جستجوی استاد راهنمای دانشگاهی

Christos Faloutsos is the Fredkin Professor of Computer Science at Carnegie Mellon University, with a courtesy appointment in Electrical and Computer Engineering. He holds a B.Sc. from the National Technical University of Athens and M.Sc./Ph.D. from the University of Toronto. His research focuses on data mining, graph analysis, fractals, and database systems. Notable contributions include foundational work on R-trees, graph mining laws (e.g., Kronecker graphs), and applications in medical imaging, network security, and fraud detection. Key projects include PEGASUS (petascale graph mining), fraud detection in online auctions (NetProbe), and tools for human trafficking analysis (TrafficVis). He has led NSF-funded projects on tensor mining, network anomaly detection, and bioinformatics. Over 300 refereed publications highlight his contributions across databases, data mining, and networks. Awards include the KDD Best Paper (2005, 2016), SIGMOD Test-of-Time Award, and recognition as a top nurturer in IT. His lab collaborations span the Parallel Data Lab (PDL), Machine Learning Department, and Computational Biology.

• Data Mining
• Graph Mining
• Fractals and Power Laws
• +۳ مورد دیگر

Marco Paggi is a Full Professor of Structural Mechanics at the IMT School for Advanced Studies Lucca, Italy, since 2017. He previously held academic roles at Politecnico di Torino (Assistant Professor, 2007-2013) and has been an Alexander von Humboldt Fellow at Leibniz University Hannover. His research focuses on fracture mechanics, contact mechanics, and computational methods applied to renewable energy systems, composite materials, and multi-scale modeling. Key Themes: Fracture propagation, contact interfaces, phase field modeling, photovoltaic durability, and material heterogeneity. Awards: Stanford Top 2% Scientists (2020-2024) Research.com Top Scientists (2022-2024) European Structural Integrity Society Young Scientist Award (2010) Publications: His work spans tribology, computational fracture mechanics, and material degradation, with recent emphasis on phase field modeling for quasi-brittle materials and photovoltaic systems. He has pioneered methods for multi-scale and multi-physics analysis of structural systems. Mentorship: Supervised 17 PhD graduates and 14 postdocs, including award-winning researchers like Pietro Lenarda and Zeng Liu.

• Fracture mechanics
• Contact mechanics
• Computational methods for nonlinear partial differential equations
• +۱۵ مورد دیگر

Giulio Cimini is Associate Professor of Theoretical Physics in the Department of Physics at the University of Rome Tor Vergata and a Research Associate at the 'Enrico Fermi' Research Center. He is a statistical physicist with a strong interdisciplinary focus on complex networks and their applications in socio-economic systems. His research interests include: Statistical Physics of Complex Networks Reconstruction and Validation of Economic Networks Social Network Interactions and Financial Markets Systemic Risk and Financial Contagion Scientific Success, Fitness, and Complexity Adaptive Social Recommendation Codon Usage Bias and Protein Interaction Networks His recent publications reveal a strong trend in applying statistical physics to real-world networks, particularly in finance and social systems. Key themes include the modeling of systemic risk in supply chains and financial networks, the dynamics of collective action on platforms like Reddit (e.g., the GameStop short squeeze), and the development of network reconstruction methods using maximum entropy and optimal transport frameworks. His work often combines empirical analysis with theoretical modeling. Scientific awards and recognitions include: Associate Editor, Frontiers in Physics – Interdisciplinary Physics Board Member, Network Science Society Member, Council of the Complex Systems Society Steering Committee, CCS/Italy He has advised or collaborated with numerous researchers, particularly in projects related to economic networks and complex systems. His work has been supported by Italian national grants such as PRIN and PNRR. He leads or co-leads research projects including RENet and C2T. His research is conducted within interdisciplinary teams involving physicists, economists, and computer scientists, often in collaboration with institutions like ISC-CNR, IMT Lucca, and the Network Science community.

• Statistical Physics
• Complex Networks
• Economic Networks
• +۱۲ مورد دیگر

Roland Ketzmerick is a Professor of Computational Physics at Technische Universität Dresden since 2002, with a Max Planck Fellow position at the Max Planck Institute for the Physics of Complex Systems (2010–2020). He was spokesperson for the DFG Forschergruppe FOR760 on Scattering Systems with Complex Dynamics (2010–2013). His research focuses on quantum chaos in mixed systems, power-law trapping in Hamiltonian systems, Floquet systems , Hamiltonian ratchets , mesoscopic physics , fractal spectra , and Bloch electrons in magnetic fields . His work bridges classical and quantum dynamics, exploring tunneling, wavefunction statistics, and nonequilibrium phenomena. His publications demonstrate a strong emphasis on chaotic resonance states , dynamical tunneling , multifractal analysis , and quantum transport in complex systems. Recent articles (2022–2025) address dielectric cavities, ultracold atom entanglement, and 4D Hamiltonian structures. Scientific Awards : Otto-Klung-Prize (1999)

• Quantum Chaos
• Hamiltonian Systems
• Floquet Systems
• +۳ مورد دیگر

James Dixon is a Professor and Director of Ecological Psychology at the University of Connecticut, where he leads the Department of Psychological Sciences and directs the Center for the Ecological Study of Perception & Action (CESPA). CESPA fosters interdisciplinary research across optics, acoustics, movement science, and nonlinear dynamics, establishing UConn as a pioneer in ecological psychology. Research Focus Dr. Dixon investigates the self-organizing principles underlying perception, action, and cognition, with emphasis on thermodynamic foundations of behavior. His work bridges psychology, physics, and complex systems theory: Self-organization in biological and non-living dissipative systems Fractal dynamics in cognitive processes Inter-entity coordination across scales End-directed evolution in complex systems Publication Trends His publications (2009-2016) converge on emergent phenomena in complex systems, with recurring themes of self-organization, entropy, and coordination dynamics. Recent work emphasizes thermodynamic principles in behavioral emergence, while earlier studies explore representational change and insight through nonlinear models. Leadership & Academic Environment As CESPA Director, he oversees collaborative research spanning 10+ specialties. The center’s ethos integrates ecological principles with physics and development, maintaining UConn’s legacy in perception-action science since its founding by J.J. Gibson.

• Self-organization in perception, action, and cognition
• Thermodynamic origins of behavior
• Complex behavior in non-living dissipative systems
• +۱ مورد دیگر

Maria Christina Mariani is a Professor and Department Chair in the Department of Mathematical Sciences at the University of Texas at El Paso (UTEP). Her interdisciplinary research bridges mathematics with applications in public health, geophysics, physics, and finance, with a focus on developing novel mathematical models for complex data analysis. Dr. Mariani earned her Ph.D. in Mathematics from the University of Buenos Aires in 1992, where she received an Outstanding dissertation award. She also holds an M.S. in Physics (1996) and an M.S. in Mathematics (1987), both from the University of Buenos Aires with highest honors. Her research interests span Applied Mathematics, Nonlinear partial differential equations, Stochastic differential equations, Machine Learning techniques, Mathematical Finance, Mathematical Physics, and Numerical Methods. She has developed mathematical models for medical data analysis (particularly breast cancer, heart disease, and prostate cancer), seismic and explosive data, and financial markets. Her work emphasizes the development of mathematical models to enhance understanding of medical data and extreme events in various phenomena. Dr. Mariani's recent research focuses on applying machine learning and stochastic models to complex data sets across multiple domains. Her work demonstrates consistent innovation in developing novel algorithms for medical diagnosis and prognosis, analyzing seismic data, and modeling financial markets using Levy processes, Ornstein-Uhlenbeck models, and wavelet techniques. She has mentored numerous students throughout her career, including PhD candidates, MS students, and post-doctoral researchers, demonstrating her commitment to academic development and knowledge transfer. Dr. Mariani has served as Department Chair and holds the Shigeko K. Chan Distinguished Professor title in Mathematical Sciences, reflecting her significant contributions to the field and institution.

• Applied Mathematics
• Nonlinear partial differential equations
• Stochastic differential equations
• +۵ مورد دیگر

Henrik Jeldtoft Jensen is a Professor of Mathematical Physics and leads the Centre for Complexity Science at Imperial College London. His work spans multiple disciplines, focusing on the statistical mechanics of complex systems, with applications in physics, biology, neuroscience, and finance. Professor, Mathematical Physics Leader, Centre for Complexity Science Institution: Imperial College London His research interests lie at the intersection of theoretical physics and complex systems. He is best known for developing the Tangled Nature Model of evolving ecosystems, which has been extended into financial modeling through the Tangled Finance approach. His work in brain dynamics involves analyzing fMRI and EEG data using tools from statistical physics. He has made significant contributions to self-organized criticality and stochastic dynamics of complex systems, particularly in condensed matter and evolutionary contexts. The recent publications reflect a strong trend toward interdisciplinary complexity science, integrating concepts from physics, biology, economics, and neuroscience. Keywords across these works include complexity, statistical mechanics, dynamical systems, and network theory, with subfields ranging from neural avalanches to financial instability and biodiversity modeling. Henrik Jensen is the author of two influential books: Self-Organized Criticality and Stochastic Dynamics of Complex Systems (with Paolo Sibani), which have been widely cited across disciplines. He has supervised numerous PhD and postdoctoral researchers through the Centre for Complexity Science, though specific names are not listed. His research has been supported by grants from UK research councils and international collaborations, particularly in interdisciplinary complexity projects. He is affiliated with the Centre for Complexity Science, a multidisciplinary research hub at Imperial College London that brings together physicists, mathematicians, biologists, and social scientists to study complex adaptive systems.

• Complexity Science
• Statistical Mechanics
• Mathematical Physics
• +۷ مورد دیگر

Olav Eklund is a Professor at Åbo Akademi University's Faculty of Natural Sciences and Engineering , Department of Geology and Mineralogy Technologies. His work focuses on geological processes in the Fennoscandian Shield, particularly magmatism, petrology, and mineral resource exploration. Research Areas : Magmatism, Migmatite Formation, Leucogranite Petrology, Graphite Ore Exploration, Post-orogenic Tectonics, Geochronology Projects : FennoFlakes (2015-2020) - Identification of flake-graphite ores and graphene applications Collaborations : Active in international geological research networks, with recent collaborations on Paleoproterozoic magmatism in Finland His research aligns with UN Sustainable Development Goals, particularly in sustainable mineral resource utilization. Publications emphasize geochemical analysis, zircon dating, and metamorphic processes in Finland's bedrock formations.

• Geology
• Mineralogy
• Sustainable Development
• +۵ مورد دیگر

Georgi S. Medvedev is a Professor in the Department of Mathematics at Drexel University. He earned his PhD from Boston University (1999) and was a Veblen Research Instructor at Princeton University and the Institute for Advanced Study before joining Drexel in 2002. His research investigates dynamical systems, stochastic analysis, and mathematical neuroscience. Research develops mathematical frameworks for understanding complex network dynamics. Primary areas include synchronization in coupled oscillator systems, metastability in stochastic networks, and continuum limits of large-scale dynamical systems. Applications span neuroscience, statistical physics, and engineering. Recent publications focus on the Kuramoto model, exploring bifurcations in networked oscillators, stability of twisted states, and continuum approximations for sparse graphs. The work bridges discrete network models with continuum descriptions using graph limit theory. He has developed interdisciplinary courses including Mathematical Neuroscience and Dynamical Networks. His research is supported by multiple NSF grants focusing on network metastability, mean-field analysis, and synchronization phenomena. Service includes editorial roles for Discrete and Continuous Dynamical Systems and Networks and Heterogeneous Media. He mentors undergraduate researchers in projects investigating metastability in oscillator networks.

• Dynamical Systems
• Stochastic Analysis
• Mathematical Neuroscience
• +۳ مورد دیگر

Professor Peter Grassberger is a distinguished researcher at the Jülich Supercomputing Centre (JSC) within the Jülich Research Centre, one of Germany's leading national research institutions. His work spans multiple decades in theoretical physics and computational science, with a particular focus on complex systems and statistical mechanics. His research has significantly advanced our understanding of critical phenomena and phase transitions in various physical systems. Grassberger's research interests center around statistical physics and complex systems, with specializations in percolation theory, self-organized criticality, and random walk models. His work explores the universal properties of phase transitions, critical phenomena, and the behavior of complex networks. His theoretical contributions have provided fundamental insights into how simple local rules can lead to complex global behavior in physical systems. His recent work continues to push boundaries in understanding extreme-value statistics, entropy estimation methods, and the dynamics of interface models. Through his extensive publication record spanning over 40 years, Grassberger has established himself as a leading authority in computational statistical physics. His work shows consistent focus on understanding universal properties of critical systems while developing innovative computational methods to analyze complex phenomena. His research bridges theoretical physics with practical computational approaches, making significant contributions to both fundamental understanding and methodological development in the field. Grassberger's scientific impact is evident through his numerous influential publications and his development of important computational techniques like the Grassberger-Procaccia algorithm for estimating fractal dimensions. His work on self-organized criticality, particularly his 2022 review "Self-Organized Criticality, Three Decades Later," demonstrates his enduring contribution to this important field. His recent publications continue to explore cutting-edge questions in statistical physics, showing active engagement with contemporary research challenges.

• Statistical Physics
• Complex Systems
• Percolation Theory
• +۷ مورد دیگر

Dr. Tomasz J. Kozubowski is a Professor in the Department of Mathematics and Statistics at the University of Nevada, Reno. He holds a Ph.D. in Statistics and Applied Probability from the University of California, Santa Barbara, and an M.S. in Statistics from the University of Texas, El Paso. His research focuses on stochastic modeling of natural phenomena across climate science, geosciences, finance, and economics. Key research areas include distribution theory (particularly Laplace and heavy-tailed distributions), limit theory, mathematical statistics, financial mathematics, and stochastic models for hydro-climatic events. He has authored/co-authored over 120 publications, including two monographs, and serves on editorial boards of multiple journals. In 2016, he received the Sentinel of Science Award from Publons for peer review contributions. Education: M.S. in Statistics, University of Texas, El Paso Ph.D. in Statistics and Applied Probability, University of California, Santa Barbara His work emphasizes interdisciplinary applications, such as modeling extreme weather events, financial risk, and environmental variability. Publications span journals like Annals of the Institute of Statistical Mathematics , Scandinavian Journal of Statistics , and Journal of Computational and Applied Mathematics . He is actively involved in academic service, including editorial roles and peer review for over 100 journals. Research tools include advanced statistical methodologies and computational frameworks for high-dimensional data analysis.

• Stochastic Modeling
• Distribution Theory
• Laplace Distribution
• +۷ مورد دیگر

Robert Dalang is a Full Professor and Chair of Probabilities at École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. He is affiliated with the School of Basic Sciences, Department of Mathematics, specifically the Probability Section. His office is located in building MA, room B2 493 at EPFL's Lausanne campus. He also serves as a Full Professor in the Section of Mathematics (SMA) and for the Doctoral Program in Mathematics (EDMA). Professor Dalang's research focuses on probability theory and stochastic analysis. His work primarily centers on: Stochastic partial differential equations (SPDEs), particularly stochastic heat and wave equations Brownian motion and Brownian sheet Lévy processes and Lévy white noise Hitting probabilities and polarity Fractal properties of random fields Stochastic optimization problems His recent publications demonstrate a continued focus on the theoretical properties of solutions to stochastic partial differential equations, including their regularity, hitting probabilities, and asymptotic behavior. He has made significant contributions to understanding the fine properties of solutions to stochastic heat and wave equations, particularly in critical dimensions. Professor Dalang has served on the elected committee for the Pension fund PUBLICA since Fall 2007, being reelected for 2009-2012. His work on this committee has focused on preserving employee interests during the transition from a defined benefits system to a defined contributions system. He has supervised numerous PhD students, including: Candil David Jean-Michel Chen Le Ciccarella Carlo Conus Daniel Dumas Frédéric Humeau Thomas Marie Jean-Baptiste Pu Fei Rossel Jean-Benoît Vinckenbosch Laura Professor Dalang teaches courses including Analysis III, Analysis IV, and Theory of Stochastic Calculus at EPFL.

• Probability Theory
• Stochastic Processes
• Stochastic Partial Differential Equations
• +۳ مورد دیگر

Sanja Aleksic is an Associate Professor at the Faculty of Electronic Engineering, University of Nis, specializing in Microelectronics and Microsystems. Her academic career began with a Physics degree from the Faculty of Philosophy in Nis (1995), followed by a Master's (2009) and PhD (2015) in Applied Physics from her current faculty. Her research focuses on semiconductor materials, photoacoustic spectroscopy, and electronic device modeling. She has published extensively in peer-reviewed journals, with 9 papers indexed with impact factors. Her work bridges applied physics and engineering, particularly in analyzing thermal and elastic properties of materials using advanced techniques like photoacoustic analysis and neural network modeling. Education: Bachelor's in Physics, Faculty of Philosophy, University of Nis (1995) Master's in Applied Physics, Faculty of Electronic Engineering, University of Nis (2009) PhD in Applied Physics, Faculty of Electronic Engineering, University of Nis (2015) Research Interests: Microelectronics, semiconductor characterization, thermoelastic effects, photoacoustic signal analysis, and material property modeling. Notably, her work employs electro-acoustic analogies to study silicon and TiO₂-coated materials, as well as neural network approaches for high electric field stress modeling in VDMOSFETs. Her recent studies (2020–2025) emphasize cutting-edge topics like solar parking canopy optimization and biomarker-based clinical outcomes in pandemic scenarios. Publications: Over 30 peer-reviewed articles, with a focus on photoacoustic techniques, semiconductor device simulation, and energy systems. Her work spans journals like Journal of Applied Physics , International Journal of Thermophysics , and Journal of Computational Electronics . Key themes include material property extraction, thermal-mechanical coupling, and sustainable energy solutions. Awards: None explicitly listed in provided texts. Labs/Teams: Engaged in interdisciplinary research at the Faculty of Electronic Engineering, collaborating on projects involving material characterization, renewable energy systems, and bio-medical applications. Active in both national and international research networks, though specific lab affiliations are not detailed here.

• Microelectronics
• Semiconductor Physics
• Applied Physics
• +۳ مورد دیگر

Olivier White is a Professor at the University of Burgundy's Faculty of Sports Science (UFR STAPS), where he maintains his laboratory at Espace Marey. With extensive teaching experience across engineering and neuroscience disciplines, he supervises MSc and PhD students while leading a multidisciplinary research program focused on motor control mechanisms under normal and altered gravity conditions. His educational background spans civil engineering and neuroscience, with a BSc (1997), MSc in Computer Science (2000, summa cum laude), DEA in Applied Mathematics (2002), and PhD in Neuroscience and Applied Mathematics (2007), all from Louvain School of Engineering, Belgium. He completed his Habilitation in 2016 with research titled 'From basic motor control to applications' and earned French Qualification for the Neuroscience Section in 2020. White's research investigates how the brain controls diverse actions through innovative approaches including 3D virtual reality, haptic devices, and gravitational manipulation via parabolic flights and centrifuges. His work addresses fundamental questions about sensory information in learning, motor skill generalization, and strategy selection. He employs motion capture, force measurements, electromyography, fMRI, and mathematical modeling approaches including optimal control and fractal analyses. His publication record reveals a consistent focus on gravity-related motor adaptation, with recent work exploring sensorimotor control in inverted postures, resonance phenomena in rhythmic movements, and spaceflight effects on operational performance. His research bridges theoretical physics with practical neuroscience applications, particularly in space physiology and rehabilitation contexts. Dr. White maintains an active teaching portfolio across multiple institutions including University of Burgundy, King's College London, and ESTP Engineering School. His courses range from basic computer science to advanced topics in computational motor control, space physiology, and deep learning applications. Motor control and learning mechanisms Altered gravity effects on human movement Virtual reality and haptic applications Fractal analysis of movement patterns Space physiology and neurorehabilitation Mathematical modeling of motor control He actively supervises research projects at undergraduate and graduate levels, building a laboratory that combines behavioral, neuroimaging, and mathematical methods to understand movement planning and execution. Through international collaborations, particularly in space-related research, he develops applications with societal benefits in rehabilitation and human performance enhancement.

• Motor control and learning
• object manipulation and dexterity
• upper limb movements
• +۱۲ مورد دیگر

Kartik Iyer is an Assistant Professor jointly appointed in the Department of Physics and Department of Mechanical and Aerospace Engineering at Michigan Tech. He earned his PhD in Aeronautics from the Georgia Institute of Technology, followed by postdoctoral appointments at the University of Rome and New York University. Research focuses on Atmospheric Physics, Turbulence, Thermal Convection, and Numerical Simulations. Director of the Iyer Research Lab , specializing in supercomputing and turbulent flow analysis. His scientific work spans turbulence theory, scalar transport, and computational methods, with over 15 recent publications in top-tier journals. Key areas include the Zeroth Law of Turbulence, circulation statistics, bifractal scaling, and subgrid-scale modeling. Despite his focus on high-performance computing, no specific awards or honors are mentioned in the provided data. Dr. Iyer teaches courses related to atmospheric physics and heat transfer, emphasizing interdisciplinary approaches between physics and engineering disciplines.

• Atmospheric Physics
• Turbulence
• Thermal Convection
• +۴ مورد دیگر