جست‌وجوی استاد و پژوهشگر

Zhenyu Cuiمشاهده پروفایل

دانشیار

• Financial Engineering
• Insurance Analytics
• Operations Research
• +۵ مورد دیگر

Zhenyu Cui is an Associate Professor of Financial Engineering at the School of Business, Stevens Institute of Technology. He holds a PhD in Statistics from the University of Waterloo and a BS in Actuarial Science from the University of Hong Kong. His research focuses on financial engineering, insurance analytics, and operations research, with notable contributions to stochastic volatility models, Monte Carlo simulation, and financial systemic risk. He has published in top journals such as Mathematical Finance, SIAM Journal on Financial Mathematics, and European Journal of Operational Research. Education: PhD (2013, Statistics, University of Waterloo); MS (2010, Quantitative Finance, University of Waterloo); BS (2008, Actuarial Science, University of Hong Kong). Research Interests: Financial Systemic Risk, Monte Carlo Methods, Stochastic Volatility, Option Pricing, and Risk Management. His work bridges theoretical finance and practical applications, emphasizing robust pricing techniques and computational methods. Grants include leadership roles in NSF-funded projects on quantum algorithms for financial risk management and collaborations with institutions like Accenture and the Society of Actuaries. Awards include recognition for top-cited articles and editorial excellence.

Hou Man Chinمشاهده پروفایل

استاد مهمان

• Quantum Physics and Information Technology
• Machine Learning in Photonic Systems
• Quantum Key Distribution
• +۳ مورد دیگر

Hou Man Chin is a Visiting Professor at the Technical University of Denmark (DTU), affiliated with the Department of Electrical and Photonics Engineering and the Department of Physics. His research spans Quantum Physics and Information Technology, focusing on Machine Learning in Photonic Systems. He explores applications in quantum key distribution, optical communication systems, and quantum cryptography, with a particular emphasis on securing network infrastructure through advanced quantum protocols. Key areas of research include squeezed light generation and recovery, digital signal processing for quantum communication, and overcoming technical challenges like phase noise and signal degradation in long-distance systems. His work addresses practical implementation of quantum technologies, such as composable security frameworks and real-world deployment of quantum encryption methods. Hou Man Chin collaborates with experts in quantum technologies, including Ulrik Lund Andersen and Darko Zibar, on projects related to quantum information processing and machine learning integration. His research group (qTReX) develops semi-autonomous quantum key distribution systems and investigates vulnerabilities in modulation leakage and carrier recovery mechanisms.

• Nanoelectronics
• Two-Dimensional Materials
• Semiconductor Device Physics
• +۵ مورد دیگر

Ivan Sanchez Esqueda is an Associate Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University. His research focuses on nanoelectronics, 2D materials, and neuromorphic computing, with significant contributions to radiation effects in semiconductor devices. Education: Ph.D. Electrical Engineering, Arizona State University (2011) M.Sc. Electrical Engineering, Arizona State University (2006) B.Sc. Electrical Engineering, University of Arizona (2004) Dr. Esqueda's research interests span nanoelectronics, two-dimensional (2-D) and one-dimensional (1-D) materials, device nanofabrication, characterization, analysis, and modeling. He explores new device functionalities for novel computing, sensing, and memory applications, particularly hardware implementation of neuromorphic computing and machine learning. His work includes fundamental understanding of nanoscale electronics, confinement and scattering effects in low-dimensional electronic systems, computational nanoelectronics, and modeling of semiconductor devices. A significant portion of his research focuses on defect-related mechanisms and their impact on performance, variability, and reliability of devices and circuits, including radiation and aging effects in commercial CMOS and emerging nanotechnologies. His publication record shows a clear trend toward neuromorphic computing applications using 2D materials, particularly hexagonal boron nitride memristors, and continued investigation of radiation effects in advanced semiconductor technologies. Recent work demonstrates increasing focus on practical implementations of neural networks and machine learning hardware using novel materials. As an educator, Dr. Esqueda teaches courses including EEE 436 (Fundamentals of Solid-State Devices) and EEE 531 (Semiconductor Device Theory I), and mentors numerous graduate students through thesis and dissertation research. His research team at ASU focuses on the fabrication, characterization, and modeling of advanced electronic technologies, developing novel devices based on low-dimensional materials for computing, sensing, and memory applications. They particularly investigate device behavior in extreme environments including radiation and cryogenic conditions.

Amarendra Kumar Sarmaمشاهده پروفایل

استاد

• Quantum Optomechanics
• Quantum Entanglement
• Circuit Quantum Electrodynamics
• +۷ مورد دیگر

Dr. Amarendra Kumar Sarma is a full Professor in the Department of Physics at the Indian Institute of Technology Guwahati (IIT Guwahati), where he has been faculty since 2007 and Professor since 2018. He leads the Theoretical Quantum Optics and Quantum Technology Group, focusing on frontier areas of quantum science including quantum optomechanics, entanglement, and nonlinear photonics. His research explores quantum technology through multiple interconnected domains: Quantum Hybrid Systems: Integrating superconducting qubits with optomechanical elements for quantum transduction and sensing Nonlinear Dynamics: Soliton physics, PT-symmetric optics, and ultrafast switching in waveguides Quantum Control: Entanglement generation, mechanical squeezing, and quantum synchronization techniques Quantum Metrology: Overcoming standard quantum limits for force sensing using electro-optomechanical approaches Analysis of his 15 most recent publications (2018-2025) reveals strong emphasis on hybrid quantum systems (60% of works), with particular focus on quantum-classical interfaces for sensing applications. PT-symmetry and nonlinear dynamics constitute 30% of output, while quantum information fundamentals comprise 10%. Machine learning integration emerges as a new frontier in quantum control methodologies. He actively mentors researchers including 7 current PhD students and 12 former advisees. Notable grants include: STARS-2 project: 'Exploring Hybrid Circuit QED Systems for Quantum Technology' (2024-2027) SERB MATRICS: 'Soliton Dynamics in PT-Symmetric Models' (2020-2023) DST Fast-track: 'Parity-time Symmetry in Nonlinear Optics' (2014-2017) The Quantum Optics and Quantum Technology Group develops theoretical frameworks for experimental quantum implementations, maintaining collaborations with international institutions in quantum materials and device physics.

Boris Shklovskiiمشاهده پروفایل

استاد

• Condensed Matter Physics
• Theoretical Physics
• Transport Theory
• +۱۰ مورد دیگر

Boris Shklovskii is a Professor at the School of Physics and Astronomy at the University of Minnesota, where he holds the A.S. Fine Chair in Theoretical Physics at the William I. Fine Theoretical Physics Institute. His office is located at 275-10 John T. Tate Hall, 116 Church Street SE, Minneapolis, MN 55455. Dr. Shklovskii's primary research interests include: Condensed Matter Physics Theoretical Physics Theory of transport and electron-electron correlations in disordered systems Quantum Hall effect Hopping conduction Metal-nonmetal transition Transport in nano-crystal films His work centers on understanding electron behavior in disordered systems. A significant portion of his research builds upon the Efros-Shklovskii Coulomb gap theory, which he helped develop half a century ago. His recent publications focus on the conductivity of two-dimensional semiconductors and topological insulators in strong Coulomb disorder, electron binding energy in bilayer graphene, and plasmons in semiconductor wires. The fingerprint analysis of his work shows strongest connections to Hopping Conduction (100%), Density of States (93%), Low Temperature physics (85%), Variable Range Hopping (81%), and Coulomb Gap (73%). Dr. Shklovskii has published extensively throughout his career, with 204 documented research outputs spanning from the 1960s to present. His most recent publications (2022-2024) continue to advance understanding in condensed matter physics, particularly in disordered systems and two-dimensional materials, with some papers accumulating over 20 citations. His notable project involvement includes: MRSEC IRG-2: Sustainable Nanocrystal Materials (2014-2020) as Senior Investigator Dr. Shklovskii's work has significant implications for understanding fundamental physics in disordered materials and contributes to UN Sustainable Development Goals related to clean energy and sustainable materials development.

Marco Willمشاهده پروفایل

پژوهشگر

• Graphene
• Carbon Nanotubes
• Resonators
• +۷ مورد دیگر

Marco Will is a Project Employee at Aalto University's Department of Applied Physics , specializing in quantum devices and nanoscale systems. He holds a Master's degree in Engineering and Technology from Rheinisch-Westfälische Technische Hochschule Aachen (awarded 2016). Education: Master's in Engineering and Technology (RWTH Aachen, 2016) Marco's research focuses on graphene-based quantum systems , carbon nanotubes , and superconducting microwave devices . Key areas include low-noise amplification , thermal response dynamics , and entanglement generation using advanced nanofabrication techniques. His work often intersects with quantum technology , microwave engineering , and condensed matter physics . Recent publications highlight his expertise in graphene microwave resonators , Josephson junction fluctuations , and Kerr-free metamaterials for quantum information processing. Collaborations span institutions in Europe, with datasets contributed to open repositories like Zenodo. Marco has presented at international conferences, including a 2020 talk on suspended CNT weak links for condensed matter sensing. His research outputs include 13 publications, multiple datasets, and a doctoral thesis on low-dimensional electrical systems .

Dima Krioukovمشاهده پروفایل

استاد

• Network Theory
• Network Geometry
• Random Geometric Graphs
• +۷ مورد دیگر

Dima Krioukov is a Professor at Northeastern University with appointments in the Departments of Physics, Mathematics, and Electrical & Computer Engineering. He is affiliated with the Network Science Institute and leads the DK-Lab research group. His work bridges theoretical physics, mathematics, and network science with applications to the Internet, neuroscience, and cosmology. Primary Office: 177 Huntington Avenue, 2nd floor, Rm. 227, Boston, MA 02115 Additional Locations: The Roux Institute (London and Portland) Contact: +1-617-373-2934 Professor Krioukov's research spans network theory , network geometry , causal sets , and fundamentals of network dynamics . His work establishes connections between geometric properties of networks and their functional characteristics, with applications to navigation in complex systems. He has demonstrated that latent hyperbolic geometry explains heterogeneous degree distributions and strong clustering in real networks, and that the large-scale structure of the universe shares properties with complex networks like the Internet and the brain. His research has led to practical applications including optimal routing schemes for telecommunication networks based on hyperbolic geometry. His recent publications reveal a strong focus on the intersection of geometry and network science, with particular attention to causal sets, Riemann surfaces, and hyperbolic geometry. The research trends show increasing sophistication in connecting discrete network structures with continuous geometric spaces, with applications ranging from quantum gravity to efficient Internet routing. The work demonstrates how fundamental geometric principles govern the structure and function of diverse complex systems across multiple domains. Top 2% scientists worldwide (Stanford University 2024 assessment) USPTO patent on super-scalable routing in telecommunication networks Krioukov leads the DK-Lab, which focuses on theoretical aspects of network science with practical applications. His lab has developed methods to infer latent geometries of networks, created optimal routing algorithms based on hyperbolic geometry, and established connections between network structure and cosmological models. Current projects include research on network geometry, navigation in networks, random graphs and their limits, fundamentals of network dynamics, and quantum gravity applications. The lab maintains strong connections with both theoretical physics and practical network engineering communities.

• Quantum Optics
• Quantum Photonics
• Quantum Technologies
• +۳ مورد دیگر

Virginia D'Auria is a University Professor at Université Côte d'Azur and currently serves as the Director of the QuantAzur Institute. She is affiliated with the Nice Institute of Physics (INPHYNI), where her research focuses on quantum optics and photonics, leveraging quantum properties of light to advance information processing and communication paradigms. Research Themes: Optics, Quantum Photonics, Quantum Technologies, Societal Issues of Quantum Science Expertise spans discrete and continuous variable quantum information encoding regimes, including their hybridization Her recent experimental work includes generating and manipulating high-dimensional entangled states on optical chips and creating Schrödinger cat-like states of light. Contact details include email Virginia.DAURIA@univ-cotedazur.fr and phone +33 4 89 15 28 58.

Daniel Alonso Ramírezمشاهده پروفایل

استاد

• Quantum Thermodynamics
• Quantum Entanglement
• Quantum Discord
• +۵ مورد دیگر

Daniel Alonso Ramírez is a Full Professor in the Department of Physics at the Faculty of Physics, University of La Laguna (ULL), Spain. He is affiliated with the University Institute of Advanced Studies (IUDEA) and The Institute of Mathematics and Applications, conducting research within the Quantum Physics Group focused on fundamental quantum phenomena. His educational background includes: Undergraduate in Physics from Universidad de La Laguna PhD in Sciences from Universite Libre de Bruxelles Postdoctoral research at Universita degli Studi di Milano (Como) Professor Ramírez's research spans Quantum Thermodynamics (energy transport in quantum thermal machines and trapped ions), Quantum Correlations (Entanglement and Discord in continuous variable systems), Decoherence in hybrid systems, Non-Markovian Quantum Open Systems, and Quantum Chaos (light scattering by black holes). His work bridges theoretical quantum physics with practical applications in quantum information and thermodynamics. Recent publications (2014-2023) demonstrate sustained focus on quantum thermodynamics and non-Markovian dynamics, with significant contributions to understanding thermal machines at quantum scales and energy transport anomalies. The research employs advanced theoretical frameworks in quantum open systems and statistical mechanics. No scientific awards were documented in the provided materials. He has supervised six PhD students including Inés de Vega, Irene Puerto, and Luis Correa. His research group comprises current members Antonia Ruiz, Jose Pascual, Santiago Brouard, Rafael Sala, Fernando Delgado Acosta, and Luis A. Correa. The Quantum Physics Group maintains collaborations with institutions in Belgium, Italy, Spain, USA, and Germany.

Lajos Hanzoمشاهده پروفایل

استاد

• Wireless Communications
• Optical Wireless Systems
• Signal Processing
• +۵ مورد دیگر

Lajos Hanzo is a distinguished Professor at the University of Southampton's School of Electronics and Computer Science (ECS), where he has established himself as a leading authority in wireless communications and signal processing. His academic profile showcases extensive contributions to the field with over 1400 publications and significant recognition through multiple prestigious fellowships. Dr. Hanzo received his degree in electronics in 1976 and his doctorate in 1983, followed by an honorary doctorate in 2009. His educational background laid the foundation for a career that has continually evolved with communication technologies from early wireless systems through to contemporary 6G research and quantum communications. Hanzo's research spans wireless communications, optical wireless systems, MIMO technologies, and increasingly intersects with artificial intelligence applications for next-generation networks. His work demonstrates remarkable synergy between theoretical foundations and practical implementations, addressing challenges in spectral efficiency, channel capacity, and reliable transmission across diverse communication scenarios. He has made seminal contributions to space-time coding, non-orthogonal multiple access (NOMA), and index modulation techniques that have influenced multiple generations of wireless standards. Analysis of his recent publications reveals a clear progression toward more complex communication paradigms, with increasing focus on 6G technologies, integration of deep learning with traditional communication theory, and exploration of quantum-inspired communication approaches. His work consistently addresses the tension between theoretical capacity limits and practical implementation constraints, with recent papers demonstrating particular interest in millimeter-wave communications, visible light communication, and massive connectivity solutions for IoT applications. FREng (Fellow of the Royal Academy of Engineering) FIEEE (Fellow of the IEEE) FIET (Fellow of the Institution of Engineering and Technology) Fellow of EURASIP (European Association for Signal Processing) DSc (Doctor of Science) While specific details of his advising activities aren't prominently featured in the provided materials, Hanzo's extensive publication record spanning multiple decades suggests significant mentorship of graduate students and postdoctoral researchers. His research has clearly attracted substantial funding to support investigations across wireless communications, with particular emphasis on coding theory, MIMO systems, and next-generation network architectures. The collaborative nature of his recent work indicates ongoing engagement with international research consortia addressing 5G evolution and 6G standardization.

Hong Qianمشاهده پروفایل

استاد

• Mathematical Biology
• Mathematical Physics
• Stochastic Mathematics
• +۷ مورد دیگر

Professor Hong Qian is the Olga Jung Wan Endowed Professor of Applied Mathematics at the University of Washington, Seattle. He holds adjunct roles in Bioengineering and has held visiting professorships at institutions like Jilin University and Fudan University. His research focuses on stochastic analysis and nonequilibrium thermodynamics in biological systems, particularly cellular dynamics and complex systems like epidemiology and economics. Education: B.A. in Astrophysics (Peking University, 1982), Ph.D. in Biochemistry and Biophysics (Washington University School of Medicine, 1989). Professional Experience: Postdoctoral fellowships at Caltech and University of Oregon, prior roles at UCLA and NIH-funded National Simulation Resource. Research interests include nonlinear stochastic systems, nonequilibrium statistical physics, and mathematical biology. He has pioneered work on mesoscopic thermodynamics of small systems and biochemical networks. His contributions span over 160 peer-reviewed articles, including books on chemical biophysics and stochastic reaction systems. Awards: APS Fellow (2010), Royalty Research Fund (2002-2003), multiple editorial roles in top journals. Grants: Over $5M in NIH/NSF funding for projects on metabolic networks, cardiac systems, and cell population dynamics. Teaching spans advanced courses in stochastic analysis, dynamical systems, and mathematical biology. Advised over 30 graduate students and postdocs, many now leading academic and industrial roles.

• Quantum Physics
• Communications Engineering
• Quantum Information
• +۳ مورد دیگر

Takaya Matsuura is a Visiting Research Fellow at RMIT University's School of Science in Australia. His research focuses on quantum physics and communications engineering, with particular emphasis on quantum information processing and quantum cryptography. Dr. Matsuura's research interests span several key areas: Quantum Error Correction and Fault-Tolerant Quantum Computation Continuous-Variable Quantum Systems Quantum Key Distribution and Quantum Cryptography Bosonic Quantum Codes Optical Quantum Computing Quantum Information Security His recent publications demonstrate a strong focus on practical implementations of quantum information processing, particularly in developing more efficient quantum error correction schemes and improving quantum communication protocols. His work bridges theoretical quantum physics with practical applications in quantum computing and cryptography, showing particular expertise in concatenated coding schemes and continuous-variable systems. Dr. Matsuura has published several significant papers in 2023 in high-impact journals including Physical Review Letters, Physical Review A, and Quantum, with his research already accumulating citations in the quantum information science community.

Jaron Skovsted Gundersenمشاهده پروفایل

عضو هیئت علمی

• Privacy-Preserving Computation
• Secure Multi-Party Computation
• Federated Learning
• +۱۵ مورد دیگر

Jaron Skovsted Gundersen is a Research Assistant at the Department of Electronic Systems, within The Technical Faculty of IT and Design at Aalborg University, Denmark. He is actively involved in the Automation & Control group and the Learning and Decisions Lab, focusing on privacy-preserving distributed systems, quantum coding, and decentralized control for infrastructure resilience. His research centers on advanced topics in secure computation and machine learning, including privacy-preserving distributed consensus , secure multi-party computation using Shamir secret sharing , federated learning , and quantum stabilizer codes . His work integrates theoretical foundations with practical applications in critical systems such as water and power distribution networks. The trend in his publications shows a strong emphasis on data privacy in distributed machine learning , leveraging techniques like subspace perturbation and differential quantization. His recent articles span high-impact journals such as IEEE Transactions on Information Forensics and Security and IEEE Journal on Selected Areas in Information Theory, reflecting contributions to both theoretical and applied aspects of information security and control systems. He has been a project participant in the SWIFT research initiative (2019–2024), which investigates decentralized control solutions for electric and water distribution systems. His activities include multiple conference presentations, participation in academic workshops, and public engagement through events like the PDJF Grundfos Prize 'The Stars of Tomorrow' EXPO. He also delivered a lecture on technological solutions in water technology at a national climate meeting in 2022. PhD graduate (March 2021) Active researcher in privacy-preserving machine learning and quantum coding Contributor to resilient infrastructure control systems Regular participant in international conferences and workshops Gundersen is affiliated with the Learning and Decisions Lab at Aalborg University, where he collaborates on cutting-edge research in distributed intelligence, secure computation, and adaptive control systems. The lab fosters interdisciplinary work combining control theory, information theory, and machine learning for real-world applications.

Pekka Parviainenمشاهده پروفایل

دانشیار

• Machine Learning
• Bayesian Networks
• Graphical Models
• +۷ مورد دیگر

Pekka Parviainen is an Associate Professor in the Department of Informatics at the University of Bergen, within the Faculty of Mathematics and Natural Sciences. His research spans machine learning, probabilistic modeling, and AI theory, with a focus on Bayesian and Markov networks, adversarial robustness, fairness, and energy forecasting. He is affiliated with the Center for Data Science (CEDAS), an active research center at the university. His research interests include: Structure learning in graphical models Probabilistic forecasting using graph neural networks Adversarial robustness and defense mechanisms Fairness in clustering and machine learning Optimization and approximation in learning algorithms Applications in renewable energy and quantum sensing His recent publications (2020–2025) reflect a strong theoretical grounding combined with real-world applications, particularly in energy systems and AI safety. The works trend toward scalable and interpretable models, with increasing focus on fairness and robustness. Key themes include Bayesian network learning, metric learning, and causal graph modeling. Scientific contributions include: Development of novel adversaries (e.g., Voronoi-epsilon) for measuring robustness Scalable algorithms for learning large DAGs and Bayesian networks Integration of continuous optimization with combinatorial heuristics Applications in electricity demand forecasting and gas sensing Parviainen advises PhD students, including Hyeongji Kim (2023 thesis on distance in machine learning), and collaborates extensively with researchers in Norway and internationally. He has received computational support via Sigma2 (NN9884K) and is part of the CEDAS project, which fosters interdisciplinary data science research. While no specific grants are detailed, his involvement in funded projects and high-impact publications indicates active grant engagement. He is associated with the Center for Data Science (CEDAS), where he contributes to advancing data-driven methodologies across domains. The team emphasizes scalable, robust, and fair AI systems, aligning with national and international research priorities in trustworthy machine learning.

Feliks Nüskeمشاهده پروفایل

استاد پژوهشی

• Data-driven modeling
• Molecular simulation
• Koopman operator theory
• +۶ مورد دیگر

Dr. Feliks Nüske is a Max Planck Group Leader at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, leading the Data-driven Modeling of Complex Physical Systems research group. He also holds a position as Guest Professor at Freie Universität Berlin (2023-2024). His research bridges applied mathematics, data science, and molecular simulation to develop novel algorithms for understanding complex physical systems at the molecular level. Dr. Nüske's educational background includes: Ph.D. in Mathematics from Freie Universität Berlin (2012-2017) Postdoctoral research at Universität Paderborn (2019-2022) and Rice University (2017-2019) His research focuses on developing data-driven methods that combine physical insights with machine learning to extract meaningful information from molecular simulation data. Key areas include Koopman operator theory for analyzing nonlinear dynamical systems, dimensionality reduction techniques, tensor methods for efficient computation, and kinetically consistent coarse-graining approaches. His work enables more efficient modeling of complex molecular processes that would otherwise be computationally prohibitive. Dr. Nüske's publication record shows a consistent trajectory of advancing both the theoretical foundations and practical applications of data-driven modeling in molecular science. His recent work emphasizes error analysis for data-driven models, control of stochastic systems, tensor-based dimensionality reduction, and methods to preserve kinetic properties in coarse-grained models. These contributions address critical challenges in scaling molecular simulations to biologically relevant timescales and system sizes. Dr. Nüske actively collaborates with researchers worldwide and has established partnerships with leading institutions including Freie Universität Berlin, Rice University, and TU Ilmenau. His collaborative network spans multiple disciplines, connecting mathematicians, chemists, and computational scientists. Dr. Nüske advises several Ph.D. students at the Max Planck Institute, including Vahid Nateghi, Lei Guo, Minakshi Verma, and Hauke Sprink. He has organized workshops on Uncertainty Quantification for molecular systems and regularly presents at major international conferences including SIAM MS, MTNS, and IMSI workshops. His research group continues to push the boundaries of what's possible in computational molecular science through innovative mathematical approaches.