جست‌وجوی استاد و پژوهشگر

• Coding Theory
• Discrete Geometry
• Finite Geometry
• +۵ مورد دیگر

Sascha Kurz is an Associate Professor at the Mathematical Institute of the Faculty of Mathematics, Physics and Computer Science at the University of Bayreuth, Germany. His research focuses on discrete structures, coding theory, voting systems, and combinatorial optimization. Professor Kurz's primary research interests span several interconnected fields in discrete mathematics and its applications: Coding Theory : With a focus on divisible codes, subspace codes, and constant dimension codes, his work explores the theoretical foundations and practical applications of error-correcting codes. Discrete Geometry : His research in finite geometry, particularly on arcs in projective spaces and vector space partitions, contributes to both theoretical understanding and coding applications. Game Theory and Voting Systems : He investigates power indices, weighted voting games, and their applications to political science and decision-making processes. Combinatorial Optimization : His work includes network coding, subspace packings, and algorithmic approaches to classification problems in coding theory. Analysis of Professor Kurz's recent publications reveals a strong focus on the intersection of coding theory and discrete geometry. His work consistently addresses fundamental questions about code parameters, classifications, and constructions, with particular attention to divisible codes and their properties. There's a clear progression from theoretical foundations to computational methods, as evidenced by his increasing use of computer-assisted classification techniques. His research demonstrates significant contributions to understanding the structure of linear codes, subspace codes, and their geometric interpretations. Professor Kurz has made notable contributions to both theoretical and applied aspects of his fields, collaborating with researchers across Europe and beyond. His work bridges pure mathematics with practical applications in information theory and network communication.

Steffen Winterمشاهده پروفایل

مدرس

• Fractal Geometry
• Geometric Measure Theory
• Stochastic Geometry
• +۱ مورد دیگر

Steffen Winter is a Lecturer (PD Dr.) at the Institute of Stochastics, Karlsruhe Institute of Technology (KIT). His research specializes in Fractal Geometry, Geometric Measure Theory, Stochastic Geometry, and Dynamical Systems. He leads the DFG-funded project Scaling of curvature measures and the modified Weyl-Berry conjecture and serves as Principal Investigator for project 12 ( Morphometric Roughness of Nanostructured Surfaces ) within the DFG Priority Programme 2265 (Random Geometric Systems). Winter's work explores the mathematical foundations of fractals, stochastic processes, and geometric measurements. Key themes include Minkowski content, curvature measures, self-similar sets, percolation models, and applications to materials science and geoscience. Recent publications emphasize fractal dimensionality, surface roughness quantification, and stochastic convergence in complex systems. He teaches advanced courses including Stochastic Geometry , Fractal Geometry , and Markov Chains , and mentors students through seminars and proseminars. No awards or research grants besides DFG projects are documented.

• Quantum Chromodynamics
• Gauge Theory
• Lattice Theory
• +۷ مورد دیگر

Martin Lundquist Hansen is a Researcher at the Department of Mathematics and Computer Science, University of Southern Denmark's Faculty of Science, with a focus on lattice field theory and high-energy physics. His work intersects Quantum Chromodynamics (QCD) Standard Model Gauge theory Perturbation theory as evidenced by his fingerprint in Fermion physics, broken symmetry, and boundary conditions. Publications since 2018 highlight advancements in radiative leptonic decays of pseudoscalar mesons chiral perturbation theory with scalars gauge-invariant mass determination QCD+QED simulation code through OpenQ∗D and collaborative lattice calculations.

Monica Jinwoo Kangمشاهده پروفایل

استادیار

• Quantum Gravity
• Quantum Field Theory
• String Theory
• +۷ مورد دیگر

Monica Jinwoo Kang is an Assistant Professor at Texas A&M University's Department of Physics and Astronomy, specializing in mathematical physics and quantum gravity. Her research bridges theoretical physics and mathematics through holography, operator algebras, and quantum error correction. Education: PhD in Physics (Harvard, 2019), Bachelor's in Mathematics and Physics (UC Berkeley, 2012), Korea Science Academy Her work focuses on non-perturbative aspects of quantum field theory and quantum gravity, particularly through entanglement structures, bulk reconstruction in AdS/CFT, and geometric engineering of SCFTs. She has developed novel operator-algebraic frameworks for understanding holography in infinite-dimensional Hilbert spaces and discovered isomorphic superconformal theories with identical central charges. Recent publications demonstrate her expertise in multiparty entanglement holography, generalized symmetry constraints on 4D SCFTs, and nonperturbative gravity corrections to bulk reconstruction, with implications for baby universe formalism and quantum error correction. Scientific Awards: AKPA Outstanding Young Researcher Award (2025), Sherman Fairchild Fellowship, Purcell Fellowship, J. D. Jackson Award She has organized international conferences on stringy geometry and quantum field theory, and contributed to pedagogical lectures at institutions like Universidad Complutense de Madrid and the Simons Center. Her interdisciplinary approach combines algebraic geometry, lattice gauge theory, and quantum information to address fundamental questions in gravity and field theory.

Patric Östergårdمشاهده پروفایل

استاد

• Discrete Mathematics
• Information Theory
• Coding Theory
• +۴ مورد دیگر

Patric Östergård is a Professor at Aalto University's Department of Information and Communications Engineering. His research focuses on fundamental problems in discrete mathematics and information theory, utilizing combinatorial algorithms and massive computations to study existence and classification of mathematical structures with applications in ICT. Department: Information and Communications Engineering Institution: Aalto University His key research areas include coding theory, design theory, graph theory, and Shannon theory. He leads a high-performance computing cluster Medusa for computational work. His research is supported by the Academy of Finland's project 'Construction and Classification of Discrete Mathematical Structures' (2015–2019). Notable trends: Steiner triple systems, Hadamard matrices, and error-correcting codes Collaboration: Active in international partnerships, particularly in combinatorics and coding theory Scientific Awards Kirkman Medal (1997) for contributions to combinatorial research Doctor et Professor Honoris Causa from University of Pécs, Hungary (2013) He has supervised 7 doctoral theses and actively participates in academic service through editorial board memberships, conference committee roles, and hosting visiting scholars.

• Spintronics
• Spin-caloritronics
• Spin-Hall Effect
• +۹ مورد دیگر

Alexey Kovalev is an Associate Professor in the Department of Physics and Astronomy at the University of Nebraska . His research focuses on advanced topics in spintronics, quantum information theory, and magnetic materials. Spintronics Spin-caloritronics Quantum Computing Topological Insulators Magnetoelectric Memory Recent work includes studies on Majorana bound states, magnetic skyrmions, and spin superfluidity in antiferromagnets. He collaborates on quantum error correction codes and spin dynamics in chiral materials.

Ram Zamirمشاهده پروفایل

استاد

• Information Theory
• Digital Communications
• Signal Processing
• +۱۰ مورد دیگر

Professor Ram Zamir is a senior faculty member in the School of Electrical Engineering at Tel Aviv University, where he has been a professor since 2009 and a faculty member since 1996. He has held leadership roles including Head of the Electrical Engineering Program (2013–2017) and Head of the School of Electrical Engineering (2020–2023). His research bridges information theory, communication, signal processing, and learning, with a strong emphasis on geometric and lattice-based coding structures. His research interests include: Information Theory and Digital Communications Statistical and Musical Signal Processing Lattice Codes and Analog Coding via Frames Sparse Modeling and Random Matrix Theory His work has led to two influential books—one on lattice codes (Cambridge University Press, 2014) and another on asymptotic frame theory (NOW Publishers, 2021)—and nearly 200 journal and conference publications with significant citation impact. His recent focus includes the intersection of electrical engineering and music, where he promotes curriculum and research integration. Prof. Zamir has served in key roles in the IEEE Information Theory Society, including as editor, branch chair in Israel, and member of the Board of Governors. He organized the ITW 2015 conference in Jerusalem and has consulted for industry leaders such as Orckit, Actelis, and served as Chief Scientist at Celeno Communications (2004–2014), later acquired by Renesas. He advises graduate students and leads research initiatives in coding and signal processing, though specific students are not listed. He also contributes to academic and technological advancement through collaborations, grants, and industrial partnerships. His lab and research group focus on fundamental coding theory and its applications in modern communication and learning systems. Notably, he and his family donated a piano to the Faculty of Engineering in memory of his late mother, Esther Elchanati-Zamir, reflecting his passion for music and interdisciplinary innovation.

Frank Vallentinمشاهده پروفایل

استاد

• Optimization
• Semidefinite Programming
• Discrete Geometry
• +۸ مورد دیگر

Frank Vallentin is a full professor of applied mathematics (computer science) at the Mathematical Institute of the University of Cologne, Germany. He has held academic positions at Technische Universiteit Delft, Centrum Wiskunde & Informatica (CWI), and the Hebrew University of Jerusalem. His research spans optimization, discrete geometry, harmonic analysis, and computational mathematics. Research Interests: His primary mathematical interests include semidefinite programming, combinatorial optimization, harmonic analysis, discrete geometry, combinatorics, geometry of numbers, special functions, computational complexity, and coding and information theory. These areas reflect a deep integration of theoretical mathematics with algorithmic and computational techniques. The 15 most recent publications reveal a strong focus on geometric optimization, lattice problems, energy minimization, and semidefinite programming bounds. Key themes include chromatic numbers of lattices, symplectic capacities, polarization phenomena, and algorithmic solutions to geometric problems. His work often involves recursive SDP hierarchies, extremal configurations, and computational verification of theoretical bounds. Scientific Awards and Grants: SIAG/Optimization Prize (2011, with Christine Bachoc) NWO VIDI Grant (2010–2015): Semidefinite programming and harmonic analysis DFG Project: Symplectic capacities of polytopes (2017–) EU Horizon 2020 MINOA Project: Optimization with limited quantum resources (2017–) DFG Project: Spectral bounds in extremal discrete geometry (2019–) Advising and Grants: Vallentin has advised numerous PhD and master’s students at TU Delft and the University of Cologne, covering topics in discrete geometry, optimization, coding theory, and quantum information. He has secured major research funding from NWO, DFG, and the EU, supporting interdisciplinary projects in algorithmic optimization and mathematical physics. He is actively involved in organizing workshops and summer schools. Labs and Teams: He leads a research group at the University of Cologne focusing on optimization and discrete geometry, with strong collaborations with CWI Amsterdam, TU Delft, and international institutes. His team works on theoretical and computational aspects of geometric optimization, often using symmetry reduction and harmonic analysis.

• Manufacturing Engineering
• Advanced Machining Processes
• CAD/CAM Simulation
• +۶ مورد دیگر

Professor Antoniadis Aristomenis is a faculty member at the Technical University of Crete, affiliated with the School of Production Engineering and Management. His work focuses on advanced manufacturing processes, CAD/CAM simulation, laser engraving, and emerging technologies in materials science and augmented reality applications. He holds a prominent role in the Vice-Chancellor Office, indicating leadership responsibilities within the institution. Key research areas include: Process optimization of machining operations (drilling, hobbing, skiving) Laser-material interaction and surface engineering Development of serious games for manufacturing education Finite element modeling of cutting processes Additive manufacturing of composite materials Recent publications highlight contributions to: Enhanced drilling performance using RSM and ANN Innovative AR interfaces for industrial guidance Laser engraving quality control methodologies Simulation of complex machining processes No specific awards or grants are explicitly mentioned in the provided text, though his extensive publication record indicates sustained research activity. His work integrates theoretical models with practical industrial applications, emphasizing both innovation and educational dissemination through gamified training systems.

Yury Polyanskiyمشاهده پروفایل

استاد

• Information Theory
• Machine Learning
• Statistics
• +۳ مورد دیگر

Yury Polyanskiy is a Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), affiliated with the Laboratory for Information and Decision Systems (LIDS), the Institute for Data, Systems, and Society (IDSS), and the MIT Statistics and Data Science Center. He holds a Ph.D. from Princeton University (2010) and an M.S. from the Moscow Institute of Physics and Technology (2005). His research focuses on information theory, machine learning, statistical inference, error-correcting codes, and wireless communication. He has contributed to fundamental limits of communication systems, finite-blocklength analysis, and applications of information theory to learning and signal processing. Notable awards include the 2020 IEEE Information Theory Society James Massey Award, the 2013 NSF CAREER Award, and the 2011 IEEE Information Theory Society Paper Award. His work spans theoretical advancements and practical applications, including the development of the SPECTRE toolbox for short-packet communication. He is also co-authoring a textbook on information theory. Recent research highlights include studies on quantization techniques for machine learning (e.g., NestQuant), transformer-based empirical Bayes methods, and novel approaches to massive random access in wireless networks (e.g., unsourced multiple access). His contributions bridge information theory and modern data science, addressing challenges in high-dimensional data representation, neural network dynamics, and efficient communication architectures.

Benjamin Lee Greenmanمشاهده پروفایل

استادیار

• Programming Languages
• Gradual/Migratory Type Systems
• Language Interoperability
• +۴ مورد دیگر

Benjamin Lee Greenman is an Assistant Professor at the Kahlert School of Computing , part of the John and Maria Price College of Engineering at the University of Utah. His research focuses on programming languages, gradual/migratory type systems, formal methods, and human factors in software development. He holds a Ph.D. from Northeastern University (2020), a CIFellows postdoc at Brown University (2020–2022), and degrees from Cornell University (B.S. in ILR, M.Eng. in CS). Key projects include: Forge: A tool for teaching formal methods with lightweight model finding. FlowFPX: Tools for debugging floating-point exceptions in scientific computing. LTL Tutor: An adaptive learning system addressing temporal logic misconceptions. Gradual Typing Benchmarks: Evaluating performance and guarantees of type systems. His work emphasizes rigorous methods for language design, including empirical studies, performance evaluation, and human-centered approaches. Recent contributions include exploring misconceptions in LTL education and advancing type system interoperability between typed and untyped code. Teaching roles include courses on compilers, software verification, and programming languages. He advocates for practical tools like Rhombus (Python-like syntax with Lisp macros) and Static Python ’s sound gradual typing system.

Antonio Ragoمشاهده پروفایل

مدرس

• Computational Science
• Lattice Gauge Theory
• Quantum Chromodynamics
• +۵ مورد دیگر

Antonio Rago is a Lecturer in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), where he contributes to computational science with a focus on lattice field theories and high-performance computing. His research bridges theoretical physics and advanced computational techniques. Research Interests: His work centers on lattice gauge theory , particularly SU(2) and QCD simulations using Wilson fermions. He specializes in GPU-accelerated algorithms and the HiRep framework for scaling simulations across thousands of GPUs. His interests also extend to fermion formulations, chiral symmetry, and numerical stability in lattice field theories. The recent publications show a strong trend toward scalable computational methods in fundamental physics, emphasizing GPU parallelism, algorithmic efficiency, and non-perturbative quantum field theory. His media contributions reflect growing engagement with science policy, particularly advocating for national AI and supercomputing infrastructure. Scientific Contributions: Active in advancing lattice QCD with novel fermion discretizations. Core developer in HiRep for distributed GPU simulations. Advocate for national investment in academic AI computing. Advising and Grants: While no formal students are listed, his research output suggests mentoring within collaborative projects. He participates in large-scale computational initiatives, likely supported by Danish or EU research grants, though specific funding sources are not disclosed in the text. Labs and Teams: Works within a computational physics group at SDU, collaborating with researchers across Europe on lattice field theory projects. His team leverages GPU clusters for large-scale simulations, focusing on algorithmic scalability and physical observables in gauge theories.

• Progressive Collapse
• Structural Fire Analysis
• Tensegrity Structures
• +۸ مورد دیگر

Dr. Feng Fu is a Senior Lecturer at the School of Mathematics, Computer Science and Engineering , City, University of London. He serves as Editor-in-Chief of the Proceedings of the Institution of Civil Engineers - Structures and Buildings and holds leadership roles in professional organizations like the Institution of Structural Engineers and American Society of Civil Engineers (ASCE). His career blends academic research, industry consultancy, and code development, including contributions to ASCE standards on blast protection and disproportionate collapse mitigation. MSc in Software Engineering (University of Oxford), MBA (University of Manchester), PhD in Structural Engineering (University of Leeds), and BSc/MSc in Structural Engineering (Beijing University of Technology). Worked at WSP Group Ltd, Waterman Plc, and Beijing Institute of Architectural Design and Research, contributing to iconic projects like The Shard and Nakheel Tower. His research focuses on progressive collapse , structural fire analysis , tensegrity structures , and steel composite joints , with recent interdisciplinary work on machine learning and IoT applications in structural design. He has authored 160+ peer-reviewed papers, four books, and developed the first numerical procedure for progressive collapse analysis used in major projects. The 15 most recent articles span diverse topics including biomaterials for diabetic wound healing , seismic performance of composite structures , advanced sensors for structural monitoring , and multi-hazard analysis , reflecting his interdisciplinary expertise. Scientific Awards : Excellence in Teaching (2016), IStructE Young Researchers' Competition (2005), WUN Award (2003). Fellowships : Institution of Structural Engineers (2019–present), American Society of Civil Engineers (2020–present), Institution of Civil Engineers (2020–present), Higher Education Academy (2012–present). He supervises research students working on topics like progressive collapse under multi-hazards , FRP-reinforced concrete , and machine learning applications in structural analysis . His lab collaborates on international projects, including EU-funded initiatives and multi-institutional studies on structural resilience.

• Structural Mechanics
• Metamaterials
• Continuum Modeling
• +۳ مورد دیگر

Vito Diana serves as a Researcher in the Department of Civil, Chemical, and Environmental Engineering (DICCA) at the Polytechnic School of the University of Genoa. He is an active member of the Building Science research group (CEAR-06/A) and contributes to academic governance as a Member of the Polytechnic School Library Board. His research centers on advanced structural modeling, with specialized expertise in metamaterials, chiral lattice systems, and continuum homogenization techniques. Key investigations include high-frequency dynamics of beam-lattices, energy-absorbing multi-layered structures, micropolar media behavior, and dynamic analysis of masonry-like materials. This work bridges theoretical mechanics with practical civil engineering applications through rigorous mathematical modeling. Analysis of his 2023-2025 publications reveals consistent focus on chirality effects in energy absorption, scale-dependent material properties, and innovative continualization methods for discrete systems. His research demonstrates strong interdisciplinary connections between structural engineering, materials science, and theoretical mechanics with emphasis on real-world structural applications. No scientific awards were documented in the provided institutional profile. Diana teaches Structural Mechanics (code 98148) and Structural Modeling of Existing Buildings (code 98149) for the Master's Degree Course in Building Engineering. He maintains regular student availability through email appointments and actively contributes to the academic ecosystem via library governance. As part of the CEAR-06/A Building Science research group, his work integrates with broader university initiatives in structural analysis and preservation engineering, particularly focusing on modeling methodologies for existing infrastructure systems.

Karl Jansenمشاهده پروفایل

پژوهشگر

• Lattice Field Theory
• Quantum Computing
• Tensor Networks
• +۵ مورد دیگر

Karl Jansen is a researcher at DESY Zeuthen, Germany, where he leads the Center for Quantum Technologies and Applications (CQTA) and contributes to the NIC research group 'Elementary Particle Physics'. His work spans computational sciences, quantum computing, lattice field theory, and theoretical biology, with a focus on interdisciplinary approaches integrating physics and AI in drug design. Affiliated institutions: DESY Zeuthen, NIC (Research Center Jülich) Research areas: Quantum technologies, computational physics, molecular simulations, and epigenetic drug development Recent publications emphasize machine learning applications in drug discovery, epigenetic inhibition mechanisms, and advanced computational modeling techniques. His leadership in quantum technologies highlights DESY's commitment to cutting-edge research infrastructure. Personal interests include diving (documented across global locations like Australia, Taiwan, and Cyprus) and music, reflecting a multidisciplinary engagement beyond formal academic roles.