Find Academic Supervisors

• Differential Geometry
• General Relativity
• Geodesic Theory
• +4 more

Antonio Masiello is a Full Professor in the Department of Mechanics, Mathematics & Management at Politecnico di Bari, Italy. His research focuses on differential geometry, general relativity, and variational methods in geometric contexts, particularly analyzing geodesics and causal structures in Lorentzian and Finsler manifolds. Current affiliation: Politecnico di Bari, Department of Mechanics, Mathematics & Management Research themes: Geodesic theory, Morse theory, Finsler and Lorentzian geometry, applications to relativity Contact: antonio.masiello@poliba.it His work explores the interplay between geometric structures and physical phenomena, including studies on lightlike and timelike geodesics, convexity in manifolds, and the mathematical foundations of gravitational lensing. Publications highlight rigorous analytical approaches to problems in causal geodesics and variational principles. Recent publications demonstrate significant contributions to understanding geodesic connectedness in Randers-Kropina metrics, homotopy properties of differential inclusions, and the application of Morse theory to stationary spacetimes. These works often bridge geometric analysis with control theory and topological methods. Scientific awards and honors are not explicitly mentioned in available sources. He has not been identified as part-time, retired, or former staff, indicating ongoing active research and teaching commitments.

Chris J BuddView profile

Professor

• Nonlinear Mathematics
• Industrial Mathematics
• Numerical Analysis
• +7 more

Professor Chris J Budd OBE is a distinguished Professor of Applied Mathematics at the University of Bath's Department of Mathematical Sciences, where he serves as Director of Knowledge Exchange for the Bath Institute for Mathematical Innovation (IMI). He is also Professor of Mathematics at the Royal Institution of Great Britain and a former Gresham Professor of Geometry. His leadership extends to directing the Centre for Nonlinear Mechanics and serving as Super Champion of the KE Hub. His educational background includes a gap year with Marconi that profoundly shaped his career, followed by undergraduate studies at Cambridge and a DPhil at Oxford. This industry experience during his formative years established his lifelong commitment to industrial mathematics and knowledge exchange. Budd's research focuses on nonlinear mathematical problems with industrial applications, particularly adaptive moving mesh methods for meteorology and climate modeling, data assimilation, non-smooth dynamical systems, and the mathematics of machine learning. He approaches linear problems as 'for cissies,' preferring the challenges of nonlinear systems that better represent real-world phenomena. His work bridges theoretical mathematics with practical applications across meteorology, environmental science, and engineering. His recent publications reveal a strong trend toward integrating machine learning with traditional numerical methods, particularly in climate modeling and solving partial differential equations. This includes Fourier Neural Operators, adaptive mesh methods enhanced by graph neural networks, and mathematical frameworks for understanding climate tipping points through non-smooth dynamics. OBE for services to mathematics National Teaching Fellowship (NTF) Knowledge Transfer Award for work with the Met Office Fellow of the Institute of Mathematics and its Applications (FIMA) Chartered Mathematician (C Math) British Science Association award for best science festival (2009) As principal investigator of the £3.5M EPSRC Programme Grant 'Maths4DL' on the Mathematics of Deep Learning, Budd leads a major collaborative effort between Bath, Cambridge, and UCL. He actively supervises numerous PhD students across diverse projects including climate modeling, machine learning applications, and industrial mathematics problems. His commitment to knowledge exchange is exemplified through V-KEMS (Virtual Forum for Knowledge Exchange in the Mathematical Sciences), which he co-founded to address challenges like the COVID-19 pandemic through mathematical approaches. Budd directs the Centre for Nonlinear Mechanics at Bath, fostering interdisciplinary research through mathematical modeling of complex systems. He also leads the Bath Institute for Mathematical Innovation's knowledge exchange activities, connecting academic mathematics with industrial and societal challenges. His work with V-KEMS has proven particularly effective during the pandemic, mobilizing teams of mathematicians to address urgent real-world problems.

Edmund SpencerView profile

Associate Professor

• Space Plasma Physics
• Space Weather
• Radio Frequency Instrumentation
• +3 more

Dr. Edmund Spencer is an Associate Professor in the Department of Electrical and Computer Engineering at the University of South Alabama , with research focused on space plasma physics and space weather . He designs advanced instruments for space science, develops theoretical frameworks for plasma characterization, and applies stochastic optimization algorithms to complex systems. Ph.D. Electrical and Computer Engineering, University of Texas at Austin M.S. Electrical and Computer Engineering, University of Texas at Austin B.S. Electrical and Electronics Engineering, University of Leicester, UK His work bridges space instrumentation with nonlinear magnetospheric dynamics , particularly in geomagnetic substorms and solar wind-earth magnetosphere interactions . Current projects include onboard space weather modules for satellites and advanced antenna systems for CubeSats . Recent research trends from his 15 most recent publications (2019-2025) include: Development of time-domain impedance probes for ionospheric electron density measurements Applications of machine learning in substorm prediction Hybrid physics-black-box modeling for Dst index forecasting Advanced antenna designs for small satellites 3D Particle-in-Cell simulations for RF instruments Collisional effects in plasma probe measurements Scientific contributions include: NSF CAREER Award (2013) for RF impedance probe development Key role in NASA's USIP CubeSat missions (e.g., JAGSAT I) Leveraging WINDMI model for substorm dynamics analysis He teaches graduate and undergraduate courses in electromagnetics and stochastic processes , contributing to the department's space science integration in engineering education.

Amar Nath Roy ChowdhuryView profile

Assistant Professor

• Structural Engineering
• Stability of Plate and Shell Structures
• Mechanics and Design of Thin-walled Structures
• +3 more

Amar Nath Roy Chowdhury is currently serving as an Assistant Professor in the Department of Civil Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur) since December 2019. He previously held an Assistant Professor position at IIT Ropar from May 2017 to December 2019, and was a Post-doctoral Research Fellow at the National University of Singapore from January 2015 to December 2016. His academic journey includes a PhD from the National University of Singapore (2010-2014), an M.Tech from IIT Bombay (2006-2008), and a B.E. from Jadavpur University (2002-2006). Doctor of Philosophy (2010-2014), Department of Civil and Environmental Engineering, National University of Singapore, Singapore Master of Technology (2006-2008), Department of Civil and Environmental Engineering, Indian Institute of Technology Bombay, Mumbai, India Bachelor of Engineering (2002-2006), Department of Civil Engineering, Jadavpur University, Kolkata, India Dr. Roy Chowdhury specializes in Structural Engineering with research interests focused on the Stability of Plate and Shell Structures, Mechanics and Design of Thin-walled Structures, and Molecular Dynamics Simulation of Materials. His work bridges traditional structural engineering with cutting-edge nanoscale mechanics, particularly in the analysis of carbon nanotubes and other advanced materials. His research employs both theoretical continuum mechanics approaches and molecular dynamics simulations to understand structural behavior at different scales. Analysis of his publication record reveals a strong focus on structural mechanics across multiple scales - from macroscopic plate and shell structures to nanoscale carbon nanotubes. His work demonstrates expertise in vibration analysis, buckling phenomena, and stability considerations across these scales. A significant portion of his research involves developing continuum shell models to analyze carbon nanotube behavior, bridging the gap between molecular dynamics simulations and traditional structural engineering principles. Dr. Roy Chowdhury teaches courses in Stability of Structures, Steel Design, Structural Analysis, and Solid Mechanics. His teaching reflects his research expertise in structural mechanics and stability analysis. While specific information about research grants and advising is not explicitly detailed in the available information, his publication record suggests active research collaboration with international scholars, particularly with researchers at the National University of Singapore.

Matthias BaitschView profile

Professor

• Construction Informatics
• Numerical Methods
• Structural Optimization
• +3 more

Matthias Baitsch serves as Professor of Construction Informatics and Numerical Methods in the Department of Civil and Environmental Engineering at Bochum University of Applied Sciences, where he concurrently heads the BIM Institute. His academic trajectory includes research assistant and senior engineer roles at Ruhr-University Bochum (2000-2009), academic coordination at the Vietnamese-German University (2009-2012), and an acting professorship at the University of Kassel (2012-2014). His educational foundation comprises: Civil Engineering studies at the University of Dortmund (1991-1997) under the interdisciplinary "Dortmund Model" Doctorate from Ruhr-University Bochum (2003) on geometric imperfection-based optimization of compressive beam structures Professor Baitsch's research integrates computational mechanics with civil engineering practice, specializing in construction informatics, numerical optimization, and high-order finite element methods. His work pioneers distributed optimization frameworks, structural health monitoring for wind energy infrastructure, and BIM-based construction informatics. Key methodological contributions include hp-FEM implementations, parallel optimization algorithms, and mobile structural analysis tools. Analysis of his recent publications reveals three dominant research trajectories: (1) Advanced numerical methods for structural optimization under uncertainty, (2) Health monitoring-driven lifetime prediction for wind turbine systems, and (3) Computational modeling of tunnel environments using viscoacoustic inversion techniques. These threads demonstrate consistent focus on robust numerical implementations and real-world civil engineering applications. As Head of the BIM Institute, he leads institutional efforts in digital construction technologies, fostering industry-academia collaboration on building information modeling standards and applications. His teaching portfolio spans foundational mathematics, numerical methods, and computer science for civil engineering students, emphasizing practical computational skills.

Furat Al-ObaidyView profile

Lecturer

• Machine Learning
• Intelligent Systems
• VLSI Circuits
• +7 more

Furat Al-Obaidy is a Lecturer in the Department of Electrical and Computer Engineering at the University of Michigan-Dearborn's College of Engineering and Computer Science. His expertise spans machine learning, intelligent systems, VLSI circuits, multi-core systems, FPGA architecture, and deep learning applications. PhD in Electrical & Computer Engineering from Ryerson University (2021) MSc in Electrical & Computer Engineering from Ryerson University (2016) MSc in Control & Instrumentation Engineering from University of Technology, Baghdad (1999) BSc in Control & Systems Engineering from University of Technology, Baghdad (1996) His research focuses on power-aware computing systems, thermal imaging for IC testing, hybrid cache architectures, and AI-driven network optimization. He has published extensively on topics including GPGPU power management, 3D NoC routing, and wireless sensor networks. His recent publications highlight applications of neural networks in cache optimization, FPGA architecture, and thermal imaging for hardware diagnostics. Earlier work includes control system simulations for wind turbines and power factor analysis in electrical circuits. Ryerson Graduate Development Award (2021) Ontario Graduate Scholarship Award (OGS) (2020) Ryerson Graduate Fellowship (2018) Graduate Research Excellence Award (2017) Queen Elizabeth II Graduate Scholarship in Science and Technology (2017)

• Functional Analysis
• Operator Theory
• Holomorphic Functions
• +6 more

Maria Pilar Rueda Segado is a Professor in the Department of Mathematical Analysis at the Faculty of Mathematics, University of Valencia. She is a leading researcher in functional analysis and operator theory, with a focus on holomorphic functions, polynomials, and multilinear operators in infinite-dimensional spaces. Her work is closely associated with the ESALDI research group. Her research interests lie primarily in Functional Analysis, particularly in the areas of: Weighted spaces of holomorphic functions Summing and dominated multilinear operators and polynomials Isometries in function spaces Factorization of operators and polynomials Spaceability and norm-attaining mappings Tensor norms and operator ideals Her extensive publication record, with over 90 works since 1996, reflects a deep and sustained engagement with core problems in nonlinear functional analysis. Her publications demonstrate a consistent focus on abstract operator theory, functional ideals, and the geometry of Banach spaces, often in collaboration with prominent mathematicians such as Daniel Pellegrino, Enrique Sánchez-Pérez, and Christopher Boyd. She earned her PhD from the University of Valencia in 1997 with a thesis on infinite-dimensional holomorphy under the supervision of Dr. Pablo Galindo Pastor. She has not received any explicitly mentioned scientific awards in the provided text. She has supervised PhD students, though their names are not listed in the provided content. Her research has been supported through institutional and collaborative academic grants, typical of senior faculty in mathematical sciences. She actively collaborates with an international network of researchers in functional analysis. She is a key member of the ESALDI (Spaces and Algebras of differentiable Functions) research group at the University of Valencia, which focuses on advanced topics in functional analysis and differentiable structures in infinite dimensions.

Yoav ZemelView profile

Lecturer

• Geometrical statistics
• Point processes
• Shape theory
• +3 more

Yoav Zemel is a Lecturer at the École polytechnique fédérale de Lausanne (EPFL) , affiliated with the School of Basic Sciences and Department of Mathematics . He specializes in statistical aspects of optimal transport and related geometric methods. B.Sc. Mathematics & Economics, Hebrew University of Jerusalem (summa cum laude, 2010) M.Sc. Applied Mathematics, EPFL (2012) PhD Mathematical Statistics, EPFL (2017), advised by Victor M. Panaretos His research focuses on geometrical statistics , point processes , shape theory , and optimal transportation . Recent work explores covariance operators, Gaussian processes, and stochastic algorithms in Wasserstein spaces. Publications bridge theoretical advancements with applications in ecology, genetics, and machine learning. Scientific awards include the Robert May Prize , Swiss government scholarship , and multiple Hebrew University honors. He has taught courses on probability, statistical machine learning, and optimal transport at EPFL, Göttingen, and Cambridge.

• Microelectronics
• MEMS Resonators
• Radio Frequency (RF) Devices
• +4 more

Dana Weinstein is a Professor in the Department of Electrical and Computer Engineering at Purdue University, West Lafayette campus. Her research focuses on cutting-edge MEMS resonators, RF device integration, and acoustoelectronic systems. Academic Rank: Professor Department: Electrical and Computer Engineering University: Purdue University Email: danaw@purdue.edu Research Interests: Microelectronics and MEMS Resonators Radio Frequency (RF) Devices and 2D Materials Silicon Photonics and Ferroelectric Transducers Acoustoelectronics and GaN/SiC Heterostructures Integrated Nonreciprocal RF MEMS Devices Scientific Awards: NSF CAREER Award (2017) NSF CAREER Award (2012) Editorial Leadership in IEEE Nanotechnology Express (2015) Key Article Trends: Her recent publications explore advanced MEMS resonators, high-frequency RF devices, acoustoelectric interactions, and integration of 2D materials into CMOS-compatible platforms. Topics include Sezawa wave SAW devices, GaN/SiC heterostructures, BEOL-compatible transistors, and ferroelectric-based transducers.

Christopher HojnyView profile

Assistant Professor

• Mixed-Integer Programming
• Symmetry Handling in Optimization
• Combinatorial Optimization
• +3 more

Christopher Hojny is an Assistant Professor at the Department of Mathematics and Computer Science at Eindhoven University of Technology , specializing in combinatorial optimization. He contributes to the EAISI Foundational group and co-develops the academic solver SCIP . His research focuses on symmetry handling in mixed-integer programming , theoretical properties of integer programs, and algorithm development for combinatorial optimization. Recent work explores applications in graph neural network verification , clustering problems, and network coding through mixed-integer programming frameworks. Key publication trends show expertise in Symmetry detection and mitigation techniques Relaxation complexity theory Applications to machine learning robustness Decision diagram-based scheduling Scientific contributions include Proof systems for symmetry certification Topological bounds tightening in GNNs Stable set problem symmetry handling SCIP solver extensions He supervises PhD students Cédric Roy (NWO project on Local Symmetries) and Sten Wessel (co-supervised with Frits Spieksma), while Jasper van Doornmalen (2019-2023) investigated symmetry propagation algorithms.

Dimitrios BetsakosView profile

Professor

• Complex Analysis
• Dynamic Theory
• Geometric Function Theory
• +2 more

Dimitrios Betsakos is a Professor at the Department of Mathematics , Aristotle University of Thessaloniki , Greece. His academic journey began with a degree in Mathematics (1990) from Aristotle University, followed by a PhD in Mathematics (1996) from Washington University in St. Louis. He has held various academic positions, including Postdoctoral Fellow at the University of Helsinki (1998-1999), Visiting Assistant Professor roles at Aristotle University and the University of Crete (1999-2002), and progressively advanced to Assistant, Associate, and Full Professor at Aristotle University (2002-). His research focuses on Complex Analysis , Dynamic Theory , and Geometric Function Theory , exploring topics like harmonic measure, symmetrization, and hyperbolic geometry. His work connects analysis with probability, particularly through Brownian motion and Markov processes. The 15 most recent publications (2004-2021) span geometric versions of Schwarz’s lemma, harmonic measure, hyperbolic metrics, and condenser capacity. These studies often involve collaborations and address extremal problems, inequalities, and applications of complex analysis to differential equations. He has supervised numerous doctoral and postgraduate students, including Kelgiannis Georgios , Tsantaris Athanasios , and Sachpazis Stylianos , guiding research on topics like holomorphic functions, geometric transformations, and hyperbolic metrics. His teaching includes courses on Real Analysis and Complex Analysis. Current research projects include geometric versions of Schwarz’s lemma under hyperbolic metrics and capacity estimation problems, reflecting his long-term engagement with conformal invariants and analytic number theory.

• Probability Theory
• Interacting Particle Systems
• Hydrodynamic Limits
• +7 more

Makiko Sasada is a Professor at the Graduate School of Mathematical Sciences, The University of Tokyo. Her research focuses on probability theory, interacting particle systems, and classical integrable systems, with an emphasis on hydrodynamic limits, spectral gaps, and non-gradient models. She has made significant contributions to understanding energy diffusion in stochastic systems and integrable cellular automata like the box-ball system. 2010: MSJ Takebe Katahiro Prize for Encouragement of Young Researchers 2011: Second JSPS Ikushi Prize 2011: University of Tokyo President's Prize Her recent work explores scaling limits in the box-ball system, thermal conductivity in stochastic models, and topological structures in large-scale systems. She actively participates in international conferences, serves as an associate editor for leading journals, and organizes educational initiatives like the FoPM program, which trains students to apply basic science to societal challenges through mathematical and physical innovation. Selected publications include: The incompressible Navier–Stokes limit from the discrete-velocity BGK Boltzmann equation (2025) Characterization of Gradient Condition for Asymmetric Partial Exclusion Processes (2025) Topological structures of large-scale interacting systems (2024)

• Applied Analysis
• Numerical Analysis
• Data Science
• +6 more

Leon Bungert is a Professor of Mathematics of Machine Learning at the University of Würzburg, working in applied analysis and numerics with a particular focus on data science and machine learning. His research investigates PDEs and variational models on graphs, adversarial robustness of machine learning, variational regularization, and nonlinear optimization. Dr. Bungert serves as a guest editor for the European Journal of Applied Mathematics, an associate editor for Advances in Continuous and Discrete Models: Theory and Applications, and is a member of the program committee at SSVM 2025. He is also an ELLIS member and actively organizes conferences and workshops, including "MIA'25" at IHP in Paris (January 13-15, 2025), "Synergies of Machine Learning and Numerics" in Osaka (March 11-13, 2025), and "Mathematical Analysis of Adversarial Machine Learning" in Oaxaca (August 17-22, 2025). Research Interests Dr. Bungert's primary research areas include: PDEs on graphs Adversarial robustness in machine learning Inverse problems Optimization Variational problems in L-infinity Nonlinear eigenvalue problems Image reconstruction with structural priors His work bridges theoretical mathematics with practical applications in machine learning, particularly focusing on the mathematical foundations of deep learning and developing robust algorithms that can withstand adversarial attacks. He has made significant contributions to understanding the connections between partial differential equations and machine learning algorithms. Research Trends Analysis of Dr. Bungert's recent publications reveals a strong focus on the intersection of machine learning and mathematical analysis. A key theme is the application of variational methods and partial differential equations to machine learning problems, particularly in understanding and improving the robustness of neural networks against adversarial examples. His work on Lipschitz learning on graphs has established important theoretical foundations for graph-based semi-supervised learning. Additionally, his research on the infinity Laplacian and p-Laplacian equations provides deep insights into the mathematical structure of machine learning algorithms. The development of Bregman learning frameworks for sparse neural networks represents a significant contribution to efficient deep learning model training. Professional Activities Dr. Bungert is actively involved in the academic community through editorial roles and conference organization. His current professional activities include: Guest editor for the European Journal of Applied Mathematics Associate editor for Advances in Continuous and Discrete Models: Theory and Applications Member of the program committee at SSVM 2025 ELLIS member Co-organizer of multiple international conferences and workshops Technical Contributions Dr. Bungert has developed several open-source software packages that implement his theoretical contributions, including: Code for convergence rates of Lipschitz learning on graphs A Bregman training framework for sparse neural networks CLIP: Cheap Lipschitz Training of Neural Networks Nonlinear Power Method for Proximal Operators and Neural Networks Robust Image Reconstruction with Misaligned Structural Information These implementations are primarily in Python and MATLAB, demonstrating his commitment to making theoretical advances accessible for practical applications.

Alexandre BaronView profile

Assistant Professor

• Metamaterials
• Nanophotonics
• Nonlinear optics
• +5 more

Alexandre Baron serves as an Assistant Professor at the University of Bordeaux and holds a concurrent position as Adjunct Assistant Professor at Duke University. Based at the Paul Pascal Research Center (CNRS) in Pessac, France, his work bridges fundamental optical physics with materials science applications in nanophotonics and metamaterials. His academic training includes: PhD in Nonlinear Optics from Institute of Optics Graduate School/University Paris-Sud 11 (2007-2011) Master Degree in Physics - Optics and Photonics from Paris-Sud 11 University (2006-2007) Engineering Degree in Optics from Institute of Optics Graduate School (2004-2007) Baron's research program focuses on cutting-edge optical phenomena, particularly in metamaterials including self-assembled structures, optical magnetism, hyperbolic metamaterials, and metasurfaces. His nanophotonics work investigates plasmonic, dielectric and composite nanoparticles, while his nonlinear optics research examines field enhancement effects and nonlinear plasmonics. His photonic crystals studies address slow light phenomena, nonlinear effects, and disorder impacts. Analysis of his publication record reveals consistent contributions to fundamental understanding of light-matter interactions at the nanoscale, with increasing emphasis on engineered nanostructures and their optical properties. His recent work demonstrates sophisticated control over multipolar responses and tailored scattering in metamaterial systems. As a member of the Paul Pascal Research Center - a joint CNRS and University of Bordeaux unit focused on functional materials and soft matter - Baron contributes to an interdisciplinary research environment that brings together chemists, biochemists, physical chemists and physicists across six research teams.

Stephan ReuterView profile

Professor

• Plasma Physics
• Plasma Medicine
• Ultrafast Laser Spectroscopy
• +4 more

Stephan Reuter is a Full Professor in the Department of Engineering Physics at Polytechnique Montréal , holding the TransMedTech Research Chair in Plasma Medicine . His work bridges plasma physics, biomedicine, and environmental technology through advanced diagnostics and interdisciplinary applications. Education: Dipl. Phys.-Ing. (Master in Engineering Physics), Dipl. Phys. (M.Sc. in Physics), Dr. rer. nat. (PhD) Affiliations: TransMedTech Institute, Institute of Biomedical Engineering, Alexander von Humboldt Foundation Alumnus Research Interests: Non-thermal plasma physics, plasma medicine, ultrafast laser diagnostics, plasma-liquid interactions, environmental remediation His 15 most recent publications (2022-2025) focus on cold atmospheric plasma jets for cancer therapy, agricultural sustainability, and microfluidic integration. These works span Plasma Medicine , Environmental Technology , and Advanced Diagnostics , with specific subfields like 3D tumor modeling, reactive oxygen species analysis, and precision plasma dosimetry. Scientific Leadership : Feodor Lynen Research Fellow (Princeton University, 2017-2018) Co-founder of Leibniz Institute's Plasma Medicine Group Editorial contributor to Plasma Sources Science and Technology Research Impact : Over 98 peer-reviewed journal articles Keynote speaker at ISPC26 (2025) Major grants: $3.4M for greenhouse plasma technology (2024), $1M NFRF Exploration Grant (2021) Labs & Collaborations : Polytechnique Montréal Plasma Biophysics Lab TransMedTech Institute International collaborations: Leibniz Institute (Germany), Queens University (UK), Lublin University (Poland)