جستجوی استاد راهنمای دانشگاهی

برای مسیر پژوهشی‌تان، استاد راهنما، استاد دانشگاه و پژوهشگر مناسب را پیدا کنید و با آن‌ها ارتباط بگیرید.

نمایش ۷۲۱-۷۳۵ از ۳٬۰۳۱ استاد راهنما

اطلاعات پروفایل‌ها از صفحات عمومی دانشگاه‌ها گرفته شده و ممکن است به‌روز نباشد.

Lingfei Wuمشاهده پروفایل

استادیار

University of PittsburghUnited States

Lingfei Wu is an Assistant Professor of Information Science at the University of Pittsburgh's School of Computing and Information, specializing in computational social science. His work focuses on understanding how science and technology advance through collaborative dynamics, particularly the roles of team size and composition. He holds a Ph.D. from City University of Hong Kong. Research interests include the Science of Science, team science, and innovation studies, leveraging big data, complexity sciences, and AI. His groundbreaking studies on team dynamics in Nature and PNAS reveal that small teams drive disruptive ideas while large teams consolidate existing knowledge. He advises organizations like Novo Nordisk Fonden and the John Templeton Foundation on data-driven teamwork evaluation. Education: Ph.D., City University of Hong Kong Awards: NSF Career Award, Richard King Mellon Award, Oxford Martin School Fellowship His work bridges research, education, and industry through analyses of skill gaps in the data economy, emphasizing soft skills' growing importance. Active in Knowledge Lab at the University of Chicago and affiliated with Swarma Club and Northwestern Institute on Complex Systems (NICO).

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Einar Iversenمشاهده پروفایل

استاد

University of BergenNorway

Einar Iversen is a Professor at the Department of Earth Science, University of Bergen (UiB), affiliated with the Geophysics research group. His work focuses on advanced computational methods in geophysics, including seismic modeling, wave propagation in anisotropic media, and dynamic ray tracing. He has contributed to developments in numerical simulation techniques for multiphysics processes in porous media and higher-order Hamilton-Jacobi perturbation theories. Research interests emphasize applications of mathematical physics to geophysical problems, such as full-waveform inversion, traveltime extrapolation, and geometrical spreading analysis. His studies often involve collaborations with institutions like NTNU, Rice University, and international researchers in seismology and applied mathematics. Key contributions include advancing ray-centred coordinate systems for dynamic ray tracing, improving finite-difference modeling accuracy in discontinuous media, and reconstructing metrics from boundary diffraction data. His work bridges theoretical developments with practical seismic data processing techniques, contributing to reservoir simulation and imaging technologies. Funding includes grants from the Research Council of Norway (e.g., projects 294404, 267769). His research outputs span journals like Geophysical Journal International , Computer Methods in Applied Mechanics and Engineering , and Geophysical Prospecting , reflecting a strong focus on computational and theoretical geophysics.

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Brian Enquistمشاهده پروفایل

استاد

University of ArizonaUnited States

Brian Enquist is a Professor in the Department of Ecology and Evolutionary Biology at the University of Arizona. He has held academic ranks from Assistant (2001-2005) to Associate (2005-2009) before becoming full Professor in 2009. He earned his Ph.D. in Biology from the University of New Mexico (1998), preceded by an M.S. (1995) and B.A. (1991) in Biology. His research focuses on integrating plant physiology, biophysics, and ecology to understand how individual-level traits influence ecosystem processes. Notable honors include the NSF CAREER Award, ESA Mercer Award, and a Fulbright Fellowship in Costa Rica (1995-1996). Research interests include scaling laws in biology, plant allometry, community ecology, and tropical forest dynamics. His lab studies functional diversity, biomass allocation patterns, and climate-vegetation interactions, with long-term fieldwork in Costa Rica’s Guanacaste Conservation Area. Recent work addresses global drought patterns, biodiversity threats from mining, and the impacts of warming on mountain ecosystems. Key contributions include foundational theories on metabolic scaling, plant vascular architecture, and ecosystem gas flux modeling. He collaborates on large-scale projects like the National Ecological Observatory Network (NEON) and the Global Future Droughts Initiative. His work bridges theoretical frameworks with applied conservation, emphasizing data integration across scales. Awards: NSF CAREER Award, ESA Mercer Award, Fulbright Fellowship. Active in interdisciplinary research initiatives such as the Biodiversity Forecasting Initiative (BioFI) and the East River Watershed study. His research outputs span >200 peer-reviewed articles, including landmark papers in Science , Nature , and Proceedings of the National Academy of Sciences .

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Marcel Ortgieseمشاهده پروفایل

دانشیار

University of BathUnited Kingdom

Marcel Ortgiese is a Reader in the Department of Mathematical Sciences at the University of Bath, affiliated with the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa) and the Probability Laboratory at Bath. His research focuses on probability theory, including spatial population models, stochastic processes in random environments, and evolving random graphs. He investigates large-scale behaviors of interfaces in evolutionary biology contexts, branching processes in inhomogeneous environments, and dynamic processes on random graph structures. His work integrates theoretical analysis with applications to real-world systems, emphasizing interdisciplinary connections between probability and complex networks. Current projects include studying the interplay between geometry and randomness in fitness landscapes for expanding populations (EPSRC-funded) and advancing methods for cumulants and superconcentration phenomena. Ortgiese has contributed to foundational research on contact processes, voter models, preferential attachment networks, and symbiotic branching systems. His recent studies explore adaptive network dynamics, subcritical random graph properties, and asymptotic behaviors in weighted recursive trees. He holds a PhD from the University of Bath (2009) under Prof. Peter Morters and has supervised numerous graduate students through SAMBa's training programs. His academic contributions are reflected in over 20 peer-reviewed articles in top journals such as Stochastic Processes and their Applications and Annals of Applied Probability . Research themes consistently emphasize stochastic analysis of complex systems, with applications ranging from epidemiological modeling to evolutionary dynamics.

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Ed Brambleyمشاهده پروفایل

دانشگاهی

University of WarwickUnited Kingdom

Dr. Ed Brambley is a Reader at the University of Warwick specializing in aeroacoustics, computational methods, and industrial mathematics. His research combines theoretical fluid dynamics with applied industrial challenges, particularly in acoustic liner optimization for aerospace and mathematical modeling of metal forming processes. Recent work advances boundary layer acoustics, wave propagation algorithms, and rolling process simulations. Collaborations span aerospace engineering and manufacturing sectors.

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Colm Connaughtonمشاهده پروفایل

استاد

University of WarwickUnited Kingdom

Colm Connaughton is a Professor and Director of the Centre for Complexity Science at the University of Warwick's Mathematics Institute. His research focuses on non-equilibrium statistical mechanics, fluid dynamics, turbulence, nonlinear waves, and complexity science. He has contributed to interdisciplinary studies ranging from wave turbulence theory to applications in traffic modeling and machine learning. Connaughton co-organized the Warwick EPSRC Mathematics Symposium and has led workshops on topics like complex networks and nonlinear science. His work bridges theoretical physics and applied mathematics, with recent projects addressing reinforcement learning in traffic control systems and the social complexity of fictional narratives. Connaughton's research often involves collaborations across disciplines, including contributions to understanding epidemic spreading dynamics and the statistical mechanics of cluster aggregation. Notable contributions include the study of Rossby wave turbulence models, the dynamics of energy condensation in two-dimensional turbulence, and the application of kinetic theory to aggregation processes. His work frequently emphasizes the interplay between mathematical rigor and real-world applications, such as optimizing traffic flow prediction and analyzing network-based disease spread. Connaughton maintains active engagement in academic service, including editorial roles and organizing international conferences. His research has been published in high-impact journals across physics, mathematics, and engineering disciplines.

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Mingtao Xiaمشاهده پروفایل

مدرس

New York UniversityUnited States

Mingtao Xia is a Courant Instructor at the Courant Institute of Mathematical Sciences, New York University (2023–present). He holds a PhD in Applied Mathematics from UCLA (2019–2023) and a B.S. in Information and Computing Science from Peking University’s School of Mathematical Sciences (2015–2019). His research focuses on mathematical modeling, numerical methods, and machine learning applications in kinetic theories, stochastic systems, and unbounded-domain differential equations. He has contributed to interdisciplinary areas including biological systems, environmental science, and epidemic control through computational methods. Education: PhD in Applied Mathematics, UCLA, 2019–2023 B.S. in Information and Computing Science, Peking University, 2015–2019 His work integrates advanced numerical techniques like spectral methods and Wasserstein-distance frameworks with real-world problems such as gene regulation dynamics, solar wind analysis, and ozone pollution impacts. Recent publications emphasize efficient algorithms for high-dimensional systems and uncertainty quantification in stochastic models. While no awards are listed, his research demonstrates strong contributions to mathematical modeling across diverse domains. Advising and grant details are currently unavailable. His affiliation with the Courant Institute positions him at the forefront of computational mathematics and its applications in interdisciplinary research.

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Govinda Poudelمشاهده پروفایل

مدرس ارشد

Australian Catholic UniversityAustralia

Dr. Govinda Poudel is a Senior Lecturer at the Mary Mackillop Institute for Health Research, Australian Catholic University (ACU), Melbourne. He is an interdisciplinary academic with a strong background in computational neuroscience, artificial intelligence, and neuroimaging, focusing on brain health and neurological disorders. His research expertise lies at the intersection of AI and advanced neuroimaging (fMRI, EEG), where he develops computational models to understand brain network alterations in conditions such as Huntington's disease, traumatic brain injury, and sleep disorders. He has pioneered methods for mapping neurodegeneration spread and enhancing brain connectivity modeling through machine learning. PhD, University of Otago, New Zealand BE (First Class Honours), University of Technology Sydney (UTS) His research has led to over 85 peer-reviewed publications in high-impact journals and approximately AUD 0.5 million in research grants. The recent publications reflect a consistent focus on brain network modeling, neurodegeneration prediction, and multimodal neuroimaging, with increasing use of machine learning and graph theory in understanding brain dynamics. Dr. Poudel has been recognized with several scientific awards: Hereditary Disease Foundation USA Fellowship Endeavour Australia Research Fellowship ECR Fellow Publication Prize, Monash University Young Biomedical Engineer Award, Engineers Australia He is an active HDR Supervisor (Full accreditation) and has contributed to research grants from organizations including the Hereditary Disease Foundation, Monash University, and the Royal Society of New Zealand Marsden Fund. He has collaborated extensively with interdisciplinary teams across the University of Sydney, Monash University, and the New Zealand Brain Research Institute. Dr. Poudel is involved in editorial roles, currently serving on the editorial board of BMC Biomedical Engineering and previously for SLEEP (2014–2017). He is a senior member of IEEE and contributes to public engagement through the International Society for Magnetic Resonance in Medicine - ANZ.

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Laura Pollacciمشاهده پروفایل

پژوهشگر ارشد

National Research Council of Italy (CNR)Italy

Laura Pollacci is a postdoctoral researcher at the Knowledge Discovery and Data Mining Laboratory (KDDLab), a joint research group of the Information Science and Technology Institute of the National Research Council (CNR) in Pisa and the University of Pisa, where she holds a position as Research Fellow in the Department of Computer Science. Her educational background includes: Bachelor's Degree in Digital Humanities (2014) from University of Pisa with 110/110 cum laude Master's Degree in Digital Humanities (2015) from University of Pisa with 110/110 cum laude PhD in Computer Science (2019) from University of Pisa with thesis on 'conjunct usage of Big Data and Sentiment Analysis for the study of Human Migration' Pollacci's research focuses on Social Network Analysis and Visual Analytics for Social Mining, Human Migration, and Sentiment Analysis. Her work bridges computational methods with social science questions, particularly examining how digital traces can reveal patterns in human behavior, migration, and emotional expression across social platforms. She has developed expertise in analyzing complex social networks, music diversity, and political polarization through data-driven approaches. Her publication record shows a clear trajectory from computational linguistics and sentiment analysis toward broader applications in social network analysis, migration studies, and musicology. Early work focused on emotive lexicon development and sentiment polarity classification for Italian language, while more recent publications examine political polarization on Reddit, human migration patterns through big data, and the fractal dimensions of music diversity. Pollacci is actively involved with the HumMingBird project, which focuses on 'Enhanced migration measures from a multidimensional perspective.' Her work at KDDLab places her at the intersection of data science and social research, contributing to the laboratory's mission of developing theory, techniques and systems for extracting knowledge from large data sets.

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Laurent Clavierمشاهده پروفایل

استاد

Mines-Telecom InstituteFrance

Laurent Clavier is a Professor at IMT Lille Douai (now IMT Nord Europe), affiliated with the Institut Mines-Télécom and conducting research within the CNRS laboratories IEMN (UMR 8520) and IRCICA (USR 3380). His work centers on digital communications and the physical layer of wireless networks for IoT applications, especially in energy-autonomous and ultra-dense environments. His research focuses on interference modeling in wireless networks, particularly under non-Gaussian and heavy-tailed conditions such as those found in IoT scenarios. He investigates the impact of interference in LoRa-like and SCMA-based networks, with a strong emphasis on statistical modeling, channel access mechanisms, and capacity analysis under α-stable noise. The recent publications highlight a consistent trend in analyzing and modeling real-world interference in low-power, large-scale wireless systems. Key themes include LoRa network optimization, unsupervised signal detection, multiuser access, and theoretical limits in non-Gaussian channels—indicating a deep integration of information theory, signal processing, and practical IoT deployment challenges. Scientific Awards: No scientific awards mentioned in the provided text. Laurent Clavier is actively involved in research projects such as ALPAGA and CASTREAU, contributing to advancements in resilient communication systems and drone-based technologies. While no formal list of advisees is provided, his HDR degree and professorial status suggest supervision of doctoral candidates. He has contributed to book chapters and high-impact journals, reflecting sustained research productivity. He is associated with research teams focusing on multi-robot systems and disaster-resilient communication frameworks, as evidenced by his participation in the Robot-IA events and comments on resilient systems. His work bridges theoretical communication models with practical IoT implementations.

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Tak Shing Chanمشاهده پروفایل

پژوهشگر

University of OsloNorway

Tak Shing Chan is a researcher in the Mechanics research group at the Department of Mathematics, University of Oslo. His work focuses on wetting dynamics, droplet behavior, capillarity, and micro-nano fluidics, with applications in soft matter physics and biophysics. He employs analytical and numerical methods to study phenomena such as viscoelastic perturbations, elastocapillary effects, and interfacial instabilities. His research contributes to understanding adhesive mechanisms in biological systems and optimizing fluidic systems in engineering contexts. Key projects include the Dynamic wetting on soft solids (DyWeSS) initiative. His publications span topics like capillary bridges, film deposition, and the physics of adhesive organs in animals. Collaborations with institutions like the Norwegian Geotechnical Institute and international universities highlight his interdisciplinary approach. His work bridges fundamental fluid mechanics with applied problems in materials science and biophysics.

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Christina Kuttlerمشاهده پروفایل

استاد

Technical University of MunichGermany

Prof. Christina Kuttler holds the position of Professor in the Department of Mathematics at the Technical University of Munich (TUM), within the TUM School of Computation, Information and Technology. Her research focuses on biomathematics, particularly deterministic mathematical models of bacterial communication and diffusion processes, aiming to understand intracellular regulatory mechanisms. She has been at TUM since 2008, following postdoctoral work at the University of Tübingen and the Helmholtz Center Munich. Her academic background includes a doctorate in mathematics (2000) from the University of Tübingen, with further studies in physics and computer science. Awards include the Erwin Schrödinger Prize (2007) and the Tübingen Doctoral Prize (2000). Research interests span mathematical modeling in biology, with publications on quorum sensing, bacterial biofilms, and cancer dynamics. Notable works include models of immunotherapy effects on lung cancer and stochastic approaches in biological systems. She teaches courses such as Mathematical Modelling and Mathematics for Engineers, and collaborates on projects like modeling cerebral hemorrhage in premature infants. Her work bridges applied mathematics, computational biology, and interdisciplinary research.

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Jeff Hepinstall-Cymermanمشاهده پروفایل

استاد

University of GeorgiaUnited States

Dr. Jeff Hepinstall-Cymerman is a Professor of Landscape Ecology at the University of Georgia's Warnell School of Forestry and Natural Resources. His research focuses on spatial ecology, integrating geospatial technologies and ecological modeling to address coupled human-natural systems challenges. He leads the Spatial Lab, which explores land use change, climate impacts, and biodiversity conservation. Educated at Colgate University (BA), University of Minnesota (MS), and University of Maine (PhD), his work bridges academic research with practical conservation applications. Education: PhD in Forest Resources (2000, University of Maine), MS in Wildlife Ecology (1992, University of Minnesota), BA in Biology (1990, Colgate University) Research Specialties: Urbanization effects, forest management, wildlife population dynamics, GIS applications Key research interests include modeling landscape-scale ecological processes, urban expansion impacts, and policy-driven conservation strategies. His lab collaborates with planners to apply spatial data for sustainable resource management. Publications span topics like tornado damage patterns, bat population dynamics, and community vulnerability to climate change. Ongoing projects include studies on nuclear-affected wildlife, agave-pollinator interactions, and invasive species behavior. Dr. Hepinstall-Cymerman's work emphasizes interdisciplinary approaches, combining ecology with policy and technology to address global environmental challenges.

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Daewoo Leeمشاهده پروفایل

استاد

Ohio UniversityUnited States

Daewoo Lee is a Professor in the Department of Biological Sciences within the College of Arts and Sciences at Ohio University. His research is centered on molecular and cellular mechanisms underlying neurodegenerative diseases, particularly Parkinson's and Alzheimer's diseases. He is based in the Life Sciences Building on the Athens campus, where he leads a research laboratory focused on protein propagation, synaptic signaling, and neuroprotection. Research Interests: Dr. Lee's lab investigates the prion-like spread of pathogenic proteins such as alpha-Synuclein and tau, with a focus on how neuronal activity drives their release and propagation. His work integrates Drosophila models and human neural cell lines to study activity-dependent protein release, mitochondrial dysfunction, dopamine signaling, and olfactory learning. He employs advanced techniques including optogenetics and primary neuronal cultures to dissect molecular pathways involved in neurodegeneration and neuroprotection. The recent publications reflect a strong trend in understanding the cellular and molecular basis of Parkinson’s and Alzheimer’s diseases, with emphasis on protein aggregation, neurotransmitter signaling, and neuronal excitability. His research bridges model organisms and human disease mechanisms, offering translational insights. Scientific Mentoring: Dr. Lee actively mentors both graduate and undergraduate students, many of whom have co-authored publications from his lab. His teaching includes courses such as Drugs and the Brain , Principles of Physiology , and Biological Chemistry , reflecting his expertise in neurobiology and cellular biochemistry. Laboratory: The Lee Lab operates in Life Sciences Building 210J, utilizing Drosophila primary neuronal cultures, ReNcell human neural progenitor cells, and optogenetic tools to study neurodegenerative processes in a controlled and reproducible manner.

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Daniel Steinمشاهده پروفایل

استاد

New York UniversityUnited States

Daniel Stein is a Professor of Physics and Mathematics at New York University, holding an office in Warren Weaver Hall. His research focuses on theoretical condensed matter physics and statistical mechanics, particularly on disorder and randomness in systems such as magnetic materials and stochastic processes. Key interests include rare nucleation events and the dynamics of disordered systems. Dr. Stein earned his Ph.D. in Physics from Princeton University (1979), preceded by an M.S. from Princeton (1977) and a B.Sc. from Brown University (1975). His work bridges fundamental physics with interdisciplinary applications, including studies on spin glasses, phase transitions, and emergent phenomena in complex systems. Recent research trends in his publications emphasize spin glass dynamics, free energy fluctuations, and metastable states in condensed matter systems. He also explores applications of statistical physics to social sciences, such as belief dynamics and collective adaptation mechanisms. Notable contributions include co-authoring the book Spin Glasses and Complexity (Princeton University Press, 2013), which synthesizes foundational concepts in spin glass theory. His work frequently addresses questions of predictability in low-temperature Ising dynamics and the interplay between disorder and thermodynamic behavior. Dr. Stein’s research extends to nanomagnetism, including micromagnetic simulations of ferromagnetic nanorings and the study of energy barriers in spin-torque-driven systems. He has also contributed to discussions on machine translation and computational tools for multilingual studies, reflecting his interdisciplinary reach.

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