جست‌وجوی استاد و پژوهشگر

Nathaniel Barlowمشاهده پروفایل

دانشیار

• Asymptotic Analysis
• Fluid Dynamics
• Waves
• +۷ مورد دیگر

Nathaniel Barlow is an Associate Professor in the School of Mathematics and Statistics within the College of Science at Rochester Institute of Technology (RIT). He holds a Ph.D. in Mechanical Engineering from Clarkson University (2009) and has conducted postdoctoral research as an NSF CI-TraCS Fellow at SUNY Buffalo, where he co-developed asymptotic approximants—a re-summation technique for divergent series. His research focuses on asymptotic analysis, fluid dynamics, and wave instability, with notable contributions to boundary layer analysis and epidemic modeling via asymptotic methods. He leads the Barlow-Weinstein research group, collaborating on projects involving undergraduate and graduate students. Education: Ph.D., Mechanical Engineering, Clarkson University, 2009 B.S., Mechanical Engineering, Clarkson University Research Interests: Development and application of asymptotic approximants Hydrodynamic stability, absolute/convective instability classification Long-time behavior of dispersive waves Mathematical modeling of epidemic dynamics (SIR/SEIR models) Computational relativity and gravitational wave analysis Awards & Honors: 2020/2021 Eisenhart Award for Outstanding Teaching (RIT's highest teaching honor) 2017/2018 RIT Innovative Teaching with Technology Award 2009 Clarkson University Outstanding Teaching Award Collaborations & Grants: Co-PI on NSF-funded projects related to asymptotic analysis Guided over 10 student publications, including undergraduates in boundary layer research Co-authored studies on SARS-CoV-2 modeling with student collaborators Teaching: Undergraduate Program Coordinator for Applied and Computational Mathematics Teaches courses in differential equations, boundary value problems, and mathematical software Recipient of Eisenhart Award for integrating technology into pedagogy

• Continuum Mechanics
• Random Fields
• Fractal Analysis
• +۴ مورد دیگر

Martin Ostoja Starzewski is a Professor at the University of Illinois at Urbana-Champaign, holding joint appointments in the Department of Mechanical Science and Engineering, the National Center for Supercomputing Applications (NCSA), and the Beckman Institute for Advanced Science and Technology. His research focuses on stochastic mechanics, continuum physics, and fractal media, with emphasis on random fields, thermodynamics, and material behavior under complex conditions. Key research interests include: Random field theory and its applications in mechanics Fractal and Hurst effect modeling in materials and turbulence Continuum mechanics of heterogeneous and anisotropic media Thermoelasticity and non-equilibrium thermodynamics Numerical methods for nonlinear dynamical systems Recent work explores odd elasticity, fractal scaling in granular systems, and heat conduction in biological tissues. He has published over 300 peer-reviewed articles and is recognized as a Fellow of multiple professional societies, including ASME and AIHEM. Notable awards include the 2024 Foreign Membership in Academia Europaea and the 2023 INI Rothschild Distinguished Visiting Fellowship. His affiliations with NCSA and Beckman Institute support interdisciplinary collaborations in computational mechanics and advanced materials research.

Lelys Guenniمشاهده پروفایل

دانشیار بالینی

• Environmental Statistics
• Climate Change Impacts
• Risk Assessment
• +۳ مورد دیگر

Lelys Guenni is a Clinical Associate Professor in the Department of Statistics and affiliated with the Center for Latin American and Caribbean Studies at the University of Illinois at Urbana-Champaign. She holds a PhD in Environmental Sciences from Griffith University (Australia) and has over 25 years of teaching experience at Simón Bolívar University in Venezuela. Her research focuses on environmental statistics, spatial-temporal analysis, and risk assessment under climate change. She has held visiting appointments at the University of California, Santa Cruz, and Northern Illinois University. Her expertise includes Bayesian modeling, wavelet analysis, and hydrological studies. She contributed to the Millennium Ecosystem Assessment as a lead author and was part of the IGBP’s Biospherical Aspects of the Hydrological Cycle project. Education: PhD in Environmental Sciences, Griffith University, Australia. MSc in Water Resources Engineering, Simón Bolívar University. Bachelor in Mathematics, Simón Bolívar University. Her research spans climate change impacts, extreme rainfall patterns, and environmental vulnerability. Key areas include water quality analysis in Cambodia, malaria vector ecology in Brazil, and renewable energy forecasting using neural networks. Awards: Recipient of the Zayed International Prize for the Environment (2005). Editorial Roles: Editor for Hydrology and Earth System Sciences , Heliyon , and Environmetrics . Her work bridges environmental data science with policy, emphasizing interdisciplinary approaches to ecological challenges.

Krishnakumar Balasubramanianمشاهده پروفایل

دانشیار

• Deep Learning Theory
• Sampling and Stochastic Optimization
• Geometric Statistics
• +۵ مورد دیگر

Krishnakumar Balasubramanian is an Associate Professor in the Department of Statistics at the University of California, Davis. His research focuses on deep learning theory, sampling and stochastic optimization, geometric and topological statistics, and nonparametric methods. He has contributed to advancements in high-dimensional statistical inference, optimization algorithms, and theoretical foundations of machine learning. He holds a Ph.D. in Statistics and has published extensively in top-tier journals and conferences. His work bridges statistical theory with practical machine learning challenges, addressing topics such as sampling algorithms, non-smooth optimization, and the analysis of complex data structures like manifolds and networks. Notably, he won the Grad Advising Award, reflecting his dedication to student mentorship. His research spans diverse areas including Stein's method applications, Langevin Monte Carlo analysis, and the theoretical properties of gradient descent dynamics. He also explores nonparametric modeling, geometric statistics, and the interplay between optimization and statistical guarantees in high-dimensional settings. Key Areas: Deep Learning Theory, Stochastic Optimization, Geometric Statistics, Topological Data Analysis, Nonparametric Methods, High-Dimensional Statistics Awards: Grad Advising Award Advising: Actively involved in mentoring graduate students, as highlighted by his award.

Georgios Gounarisمشاهده پروفایل

پژوهشگر

• Condensed Matter Physics
• Biophysics
• Complex Networks
• +۳ مورد دیگر

Georgios Gounaris is a Postdoctoral Researcher at the University of Pennsylvania's Department of Physics and Astronomy, affiliated with the School of Arts & Sciences. His research focuses on condensed matter physics, biophysics, and complex systems, particularly exploring optimal navigation in flow networks, Braess paradox analogs in physical systems, and vascular morphogenesis. Education: B.S. in Physics from the University of Athens (2016). Research Interests: Georgios investigates the interplay between network structure and function in biological and physical systems. He studies microbial navigation in fluid networks, optimization principles in transport systems, and the role of metabolic processes in vascular development. His work combines statistical mechanics, nonlinear dynamics, and computational modeling to uncover universal design principles in complex systems. Key Article Trends: Recent studies analyze counter-intuitive phenomena in network efficiency, such as Braess-like paradoxes, and examine how biological systems achieve uniform perfusion through optimized vascular architectures. Earlier work includes quantum anyon statistics and non-local current phenomena in condensed matter systems. Labs/Teams: Active in the Department of Physics and Astronomy's biophysics and complex systems research groups, collaborating on interdisciplinary projects at the intersection of physics and life sciences.

Meryem Ayşe Yücelمشاهده پروفایل

استاد پژوهشی

• Functional Near-Infrared Spectroscopy
• Brain Imaging
• Clinical Applications
• +۳ مورد دیگر

Meryem Ayşe Yücel serves as a Research Associate Professor in the Department of Biomedical Engineering at Boston University's College of Engineering, where she also holds the position of Technical Director for the Neurophotonics Center. Her work bridges engineering innovation with clinical neuroscience applications, focusing on advancing functional Near-Infrared Spectroscopy (fNIRS) technology for real-world implementation. Dr. Yücel earned her PhD in Biomedical Engineering from Bogazici University in Turkey. Her educational foundation supports her interdisciplinary approach to neuroimaging research. Her research centers on developing and refining fNIRS methodologies for brain imaging, with particular emphasis on clinical translation and accessibility. She investigates cortical activation patterns during naturalistic activities like walking, conversation, and cognitive tasks, applying these insights to conditions including knee osteoarthritis, aphasia, stroke recovery, and pediatric development. Her work consistently addresses critical barriers in neuroimaging such as signal quality across diverse skin and hair types, driving inclusive research practices. Recent publications highlight her leadership in standardization efforts through projects like the fNIRS glossary and NIRS-BIDS data framework. Analysis of her recent publications reveals a strong trajectory toward mobile, high-density fNIRS systems operating in natural environments. Her research increasingly integrates multimodal approaches (fNIRS-EEG), develops open-source hardware (ninjaNIRS, ninjaCap), and establishes reproducibility standards for the field. Clinical applications dominate her output, particularly in pain assessment, rehabilitation, and cognitive neuroscience. Dr. Yücel's scientific recognition includes: Society of Functional Near-Infrared Spectroscopy Community Award (2022) Light of the Lab Award for Functional Inclusiveness (2022) TUBITAK Fellowships for Visiting Scientists (2022) Facebook Award for Engineering Approaches to Responsible Neural Interface Design (2021) SfNIRS Early Investigator Award Finalist (2016) Britton Chance Symposium Travel Award (2013) TUBITAK Integrated Doctoral Fellowship (2006-2010) As Technical Director of the Neurophotonics Center, she leads a multidisciplinary team developing next-generation optical brain imaging systems. Her leadership extends to community-building initiatives that promote open science and methodological rigor in fNIRS research, while her Facebook-funded project demonstrates successful translation of engineering solutions to neural interface challenges. The Neurophotonics Center under her technical direction pioneers wearable fNIRS technologies for naturalistic neuroscience, with recent innovations including flexible circuit-based imaging systems and 3D-printable headgear that enable high-density measurements during real-world activities. This work directly supports her research on brain function during daily movements and clinical applications.

Dora Angelakiمشاهده پروفایل

استاد

• Neural Science
• Computational Neuroscience
• Sensory Integration
• +۳ مورد دیگر

Dora Angelaki is a Professor of Neural Science and Mechanical and Aerospace Engineering at New York University. She holds a Ph.D. from the University of Minnesota (1991). Her research focuses on understanding the computational principles underlying brain function, particularly in navigation, multi-sensory integration, and causal inference. She employs engineering approaches like Kalman filters and POMDP frameworks to study neural dynamics in macaques and rodents. Her work bridges neuroscience with artificial intelligence, aiming to explain how the brain optimally processes sensory information and how deficits arise in neuropsychological disorders. Education: Ph.D., 1991, University of Minnesota. Research Interests: Neural implementation of canonical computations, sensory inference, spatial orientation, and computational models of cognition. She investigates how hierarchical causal inference is implemented across brain regions, emphasizing dynamic reconfiguration of neural connectivity and belief propagation. Her lab explores these mechanisms using naturalistic foraging tasks and closed-loop virtual environments. Lab Website: Pending Contact: da93@nyu.edu Advising and Grants: No explicit student advisees or grant details provided in text. Labs/Teams: Her research group focuses on systems, computational, and cognitive neuroscience, with an international collaborative network as noted in her 2017 publication.

• Healthcare Operations Management
• Operations Research
• Health Informatics
• +۳ مورد دیگر

Gréanne Leeftink is an Associate Professor at Utrecht University, holding roles in the Digital Society Institute, Industrial Engineering & Business Information Systems, and TechMed Centre. Her research focuses on optimizing healthcare operations through advanced analytics, process mining, and operations research, addressing challenges such as nurse allocation, bed census prediction, and inter-organizational resource pooling. She earned her PhD from Utrecht University with a thesis on healthcare process optimization. Her expertise spans healthcare logistics, scheduling strategies, and simulation-optimization methods. Key contributions include models for hospital capacity planning, cost analysis of Connected Care interventions, and reducing failures in medical practices. She has organized conferences like the CHOIR PhD Summer School on Healthcare Operations Research. Scientific Awards: CTIT Best poster award (2015) NWO MaGW Research Talent Grant (2014) Prins Bernhard Cultuurfonds grant (2016) Gréanne collaborates across disciplines to improve healthcare systems, emphasizing data-driven decision-making and sustainable resource management. She has supervised one PhD student and contributed to grants focusing on integrated healthcare processes and rapid diagnostics.

• Law and Digital Technology
• Chinese Public Law
• Comparative Administrative Law
• +۴ مورد دیگر

Dr Clement Chen is a Lecturer at the ANU Law School, part of the ANU College of Law, Governance and Policy. He holds affiliations as a Fellow at Sun Yat-sen University’s Center for Public Law and a Visiting Fellow at The University of Hong Kong's Law & Technology Centre. His research focuses on public law, law & technology, comparative administrative law, and algorithmic regulation, with a particular emphasis on China's legal system and governance structures. He obtained his LLB and MPhil from Sun Yat-sen University, a PhD from the University of Hong Kong, and a Postgraduate Diploma from the University of Paris 1 Panthéon-Sorbonne. His work explores intersections between legal theory, technology governance, and Chinese legal practices, including the Social Credit System’s implications and AI-driven legal decision-making. Research trends in his publications highlight critical analysis of China’s regulatory frameworks, digital governance challenges, and algorithmic accountability. His 2024 work on Social Credit-based punishment examines deterrence mechanisms and autonomy erosion, while 2023 collaborations demonstrate AI applications in legal knowledge dissemination. Earlier works (2015–2022) analyze FOI regimes, data privacy, and judicial transparency dynamics. He secured a HK$705,920 General Research Fund grant for algorithm-assisted sanctions research. Teaching includes postgraduate courses on data regulation and Chinese law across Hong Kong, Italy, and Australia. Clement actively advises on legislation related to digitization and freedom of information in China.

Viktor Škultétyمشاهده پروفایل

پژوهشگر ارشد

• Neuroscience
• Neuroimaging
• Hemodynamics
• +۵ مورد دیگر

Viktor Škultéty is a theoretical physicist working as a post-doctoral fellow at MIP:Lab, specializing in functional ultrasound localization microscopy (fULM) to study hemodynamic flow in the brain's microvascular system. As part of the MICROVASC project, he collaborates with Michael Tanter’s group at INSERM (Paris) to analyze blood flow changes in micron-scale capillaries related to brain activity and small vessel diseases. His educational background includes: PhD from the University of Edinburgh under Prof. Alexander Morozov, focusing on analytical and numerical tools for microswimmer systems (E. coli correlations, rheology, spatial confinement) MSc from Stockholm University with Juha Honkonen (University of Helsinki), researching stochastic processes and hydrodynamic turbulence via field-theoretic renormalization group Škultéty's research spans Neuroscience, Neuroimaging, and Hemodynamics, with current work on microvascular blood flow analysis using fULM. His theoretical physics background in Fluid Dynamics and Statistical Mechanics informs his approach to modeling biological systems, particularly in understanding collective motion in active matter. This interdisciplinary focus bridges fundamental physics with biomedical applications in brain imaging. Analysis of his 10 publications (2018-2024) reveals a clear trajectory from theoretical studies of microswimmer hydrodynamics and active membranes toward neuroscience applications. Early work emphasized renormalization group methods and stochastic processes, while recent publications integrate these techniques with neuroimaging to address hemodynamic instabilities in brain capillaries. No scientific awards were mentioned in the source material. There is no information available regarding student advising or research grant funding in the provided text. Škultéty is embedded within the MIP:Lab research team and maintains a key collaboration with INSERM in Paris for the MICROVASC project, which focuses on developing methods to detect subtle blood flow alterations in cerebral microvasculature for both fundamental neuroscience and clinical diagnostics of small vessel diseases.

Lukas Riedelمشاهده پروفایل

پژوهشگر

• Climate Risk Modeling
• Flood Impact Assessment
• Soil Hydrology
• +۴ مورد دیگر

Lukas Riedel is a Researcher at the Department of Environmental Systems Science (D-USYS) at ETH Zurich, affiliated with the Weather and Climate Risk Group under Prof. David N. Bresch and collaborating with MeteoSwiss. His research focuses on climate risk modeling, particularly impact estimation of hydrometeorological events using the CLIMADA platform in the Weather4UN project. He specializes in fluvial flood inundation modeling, socio-economic impact assessments, and open-source software development for disaster risk reduction. Education: Dr. Riedel holds a Physics degree from Heidelberg University and a PhD in numerical modeling and data assimilation of soil water flow from the Institute of Environmental Physics. His postdoctoral work included developing elasticity models for biological cells at the 'Structures' Cluster of Excellence, collaborating with the Physics of Complex Biosystems and Scientific Computing groups. Research Interests: His work bridges environmental physics and computational science, with contributions to software frameworks like DORiE (soil water flow solver) and Utopia (modeling complex systems). He emphasizes open data utilization, such as OpenStreetMap integration for climate risk assessments, and anticipatory humanitarian action through impact-based forecasting. Key Projects: Co-developed the globally consistent river flood impact model using open data, and advanced CLIMADA’s impact function calibration module. His research addresses flood hazard mapping, tropical cyclone displacement forecasting, and uncertainty quantification in climate risk models. Awards: None explicitly mentioned. Advising & Grants: No formal advisees listed, but contributes to collaborative projects like Weather4UN, which integrates multi-stakeholder decision-making for humanitarian response. Labs/Teams: Core member of the Weather and Climate Risk Group at ETH Zurich, and previously part of the 'Structures' Cluster of Excellence and the Interdisciplinary Center for Scientific Computing (IWR).

• Transportation Systems Analysis
• Discrete Choice Models
• Operations Research
• +۳ مورد دیگر

Michel Bierlaire is a Full Professor at the Swiss Federal Institute of Technology in Lausanne (EPFL), affiliated with the School of Architecture, Civil and Environmental Engineering (ENAC) and the Transport and Mobility Laboratory (TRANSP-OR). He holds additional roles as Director of the Transport Center and the Doctoral Program in Civil and Environmental Engineering at EPFL, and as a Research Affiliate at MIT and Extraordinary Professor at the University of Stellenbosch. His expertise spans transportation systems analysis, discrete choice models, operations research, and nonlinear optimization. He has authored over 113 journal articles, 4 books, and 39 book chapters, with an h-index of 51 on Google Scholar. Bierlaire is the founder of the European Association for Research in Transportation (hEART) and serves as Editor-in-Chief of the EURO Journal on Transportation and Logistics. His research focuses on modeling transportation demand, traffic management systems, and urban mobility solutions. Notable contributions include work on pedestrian flow dynamics, vehicle sharing systems, and policy-driven transport optimization. He has led projects on decarbonizing urban transport and enhancing mobility through advanced discrete choice models. Awards and recognitions include editorial roles at major journals and international leadership in transportation research associations. His work integrates behavioral economics, data science, and engineering to address complex urban and transportation challenges.

Manuel Torrilhonمشاهده پروفایل

استاد

• Continuum Physics
• Kinetic Theory
• Rarefied Gas Dynamics
• +۴ مورد دیگر

Manuel Torrilhon serves as Professor and head of the Research Lab for Applied and Computational Mathematics (ACoM) at RWTH Aachen University, where he has held a full professorship since 2010. He currently leads the Department of Mathematics as its elected Speaker for the 2024-2026 term, overseeing academic strategy and research initiatives within the Faculty of Mathematics, Computer Science and Natural Sciences. His academic foundation includes: Diplom-Ingenieur in Engineering Physics from TU Berlin (1994-1999) PhD in Applied Mathematics from ETH Zurich (2004) Postdoctoral research at HKUST (2004/05) and Princeton University (2005/06) Research Assistant Professor at ETH Zurich (2007-2010) Professor Torrilhon's research pioneers mathematical modeling in continuum physics and kinetic gas theory , with seminal contributions to the Boltzmann equation, rarefied gas dynamics, and magnetohydrodynamics. His work develops advanced numerical methods for nonlinear hyperbolic systems , particularly entropy-stable high-order schemes and multi-scale time integrators. The ACoM lab under his direction bridges theoretical mathematics with engineering applications through computational frameworks like fenicsR13 for moment equation solvers. His methodologies enable high-fidelity simulations of micro-flows, plasma instabilities, and electron transport phenomena critical to aerospace and materials science. Analysis of his 2025-2024 publications reveals dominant trends in entropy-conservative numerical schemes for kinetic equations, multirate time integration for stiff systems, and moment-method extensions to polytropic gases and shallow flows. These works consistently address computational challenges in rarefaction effects, non-equilibrium thermodynamics, and high-enthalpy regimes, demonstrating cross-cutting applications from microfluidics to plasma physics. Scientific recognition includes: EURYI Award (Pre-ERC) from European Science Foundation (2006) As director of ACoM, Professor Torrilhon secures research funding for computational mathematics projects and mentors graduate students in numerical analysis and kinetic theory. His lab maintains strong collaborations with engineering departments for applied validation of mathematical models, particularly in micro-flow devices and plasma containment systems. Current grants focus on adaptive solvers for multi-scale kinetic problems and inverse methods for electron probe microanalysis. The Research Lab for Applied and Computational Mathematics (ACoM) operates as an interdisciplinary hub developing open-source computational tools like fenicsR13. The team specializes in tensor-based numerical methods for moment equations, with ongoing projects in X-ray emission modeling, Richtmyer-Meshkov instability simulations, and thermodynamically consistent electrolyte solvers. ACoM maintains strategic partnerships with aerospace research institutes for hypersonic flow validation and with materials science centers for nanoscale transport studies.

Edgar Choueiriمشاهده پروفایل

استاد

• Applied Physics
• Electric Propulsion
• Plasma Dynamics
• +۵ مورد دیگر

Edgar Choueiri is a tenured Professor of Mechanical and Aerospace Engineering at Princeton University, Director of the Electric Propulsion and Plasma Dynamics Laboratory (EPPDyL), and Director of the 3D Audio and Applied Acoustics (3D3A) Lab. He holds affiliations with the Astrophysical Sciences Department and Program in Plasma Physics. He earned his Ph.D. from Princeton University in 1991. His research spans advanced spacecraft propulsion, plasma dynamics, and 3D audio technologies. Key areas include magnetoplasmadynamic thrusters, lithium-fed propulsion systems, and spatial audio innovations like the BACCH 3D Sound technology. He has led over 40 research projects funded by NASA, AFOSR, and private entities, with two space experiments on the Space Shuttle and APEX spacecraft. Choueiri has authored over 220 publications and patents, advised over 100 students (10 PhD graduates), and developed novel courses in astronautics and plasma propulsion. His honors include a knighthood from Lebanon and leadership roles in the Electric Rocket Propulsion Society and AIAA’s Electric Propulsion Technical Committee. Education: Ph.D. in Mechanical and Aerospace Engineering, Princeton University (1991) Notable Projects: 3D3A Lab’s BACCH Sound, high-power lithium MPD thrusters for Mars missions Grants: Over $50M in funding from NASA, AFOSR, and NSF Awards: Knight of the Cedar (Lebanon), Lebanese Academy of Sciences President (2008) His labs focus on plasma thruster development, acoustic innovations, and space propulsion systems for future missions.

• Complex systems
• Complex networks
• Information theory
• +۳ مورد دیگر

Associate Professor Joseph Lizier is a leading academic at the School of Computer Science, The University of Sydney, with a focus on complex systems and information theory. He has held this position since 2019, following a DECRA Fellowship (2016-19) and Senior Lecturer role (2015-18). Previously, he worked at CSIRO ICT Centre (2012-14) and the Max Planck Institute (2010-12), and has industry experience in telecommunications. His research spans computational neuroscience, complex networks, and information theory, examining how biological and artificial systems process information through transfer entropy and distributed computation. Key themes include neural information flows, small-world network properties, and applications to brain imaging, financial markets, and epidemic modeling. Current projects involve ARC Discovery grants and international collaborations with German institutions. Recent publications analyze multiscale brain dynamics, cholinergic stabilization of neural networks, and information processing in neuromorphic nanowires. His work reveals patterns in neuronal bursts, epidemic modeling, and swarm intelligence through information-theoretic approaches. Scientific awards include the Entropy Best Paper (2019), Sydney Accelerator Fellowship (SOAR), and multiple conference and thesis prizes. He supervises PhD students working on topics like self-organization, neural synchrony, and information flow in biological systems.