جست‌وجوی استاد و پژوهشگر

Rob Eggermontمشاهده پروفایل

استادیار

• Algebraic Geometry
• Discrete Mathematics
• Polynomial Representations
• +۵ مورد دیگر

Rob Eggermont is an Assistant Professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e), specializing in the Discrete Algebra and Geometry research group. His work focuses on finiteness properties in infinite-dimensional algebraic settings with symmetry, connecting algebraic geometry, representation theory, and combinatorics. His research has significant applications in fields including phylogenetics, chemistry, and algebraic statistics. Education: MSc in Mathematics from Leiden University (2011), cum laude PhD from Eindhoven University of Technology (2015), cum laude Rob Eggermont's research centers on how algebraic structures with symmetry maintain finiteness properties even in infinite-dimensional settings. His work on topological noetherianity demonstrates that in systems with sufficient symmetry, problems involving millions of variables can be as tractable as those with only a few variables. This has profound implications for computational algebra and geometric modeling. His research group plays a leading role in algebraic graph theory, finite and incidence geometry, and discrete Lie theory. An analysis of his recent publications (2017-2025) reveals a consistent focus on polynomial representations, GL-varieties, and symmetric matrix structures. His work frequently explores how finiteness properties emerge in infinite-dimensional settings through symmetry constraints. Collaborations with Jan Draisma and other mathematicians form a significant portion of his output, indicating strong research networks in algebraic geometry and representation theory. Scientific Awards: Jong Talent Aanmoedigingsprijs (2007) - awarded to the best first-year mathematics student at Leiden University Veni grant 016.Veni.192.113 from the Netherlands Organization for Scientific Research (NWO) Dr. Eggermont has secured research funding through competitive grants and has participated in numerous international workshops and conferences, including the AIM workshop on 'Representation stability' (San Jose, 2016) and the BIRS workshop on 'Free Resolutions, Representations, and Asymptotic Algebra' (Banff, 2016). His research group actively contributes to the DIAMANT symposium and the Intercity Number Theory Seminar. Within the Discrete Algebra and Geometry group at TU/e, Eggermont collaborates with colleagues on advancing the theoretical foundations of algebraic structures with symmetry. His work has helped establish connections between representation theory, combinatorics, and practical applications in scientific computing.

• Condensed Matter Theory
• Quantum Information Science
• Topological Order
• +۴ مورد دیگر

Julia Wildeboer is a Researcher in the Condensed Matter Physics and Materials Science Department at Brookhaven National Laboratory . Her work bridges condensed matter theory , quantum information science , and computational physics , focusing on non-equilibrium quantum systems, topological phases, and quantum memory design. Ph.D. : Washington University in St. Louis (advisor: Prof. Alexander Seidel, Thesis: "Physics of Resonating Valence Bond Spin Liquids") M.Sc. : Technical University of Dresden, Germany Her research spans quantum many-body scars , topological order in 2D systems , quantum dimer models , and non-Abelian anyons . She develops exactly solvable models for unconventional quantum phenomena and investigates entanglement entropy as a probe of topology. Recent work explores quantum phase transitions in kagome metals and symmetry-protected quantum memory . Scientific contributions include designing novel quantum scars , solving sign-problems in Monte Carlo simulations , and proposing probes for topological order . Her publications highlight expertise in DMRG , exact diagonalization , and Monte Carlo methods . Contact: jwildeboe@bnl.gov .

• Topological Quantum Field Theory
• Quantum Computing
• Condensed Matter Physics
• +۲ مورد دیگر

Alexei Yurievich Kitaev is a Russian-American theoretical physicist and professor at the California Institute of Technology. His work spans topological quantum field theory, quantum computing, and condensed matter physics, with groundbreaking contributions to fault-tolerant quantum computation and topological phases of matter. Education: Moscow Institute of Physics and Technology (1986), Ph.D. from Landau Institute for Theoretical Physics (1989). Affiliations: Caltech (since 2002), Microsoft Research (1999–2001), Landau Institute (1989–1998). Research focuses on topological quantum field theory, quantum computing, and condensed matter physics, including the development of the toric code, Kitaev spin liquid, and Sachdev–Ye–Kitaev model. His 2006 paper introduced exactly solvable lattice models for topological order. Key awards include the MacArthur Fellowship (2008), Breakthrough Prize in Fundamental Physics (2012), Dirac Medal (2015), Oliver E. Buckley Prize (2017), and the Henri Poincaré Prize (2024). Kitaev also advocates for political causes, notably signing an open letter against the Russian invasion of Ukraine in 2022. He collaborates with Google Quantum AI on experimental realizations of fault-tolerant quantum computation using the toric code, as seen in recent publications (e.g., 2021–2023 studies on topological qubits and error suppression).

Charles L. Kaneمشاهده پروفایل

استاد

• Theoretical Condensed Matter Physics
• Topological Insulators
• Quantum Spin Hall Effect
• +۳ مورد دیگر

Charles L. Kane is a renowned theoretical condensed matter physicist and the Christopher H. Browne Distinguished Professor of Physics at the University of Pennsylvania. He earned his B.S. in physics from the University of Chicago (1985) and his Ph.D. from the Massachusetts Institute of Technology (1989). His research focuses on topological insulators, quantum spin Hall effect, and novel quantum phases in condensed matter systems. Dirac Prize (2012) Oliver E. Buckley Prize (2012) Breakthrough Prize in Fundamental Physics (2019) His work has revolutionized the understanding of topological materials, particularly through predicting the quantum spin Hall effect in graphene and pioneering concepts in topological insulators. Recent research explores topological density correlations, multipartite entanglement, and nonlinear transport phenomena. Kane's scientific contributions have been recognized by numerous prestigious awards, including the Franklin Medal (2015) and the Frontiers of Knowledge Award (2018). He maintains active collaborations and continues to advance frontiers in theoretical condensed matter physics.

• Information Theory
• Digital Communication
• Multi-User Information Theory
• +۴ مورد دیگر

Prof. Uri Erez, born in 1971 in Tel Aviv, Israel, is a faculty member at the Department of Electrical Engineering-Systems, Tel Aviv University. He received his B.Sc. in Mathematics and Physics (1996), M.Sc. (1999), and Ph.D. (2003) in Electrical Engineering from Tel Aviv University. From 2003 to 2004, he was a Post-Doctoral Associate at MIT's Signals, Information and Algorithms Laboratory. Since 2005, he has been affiliated with Tel Aviv University's engineering faculty. Research Interests Information theory and digital communication Algorithms and signal processing for communication systems Space-time coding and dimension reduction Lattice structures in digital communication applications Contact: uri@eng.tau.ac.il | Office: Electrical Engineering Building, Room 120

• Applied Mathematics
• Theoretical Computer Science
• Probability Theory
• +۲ مورد دیگر

Alex Karrila is an Assistant Professor (tenure track, level 2) at Åbo Akademi University's Faculty of Natural Sciences and Engineering , Department of Mathematics. Their research focuses on lattice theory, random conformal geometry, and mathematical analysis, with applications in coding theory and statistical mechanics. Specializes in Well-rounded Lattices and Gaussian Wiretap Channels Active in Positively Homogeneous Functions and Minkowski Inequality Investigates Eavesdropper security models and Coset Coding Recent publications analyze the six-vertex model's height function delocalization and convergence of random curves in conformal geometry. Their work intersects with subfields including Schramm-Loewner Evolution (SLE), KPZ equation scaling limits, and Green's functions. All publications are peer-reviewed and open-access where available.

• Quantum Computing
• Quantum Foundations
• Diagrammatic Reasoning
• +۳ مورد دیگر

John van de Wetering is an Assistant Professor at the Theoretical Computer Science group of the Informatics Institute at the University of Amsterdam . He works with the QuSoft research center and co-develops the PyZX open-source quantum compiler. His research spans quantum computation, diagrammatic reasoning, and quantum foundations. Education: PhD in Computer Science (2022, Radboud University) Research: Focuses on ZX-calculus for quantum circuit optimization, verification, and simulation. Explores quantum foundations through algebraic and compositional methods. Recent work includes quantum circuit optimization with AlphaTensor, completeness proofs for ZH-calculus, and scalable spider nets for transversal non-Clifford gates. He directs the new Master's program in Quantum Computer Science at UvA and co-authored the book Picturing Quantum Software . Notable collaborations include PyZX development and EU Gender Equality Working Group participation. Supervision includes current PhD students Lia Yeh (Oxford), Sarah Li (UvA), and Marc Farreras (Leiden). Former students include Boldizsár Poór (Quantinuum), Julien Codsi (Princeton), and Yanbin Chen (TUM). Tools & Outreach: Maintains the ZX-calculus Wikipedia page, co-lectured courses like Quantum Processes and Computation , and develops the ZX-calculus educational website. Organized QPL2026 conference and contributed to open-access journal Quantum .

• Wireless Communication
• Mobile Networks
• Wireless IoT Applications
• +۶ مورد دیگر

Prof. Dr. Luciano Sarperi is a Lecturer at the ZHAW School of Engineering ’s Institute of Signal Processing and Wireless Communications , focusing on applied R&D with industry partners. His work spans Wireless Communication Systems , Mobile Networks (NR, LTE, NB-IoT), and Software Defined Radio . Expertise in GNSS Localization , Wireless Time-Synchronization , and Interference Cancellation for MIMO systems. Active in UAV navigation, RFI detection, and LoRa/Wi-Fi applications. Research Trends (2025–2004): Peer-reviewed work on MIMO Pre-coding , GNSS for Drones , Blind Signal Processing , and Wireless Standards . Patents in Multi-Cell MIMO and Channel Feedback . Education : PhD in Digital Signal Processing for MIMO-OFDM from the University of Liverpool (2007), M.Sc. in Microelectronic Systems and Telecommunications (2002). Experience : 2010–2017 at Swisscom (Research Engineer), 2007–2010 at Fujitsu Laboratories (U.K.).

• Wireless Communication
• Information Theory
• Error Correction Coding
• +۳ مورد دیگر

Dr. Min Qiu is a Postdoctoral Research Associate at the University of New South Wales (UNSW), with a research focus on coding theory, information theory, and wireless communication systems. He received his Ph.D. in Electrical Engineering from UNSW in 2019 and a B.E. (Hons.) in Electronics and Telecommunications Engineering from the Australian National University in 2012. His work addresses fundamental limits of communication systems and designs reliable networks and storage solutions under unreliable conditions. Dr. Qiu's research spans bandwidth-efficient coded modulation, delay-Doppler communications, finite blocklength coding, lattice coding for interference management, and joint sensing and communications. He has served as a reviewer for over 15 journals and conferences, including IEEE Transactions on Communications and the IEEE International Symposium on Information Theory. Key scientific contributions include awards for exceptional peer-review service and grants such as the 2021 ECA EDI Seed Grant. He is affiliated with IEEE Communication Society, IEEE Information Theory Society, and Engineers Australia.

Manuel Pereiroمشاهده پروفایل

پژوهشگر

• Magnetic Topological Systems
• Atomistic Spin Dynamics
• Magnonics
• +۶ مورد دیگر

Manuel Pereiro is a Researcher at the Department of Physics and Astronomy; Materials Theory , Uppsala University , Sweden. His work bridges condensed matter physics , magnetic materials , and computational modeling , with a focus on atomistic spin dynamics and ab-initio methods. He is a key member of the Atomistic Spin Dynamics (ASD) team , contributing to the development of the UppASD simulation code used globally. PhD in Physics, University of Santiago de Compostela (Spain), with over 55 high-impact publications Recipient of the Best PhD Thesis 2010 in the Faculty of Physics, Santiago de Compostela Awarded a European Thesis during postdoctoral work Secured Knut and Alice Wallenberg Foundation Grant (2018) for research on time crystals and topological magnetic materials Research Focus : Manuel specializes in magnetic topological systems , including skyrmions in kagome magnets and B20 compounds . His work explores ultrafast demagnetization driven by spin-polarized currents , quantum spin dynamics (e.g., magnon-magnon entanglement ), and non-collinear magnetism in van der Waals magnets and chiral materials . He combines Landau-Lifshitz-Gilbert equations with density functional theory to model spin-lattice interactions and predict novel magnetic phenomena. Collaborations and Impact : He collaborates internationally with groups at IFW Dresden (Germany), Federal University of Pará (Brazil), and University of South Florida (USA). His research targets energy-efficient electronics via magnonic logic devices and quantum vacuum energy extraction . His 15 most recent publications highlight advancements in spin-lattice coupling , skyrmion dynamics , and quantum entanglement in antiferromagnets . Scientific Awards : Best PhD Thesis Award, 2010 (University of Santiago de Compostela) European Thesis Award (postdoctoral period) Knut and Alice Wallenberg Foundation Grant (2018) Technological Contributions : Developed the UppASD code , enabling global research on atomistic spin dynamics. His methods integrate first-principles calculations with spin models to study magnetic materials without prior assumptions. This includes modeling non-collinear systems , strongly correlated materials , and time-crystal analogs .

• Algebraic Cryptanalysis
• Post-Quantum Cryptography
• Symmetric Cryptography

Morten Øygarden is a Postdoctoral Fellow in the Department of Cryptography at Simula UiB, a joint research initiative between Simula Research Laboratory and the University of Bergen. His work bridges theoretical cryptography and practical security analysis within Norway's premier cryptographic research environment. His educational background culminates in a 2021 PhD from the University of Bergen with the thesis "Algebraic Cryptanalysis of Cryptographic Schemes with Extension Field Structure", establishing his expertise in algebraic methods for cryptanalysis. Øygarden's research focuses on Algebraic Cryptanalysis , Post-Quantum Cryptography , and Symmetric Cryptography , specializing in vulnerabilities of multivariate systems, code-based schemes, and ring-based primitives. He develops novel Gröbner basis techniques to break cryptographic assumptions underlying quantum-resistant candidates, with direct implications for NIST standardization processes. Analysis of his 2020-2024 publications reveals consistent innovation in algebraic attack methodologies, particularly against arithmetization-oriented primitives for zero-knowledge proofs and MPC-friendly ciphers. His work demonstrates exceptional depth in exploiting mathematical structures of symmetric primitives while advancing post-quantum security evaluations of multivariate and code-based systems. His publication record in top venues including CRYPTO, EUROCRYPT, and the Journal of Cryptology reflects significant contributions to cryptographic science, though specific awards or grant details are not documented in available sources.

• Data Science
• IoT
• Blockchain
• +۵ مورد دیگر

Zheng Wen is an Associate Professor (non-tenure-track) at Waseda University, affiliated with the Faculty of Science and Engineering and the Global Center for Science and Engineering. His research spans multiple interdisciplinary domains at the intersection of information technology, security systems, and artificial intelligence applications. Dr. Wen received his Ph.D. from Waseda University between 2013 and 2019, following undergraduate studies at Wuhan University from 2005 to 2009. Dr. Wen's research interests focus on the convergence of emerging technologies for practical applications. His primary areas include Data Science , Internet of Things (IoT) , Blockchain , and Artificial Intelligence , with specific applications in communication networks, disaster management, and content-oriented networking. His work demonstrates a strong emphasis on solving real-world problems through technological innovation, particularly in security-critical domains. Analysis of Dr. Wen's publication record reveals a consistent research trajectory focused on applying machine learning and AI techniques to security and communication challenges. His recent work shows increasing emphasis on blockchain applications for IoT security, GNSS spoofing detection for drone systems, and millimeter-wave imaging for security applications. The interdisciplinary nature of his research connects computer science, electrical engineering, and practical security implementations. Dr. Wen is an active member of professional organizations including IEEE and IEICE, reflecting his engagement with the broader academic community in his fields of expertise. While specific details about his advising and grant activities are not provided in the available information, his extensive publication record across multiple domains suggests active research supervision and likely participation in collaborative research projects. His work on drone security, blockchain applications, and millimeter-wave imaging indicates potential industry partnerships and practical implementations of his research. Dr. Wen's research appears to be conducted within collaborative teams focusing on security systems, wireless communications, and AI applications, with frequent co-authorship patterns suggesting established research groups working on related projects in these domains.

Keivan Esfarjaniمشاهده پروفایل

دانشیار

• Computational Materials Science
• Thermoelectricity
• Condensed Matter Physics
• +۴ مورد دیگر

Keivan Esfarjani is an Associate Professor at the University of Virginia in the Department of Mechanical and Aerospace Engineering . He holds a Ph.D. in Condensed Matter Theory from the University of Delaware (1991) and conducts research in Computational Materials Science , focusing on thermoelectricity and heat/charge transport modeling using first-principles DFT calculations. Education : Ph.D., 1991, University of Delaware His work spans materials like carbon, silicon, germanium , and 2D transition metal dichalcogenides (TMDCs) , with recent advancements in thermoelectric transport, anharmonic lattice dynamics, and thermal management of 2D heterostructures. He develops novel computational tools like ALATDYN and ELEMENTS for analyzing thermal conduction and phase changes at atomic scales. Contact: ke4c@virginia.edu

Marcelo Reggioمشاهده پروفایل

استاد

• Fluid Mechanics
• Computational Fluid Dynamics
• Lattice Boltzmann Method
• +۳ مورد دیگر

Marcelo Reggio is a Full Professor in the Department of Mechanical Engineering at Polytechnique Montréal, where he has established a significant research career spanning fluid dynamics and computational methods. He is an active member of the Fluid Dynamics Laboratory (LADYF), focusing on cutting-edge simulations of complex fluid phenomena. His educational background includes: Baccalaureate from Chile Master of Applied Science (M.Sc.A.) from Polytechnique Montréal Ph.D. from Polytechnique Montréal Research Focus: Professor Reggio's work centers on Computational Fluid Dynamics (CFD) with specialization in the Lattice Boltzmann Method (LBM). His research addresses fundamental and applied challenges in: Turbomachinery design optimization Wind turbine aerodynamics and icing effects Rarefied gas flows through porous media Multicomponent and multiphase flow modeling River current dynamics This work bridges theoretical fluid mechanics with industrial applications in energy and manufacturing. Publication Trends: Analysis of his 15 most recent articles (2016-2024) reveals dominant themes: advanced LBM techniques for non-equilibrium gas flows, validation of open-source CFD codes, multiphase interactions, and stochastic modeling of porous materials. His methodological innovations consistently target improved accuracy in complex physical scenarios. Academic Supervision: Professor Reggio maintains an active research group, having supervised: 12 doctoral students 20 master's students Student theses frequently explore LBM applications, turbomachinery, and numerical method development. Laboratory Leadership: At the Fluid Dynamics Laboratory (LADYF), he contributes to developing computational frameworks for fluid simulation, emphasizing GPU acceleration and industrial problem-solving.

Nikhil Guptaمشاهده پروفایل

استاد

• Cybersecurity in Manufacturing
• Additive Manufacturing of Composite Materials
• Materials Characterization under Dynamic Loading
• +۵ مورد دیگر

Dr. Nikhil Gupta is a Professor in the Department of Mechanical and Aerospace Engineering at the NYU Tandon School of Engineering , with affiliations to the Department of Civil and Urban Engineering and the Composite Materials and Mechanics Laboratory (CMML). He focuses on cybersecurity in additive manufacturing , dynamic materials characterization , and machine learning for composites . Education : Bachelor of Engineering, Metallurgical Engineering, Malaviya National Institute of Technology, Jaipur (1996) Master of Engineering, Metallurgical Engineering, Indian Institute of Science (1998) PhD, Mechanical Engineering, Louisiana State University (2003) His research explores additive manufacturing of complex composites , structural health monitoring , and cybersecurity threats in digital manufacturing . Notably, he co-developed embedded authentication codes to prevent 3D printing counterfeiting and pioneered machine learning techniques for defect detection in AM parts. His work is supported by the National Science Foundation and Texas A&M Engineering Experiment Station. The 15 most recent articles highlight trends in metamaterial design , bioprinting for tissue engineering , and cybersecurity frameworks for cyber-physical manufacturing , with a strong emphasis on experimental validation, computational modeling, and industrial applications. Scientific Honors : Fellow, ASM International (2022) Fellow, American Society for Composites (2022) Senior Member, National Academy of Inventors (2024) Brimacombe Medalist Award, TMS (2020) ASM Silver Medal (2013) As advisor to PhD student Youssef AbouelNour , Gupta investigates viscoelastic material modeling and in-situ monitoring for additive manufacturing. His lab, CMML, integrates fiber-optic sensors and AI-driven diagnostics to enhance manufacturing security and material performance.