integrated photonic systems that leverage multiple physical phenomena simultaneously. Del'Haye's group has pioneered approaches to control dispersion through segmented sidewall modulation, generate multiple comb states via cascaded Brillouin scattering, and combine different nonlinear effects in single devices through hybrid material platforms. This work has significant implications for telecommunications, sensing, quantum information processing, and precision metrology, with many publications highlighting the potential for CMOS-compatible implementations that could enable commercial applications and large-scale integration. As a Group Leader at one of the world's premier photonics research institutions, Del'Haye supervises multiple researchers and students, fostering the next generation of photonics scientists. His work is supported by significant research funding that enables state-of-the-art experimental capabilities for nanofabrication and optical characterization, with recent publications indicating strong collaborations across multiple institutions and research groups. The Microphotonics group operates advanced laboratories for photonic device fabrication and testing, with particular expertise in silicon nitride photonics, microresonator design, and frequency comb generation. The group collaborates extensively with other divisions at MPL and with international research teams to push the boundaries of integrated photonics technology, with recent work spanning from fundamental theoretical investigations of symmetry breaking to practical device implementations for optical switching and communication applications.

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.

Daniele Marinazzoمشاهده پروفایل

استاد

• Computational Neuroscience
• Complex Systems
• Neurophysics
• +۴ مورد دیگر

Daniele Marinazzo is a Full Professor in the Department of Data Analysis at Ghent University (Belgium), with a background in statistical physics and a focus on computational neuroscience and complex systems. He serves as Deputy Editor at PLOS Computational Biology , Co-Editor-in-Chief at Neurons, Behavior, Data Analysis, and Theory , and academic editor at Network Neuroscience and Imaging Neuroscience. His work spans theoretical physics, neuroscience methodology, and experimental neurophysiology. Academic Affiliation: Ghent University (Belgium) Editorial Roles: 3+ journals Research Initiatives: EBRAINS representative Research Interests combine computational neuroscience, complexity science, and network analysis. He investigates higher-order interactions in brain networks, synergistic information processing, and methodological advancements in neuroimaging. Recent work includes MEG/EEG analysis, gene expression modeling, and developing open-source tools like SPM-Python. Scientific Contributions include 15+ recent publications on topics ranging from individual brain fingerprinting to multisensory integration models. His work appears in venues like Nature Communications , Physics of Life Reviews , and Entropy , with methodological innovations in hidden factor localization and network synchronization analysis. Current projects include PhD/postdoc recruitment for fast-sampled fMRI analysis and organizing the Erice workshop Higher-Order Interactions: Mechanisms, Behaviors, and Networks (August 2025).

Xavier Claeysمشاهده پروفایل

استاد

• Wave Propagation
• Mathematical Modeling
• Numerical Analysis
• +۵ مورد دیگر

Xavier Claeys is a Professor at ENSTA Paris, affiliated with the Applied Mathematics Unit (UMA) and the Wave Propagation, Mathematical Study and Simulation (POEMS) research team. His work focuses on the mathematical modeling and numerical analysis of wave propagation phenomena with applications in electromagnetics and acoustics. He maintains an active research program with numerous publications spanning from 2007 to the present, demonstrating sustained scholarly contributions to his field. Dr. Claeys earned his PhD from Université Versailles Saint-Quentin-en-Yvelines in 2008 with a thesis on 'Asymptotics and numerical analysis for wave diffraction by thin wires.' He completed his Habilitation from Université Pierre-et-Marie Curie in 2016 with research on 'Boundary integral equations of time harmonic wave scattering at complex structures.' His academic trajectory shows a consistent focus on developing mathematical frameworks for wave propagation problems. His primary research interests center on the modeling and numerical analysis of linear wave propagation phenomena, particularly in the context of frequency domain electromagnetics and acoustics. His specific technical interests include domain decomposition methods, boundary element methods, scientific computing, multi-scale problems, and singularities in elliptic problems. Dr. Claeys has developed specialized software tools including bemtool (a boundary element library) and ddmtool (a domain decomposition library) to support his research, demonstrating his commitment to translating theoretical advances into practical computational tools. Analysis of his publication record reveals a consistent evolution toward increasingly sophisticated domain decomposition approaches, particularly optimized Schwarz methods and multi-trace boundary integral formulations. His work demonstrates a strong theoretical foundation combined with practical implementation considerations, with applications spanning electromagnetic scattering, acoustic wave propagation, and metamaterial analysis. Recent publications show increasing focus on addressing computational challenges related to complex geometries and physical boundaries. Dr. Claeys has led significant research projects including 'NonlocalDD' funded by the French National Research Agency (ANR), which investigated boundary integral equations in conjunction with domain decomposition. He was previously involved in the ANR-funded 'METAMATH' project focused on the modeling and numerical analysis of metamaterials. His research contributes to ENSTA Paris's broader research focus on cutting-edge areas with applications in sustainable energy, transportation, and defense. His work aligns particularly with the 'Waves and Vibrations' research axis at ENSTA Paris, which encompasses activities related to wave propagation phenomena with applications including seismic effects on infrastructure, non-destructive testing, and acoustic management in transportation and energy sectors. Dr. Claeys' theoretical contributions provide foundational support for these applied research directions through advanced mathematical modeling and numerical methods development.

• Harmonic Analysis
• Incidence Geometry
• Geometric Measure Theory
• +۳ مورد دیگر

Marina Iliopoulou is a Professor of Mathematics at the Department of Mathematics, National and Kapodistrian University of Athens, Greece. Her research focuses on harmonic analysis, incidence geometry, geometric measure theory, and additive combinatorics. She has made significant contributions to understanding oscillatory integral operators, Kakeya-type problems, and inequalities in harmonic and functional analysis. Education: PhD in Mathematics from the University of Edinburgh (2013), thesis titled Discrete analogues of Kakeya problems . Research Highlights: Developed sharp estimates for oscillatory integral operators using polynomial partitioning, earning a Frontiers of Science Award (2018-22). Advanced studies on incidence geometry, including joints problems and multijoints over arbitrary fields. Contributed to Mizohata-Takeuchi-type inequalities and Riesz-Sobolev inequalities on Abelian groups. Recognition: Recipient of the Frontiers of Science Award for the paper Sharp estimates for oscillatory integral operators via polynomial partitioning . Advising & Grants: No listed advisees or grant details provided. Labs/Teams: No specific laboratories or collaborative teams explicitly mentioned in the provided information.

• Numerical Analysis
• Stochastic Differential Equations
• Runge-Kutta Methods
• +۴ مورد دیگر

Anne Kværnø is a Professor in the Department of Mathematical Sciences at NTNU. Her research focuses on numerical analysis, particularly stochastic differential equations, Runge-Kutta methods, and geometric integration. She has made significant contributions to the development of high-order numerical schemes for stochastic systems, including exponential integrators and Lawson schemes. Her work emphasizes preserving invariants and stability properties in stochastic and deterministic systems. Key research areas include multirate methods for coupled systems, differential-algebraic equations, and applications in energy storage modeling. She has collaborated extensively on projects involving aquifer thermal energy storage (ATES) systems and groundwater flow analysis. Her publications span prestigious journals like BIT Numerical Mathematics, SIAM Journal on Numerical Analysis, and Journal of Computational Physics. She has presented at major conferences such as ICIAM, SciCADE, and ENUMATH, focusing on stochastic numerical methods and their applications. Her research bridges theoretical developments with practical computational challenges in engineering and environmental modeling.

• Chemical Engineering
• Process Intensification
• Reactor Design
• +۶ مورد دیگر

Professor Adam Harvey is a distinguished academic in the Department of Chemical Engineering at Newcastle University's School of Engineering. With a prolific publication record spanning over two decades and extending to 2026, his research has significantly advanced the fields of chemical engineering, process intensification, and sustainable energy technologies. His work demonstrates exceptional innovation in reactor design and optimization for diverse chemical processes. Professor Harvey's research expertise centers on process intensification, with pioneering contributions to oscillatory baffled reactors (OBRs) and their applications across multiple domains. His work has revolutionized the use of OBRs for biodiesel production from various feedstocks, microalgae cultivation systems, and numerous chemical transformations. He has also made substantial contributions to non-thermal plasma technologies for environmental applications, particularly in pollutant removal and biomass conversion. His research effectively bridges fundamental chemical engineering principles with practical industrial applications, emphasizing sustainability and efficiency. Analysis of Professor Harvey's recent publications reveals a strategic evolution toward sustainable chemical processes and bio-based product development. His work increasingly focuses on CO 2 utilization pathways, waste biomass conversion technologies, and green chemical processes that minimize environmental impact. The integration of advanced reactor design with renewable feedstocks represents a defining theme in his current research portfolio, demonstrating his commitment to developing environmentally sustainable solutions for the chemical industry. Throughout his distinguished career, Professor Harvey has mentored numerous researchers and established extensive collaborations with both academic institutions and industry partners. His research group operates state-of-the-art facilities for reactor design, process optimization, and biofuel production. The group maintains strong industry connections, facilitating the translation of fundamental research into practical applications that address real-world challenges in energy and environmental sustainability.

• Probability Theory
• Stochastic Processes
• Mathematical Physics
• +۴ مورد دیگر

Sonia Mazzucchi is a Full Professor in the Department of Mathematics at the University of Trento, specializing in probability theory, stochastic processes, and mathematical physics. Her research focuses on Feynman path integrals, quantum mechanics, and operator theory, with recent extensions into quantum information and photonics applications. She teaches core courses including Probability Calculus II, Mathematics and Statistics II, Quantum Information, and Stochastic Processes. Her research interests bridge abstract mathematical theory with practical quantum technologies. She investigates stochastic processes for modeling quantum systems, develops rigorous mathematical frameworks for path integrals on Lie groups, and applies probability theory to quantum random number generation and LiDAR systems. Her work combines functional analysis, measure theory, and differential equations to solve problems in quantum mechanics and information science. Recent publications (2022-2025) reveal a strong interdisciplinary trajectory merging mathematical physics with quantum engineering. Key trends include quantum random number generators using single-photon entanglement, SPAD-based LiDAR innovations for photon flux measurement, and advanced treatments of path integrals on Riemannian manifolds. Her work demonstrates consistent progression from foundational mathematical theory to quantum technology applications. No scientific awards are documented in the available information. Details regarding graduate student supervision and research grants are not specified in the source materials. Her academic activities center on teaching core mathematics courses and publishing in high-impact journals spanning mathematical physics and quantum information science.

• Neuromorphic Engineering
• Spiking Neural Networks
• CMOS Circuit Design
• +۳ مورد دیگر

Hugh Greatorex serves as a Researcher at the University of Groningen within the Faculty of Science and Engineering, affiliated with the Bio-inspired Circuits & Systems research group. His work centers on neuromorphic hardware design, specializing in spiking neural networks and event-based processing systems that prioritize energy efficiency and real-world applicability in robotics and embedded AI. His research spans critical areas in neuromorphic engineering: Neuromorphic Engineering Spiking Neural Networks CMOS Circuit Design Memristive Computing Event-based Vision and Audio Processing Symbolic Computation in Neural Hardware Greatorex integrates circuit design with neural algorithms to solve power efficiency challenges, frequently exploring beyond-CMOS technologies like memristors and multi-timescale neural dynamics for practical implementations. Analysis of his 14 recent publications (2022-2025) reveals a cohesive trajectory toward hybrid neuromorphic processors combining CMOS with emerging devices. Key contributions include the TEXEL and Fused-MemBrain architectures for beyond-CMOS integration, alongside advancements in event-based sensory processing and symbolic operations within spiking hardware. This work consistently bridges neural computation with symbolic AI paradigms while emphasizing scalability and robustness. No scientific awards were documented in available sources. Information regarding student advisement and research grants was not provided in the source materials. As a core member of Groningen's Bio-inspired Circuits & Systems group, Greatorex contributes to internationally collaborative projects focused on biologically inspired electronic systems for intelligent processing, with applications spanning edge AI and neural computation modeling.

Heather Readمشاهده پروفایل

استاد

• Sensory Neuroscience
• Sound Perception
• Auditory Processing
• +۳ مورد دیگر

Heather Read is a Professor at the University of Connecticut's Department of Psychological Sciences, where she leads research in sensory neuroscience and auditory processing. Her work investigates how mammals perceive sound frequency, shape, and rhythm, with implications for understanding cortical developmental disorders like dyslexia and autism. She directs the Read Lab, focusing on neural mechanisms from single neurons to behavior, aiming to develop innovative diagnostic tools and prosthetic hearing devices. Research spans neurobiology of sound perception, including: Neural circuit anatomy underlying auditory processing Perceptual deficits in developmental disorders Computational models of natural sound encoding Novel neurotechnologies for auditory rehabilitation Her publications (2018-2024) demonstrate evolving focus: earlier work established thalamocortical auditory pathways and neural coding principles, while recent research emphasizes closed-loop neuromodulation systems, wearable EEG technology, and translational applications for hearing disorders. Studies consistently integrate neurophysiological recordings, computational modeling, and behavioral analysis across species. Awards and honors include: Kavli Frontiers Fellow (National Academy of Science) Schmitt Dissertation Award Marine Biological Laboratories Undergraduate Fellowship Graduate Merit Fellowship She teaches undergraduate courses in Sensation/Perception (PSYC 3501) and Sensory Neuroscience Lab (PSYC 3253). Contact: heather.read@uconn.edu | Office: Bousfield 114, Storrs Campus.