جست‌وجوی استاد و پژوهشگر

Charlotte Changمشاهده پروفایل

استادیار

• Conservation Biology
• Social-Ecological Systems
• Quantitative Ecology
• +۵ مورد دیگر

Charlotte Chang serves as Assistant Professor of Biology and Environmental Analysis at Pomona College, where she has been faculty since 2020. Her dual appointment bridges the Department of Biology and Environmental Analysis program, with laboratory space in Seaver South. She maintains active affiliations including a Visiting Science Fellowship with The Nature Conservancy's One Conservancy program and collaborations with Centre for Wildlife Studies India and Wildlife Conservation Society. Ph.D. in Ecology and Evolutionary Biology, Princeton University Master of Philosophy, University of Cambridge Bachelor of Arts, Pomona College Chang's research integrates social-ecological systems analysis to advance conservation science, specializing in digital conservation constituencies, illicit wildlife hunting dynamics, and agroforest management for habitat specialists. Her lab employs innovative methodologies combining data science, quantitative ecology, and field methods to examine human-environment interactions across tropical systems. Current projects include LLMs for natural climate solutions evidence mapping and environmental social media analysis for conservation outreach optimization. Her publication record demonstrates consistent high-impact output across conservation biology, ecological modeling, and social science journals. Trends show increasing focus on digital conservation mobilization since 2020, with notable work on Twitter environmental discourse and platform migration patterns. Earlier research established foundational work on hunting motivation in Southwest China and coffee agroforest biodiversity in India's Western Ghats. David H. Smith Conservation Research Fellow National Science Foundation NIMBioS Postdoctoral Fellow IUCN Critical Ecosystem Partnership Fund Research Grant NSF GROW with USAID research fellowship Fulbright Fellowship Chang actively mentors early-career researchers across North America and Asia, with notable success in placing mentees in conservation organizations and graduate programs. Her lab receives funding from multiple NSF programs and conservation NGOs, supporting fieldwork in China, India, and Southeast Asia. Current grants focus on social media analysis for conservation outreach and natural climate solutions mapping. The Chang Lab operates as an interdisciplinary hub combining computational ecology, conservation social science, and field research. Her team collaborates with environmental practitioners, community leaders, and academic colleagues globally, with recent projects spanning the Western Ghats, Southwest China, and digital conservation networks worldwide.

Vincent Wheatleyمشاهده پروفایل

استاد

• Supersonic Plasma Flows
• Hypersonics
• Computational Fluid Dynamics
• +۷ مورد دیگر

Professor Vincent Wheatley is a Professor at the School of Mechanical and Mining Engineering, University of Queensland , and Co-Director of the Centre for Hypersonics . His research focuses on supersonic plasma flows , hypersonics , and computational fluid dynamics , with applications in inertial confinement fusion and scramjet engines for space propulsion. Education: PhD in Aeronautics (2005), California Institute of Technology MEngSc (Mechanical), University of Queensland BE (Mechanical and Space), University of Queensland His recent work (2025–2021) explores scramjet combustion dynamics (e.g., hydrogen/ethylene fuel injection), plasma instabilities in multi-fluid models, and hypersonic noise and shock wave interactions . These studies employ direct numerical simulation (DNS) , large eddy simulation (LES) , and reacting flow modeling . Scientific Awards: Australia's Research Field Leader in Aerospace and Aviation Engineering (2018) 2017 Australian Award for University Teaching – Award for Teaching Excellence Professor Wheatley supervises projects on plasma fuel engines and hypersonic propulsion , supported by grants from the Australian Research Council (ARC) and Commonwealth Defence Science and Technology Group . His team collaborates on multi-fluid plasma simulation and scramjet optimization .

Nikos Giatrakosمشاهده پروفایل

استادیار

• Big Data Management
• Internet of Things (IoT)
• Distributed Systems
• +۳ مورد دیگر

Nikos Giatrakos is an Assistant Professor at the School of Electronic & Computer Engineering, Technical University of Crete, and a core member of the Software Technology and Network Applications Lab (SoftNet) . His work bridges Big Data systems, IoT, and advanced analytics, with a focus on real-time processing and scalable architectures. Previously, he served as a postdoctoral researcher at the same laboratory. Education PhD in Computer Science, University of Piraeus (2012) Postgraduate Diploma in Information Systems, Athens University of Economics and Business (2008) BSc in Computer Science, University of Piraeus (2006) Research Focus : Nikos specializes in software architectures for Big Data streaming, including Distributed Big Data Processing , Federated Machine Learning , Cloud-to-Edge Data Management , and Approximate Query Processing . His work has also advanced Complex Event Processing and Outlier Detection in decentralized environments. Scientific Contributions : His research has led to the DAG* workflow optimizer for IoT, the SuBiTO framework for real-time neural learning, and the INFORE approach for cross-platform analytics. He received the Best System Demonstration Award at ACM CIKM 2020 for INforE. Academic Leadership : Nikos teaches Object-Oriented Programming, Data Science, and Distributed Systems. He has supervised numerous European and national grants as Principal Investigator and served on program committees for top-tier conferences like SIGMOD, VLDB, and DEBS.

• Numerical Analysis
• Uncertainty Quantification
• Inverse Problems
• +۳ مورد دیگر

Oliver G. Ernst is a Professor of Numerical Analysis at Technische Universität Chemnitz . His research focuses on Numerical Analysis , Uncertainty Quantification , and Inverse Problems , with applications in Thermo-Hydro-Mechanical (THM) processes , Electromagnetics , and Stochastic Partial Differential Equations . He is associated with the Numerical Analysis group at TU Chemnitz. Key Research Areas : Efficient numerical methods for PDEs Krylov subspace techniques Stochastic finite element methods Multi-physics modeling Geoscientific applications Recent Publications (2025-2010): THM simulations under uncertainty Neural network PDE solvers Bayesian inversion frameworks Rational Krylov algorithms Deflated restarting strategies Collaborations : TU Bergakademie Freiberg University of Manchester Technical University of Munich University of Maryland University of Geneva Software Development : Contributor to OpenGeoSys platform Developer of FEMALY MATLAB library Academic Recognition : h-index 32, i10-index 66, with over 4423 citations since 2020.

Shiqiang Yanمشاهده پروفایل

استاد

• Wave/current/wind interaction
• Structure responses in extreme sea conditions
• Renewable energy and low carbon technologies
• +۲ مورد دیگر

Professor Shiqiang Yan is an ocean engineering expert at City St George's, University of London , with over 25 years of academic experience. He obtained his PhD in Hydraulics (2007) from City University London, following MSc (2004) and BEng (1999) from Dalian Maritime University. His career includes Postdoctoral Research Fellow (2007-2012) and Lecturer (2012–present) positions at City University. Specializes in Wave-Structure Interaction and Extreme Sea Condition Modeling Developed QALE-FEM and ISPH-GNN hybrid numerical methods Research spans Wave Energy , Offshore Wind , and Marine Pollution Control His 15 most recent publications (2021-2025) demonstrate expertise in Wave-Structure Interaction (40% of articles), Hybrid Modeling (30%), and Renewable Energy Systems (25%). Key subfields include Wave-WEC Coupling , Ice Floe Dynamics , and Multi-Scale Hydrodynamic Modeling . He has advised PhD student Hao Yang (2013–present) on submerged oil spill research. Professional memberships include the International Society of Ocean & Polar Engineering (2013–present).

Peter B. Flemingsمشاهده پروفایل

استاد

• Basin-scale Fluid Flow
• Methane Hydrates
• Shale and Mudstone Permeability
• +۵ مورد دیگر

Peter B. Flemings is a Research Scientist at the University of Texas Institute for Geophysics (UTIG) and Professor in the Department of Earth and Planetary Sciences at the Jackson School of Geosciences, University of Texas at Austin. He holds the Leonidas T. Barrow Centennial Chair in Mineral Resources and is a leading expert in geopressure, methane hydrates, and fluid flow in sedimentary basins. B.A., Geology, Dartmouth College (1984) M.S., Geology, Cornell University (1987) Ph.D., Geology, Cornell University (1990) Dr. Flemings investigates crustal fluid flow at human and geologic timescales, focusing on pore pressure prediction, methane hydrate formation, and the role of fluid dynamics in continental margin morphology. His work integrates theoretical analysis with field studies, laboratory experiments, and industry collaboration through the UT GeoFluids research consortium. His research group simulates methane hydrates in the GeoMechanics Laboratory and develops downhole technologies for ocean drilling. Recent projects include a Gulf of Mexico methane hydrate drilling initiative and studies on mudstone permeability and deformation. Scientific Awards: Robert R. Berg Outstanding Research Award Dr. Flemings leads the Genesis of Methane Hydrate Project, a multi-disciplinary effort supported by the U.S. Department of Energy, and contributes to international ocean drilling programs. He is the author of the landmark textbook A Concise Guide to Geopressure , published in 2021 by Cambridge University Press.

Anna Caiمشاهده پروفایل

مدرس

• Mathematical Biology
• Biomathematics
• Mathematical Modeling
• +۳ مورد دیگر

Dr. Anna Cai is a Lecturer in the Department of Applied Mathematics within the School of Mathematics & Statistics at the University of New South Wales (UNSW), a position she has held since 2011. Prior to this, she served as a postdoctoral researcher and lecturer at the University of California, Irvine from 2007 to 2011. Her educational background: Ph.D., The University of Melbourne, 2008 B.Sc. (First Class Honours), The University of Melbourne, 2004 Dr. Cai's research centers on Mathematical Biology , with specialization in cell migration dynamics , developmental pattern formation , and robustness in biological systems . She employs multi-scale mathematical modeling and stochastic analysis to investigate phenomena ranging from wound healing to zebrafish hindbrain development. Her work bridges theoretical mathematics with experimental biology to decode fundamental mechanisms governing cellular behavior and morphogenesis. Analysis of her 11 publications (2006-2015) reveals an evolutionary trajectory from foundational work on cell migration mechanics to sophisticated studies of developmental robustness. Early research established mathematical frameworks for wound-healing assays and immune cell dynamics, while later work pioneered noise-driven pattern formation models in zebrafish. A unifying thread is her focus on how biological systems maintain precision despite environmental fluctuations. Administrative responsibilities include: Applied representative on the postgraduate review committee UNSW study abroad and exchange course authority Current teaching assignments: MATH2121: Theory and Applications of Differential Equations MATH2018: Engineering Mathematics 2D Prior courses taught: MATH3041: Mathematical Modeling for Real World Systems MATH6781: Biomathematics

• Solar MagnetoHydroDynamics (MHD)
• Nonlinear Plasma Waves
• Solar Corona Heating
• +۷ مورد دیگر

Dr. Istvan Ballai is a Senior Lecturer in Applied Mathematics at the School of Mathematical and Physical Sciences , University of Sheffield. His research focuses on MHD waves in solar and interplanetary plasmas , particularly their role in energy transport, plasma heating, and diagnostics. University : University of Sheffield Email : i.ballai@sheffield.ac.uk His work encompasses linear and nonlinear wave phenomena in partially ionized plasmas, with applications to solar corona heating and wave-based plasma diagnostics. Recent publications highlight advancements in modeling Alfvén waves , solar vortices , and photospheric flux tubes . Articles span 2025–2022 , emphasizing numerical simulations and observational analysis of wave propagation, energy concentration, and instability dynamics. Dr. Ballai has received grants from Leverhulme , Royal Society , Nuffield , and STFC , and contributes to teaching in Differential and Difference Equations , Complex Analysis , and Numerical Methods .

• Concrete Technology
• Durability of Materials
• Mechanical Behavior of Materials
• +۳ مورد دیگر

Mouad JEBLI is an Associate Professor at CESI Engineering School in Aix-en-Provence, France, where he serves as a Teacher-researcher within the Engineering and Digital Tools research team. His academic focus centers on the chemomechanical behavior and durability of concrete materials, with particular expertise in interfacial transition zone (ITZ) characterization and degradation mechanisms. His educational background includes a Doctorate in Mechanics and Civil Engineering (2013-2016) from University of Montpellier/IMT Mines Alès, with research on local-scale mechanical properties of cement paste-aggregate interfaces, and a Specialized Master in Engineering and Project Management of Building and Public Works (2011-2012) from University of Montpellier 2 and Cadi Ayyad University, Morocco. Dr. JEBLI's research spans Concrete Technology, Durability of Materials, and Mechanical Behavior of Materials, emphasizing experimental characterization of chemomechanical degradation processes including leaching, internal sulfate attack, and interface mechanics. His work integrates multi-scale approaches from nanoindentation to structural testing, with significant contributions to cohesive zone modeling and composite repair techniques for concrete structures. Analysis of his 15 most recent publications (2018-2024) reveals consistent focus on experimental methodologies for concrete durability assessment, with strong emphasis on interface mechanics, degradation modeling, and sustainable repair solutions. Key thematic trends include the evolution of ITZ properties under chemical attack, development of predictive models for material interfaces, and application of natural fiber composites for structural rehabilitation. His scientific recognition includes: Best Poster Award at 36èmes Rencontres de l’AUGC (2018) Dr. JEBLI actively supervises graduate research, currently guiding PhD candidate MA TAZI (defending 2026) on composite patch repairs, and previously supervised PhD graduates S. NESRINE (2021) and A. Girboveanu (2020), along with multiple Master's students including Fabrice GBEWADE (2019) and Kim Quyen Nguyen (2016). His research is conducted through the Engineering and Digital Tools team, which develops advanced engineering methodologies for construction materials and structural systems.

• Astronomy
• Astrophysics
• Machine Learning
• +۵ مورد دیگر

Robert Brunner serves as Professor of Astronomy at the University of Illinois at Urbana-Champaign, where he bridges astrophysical research with computational innovation. His work focuses on extracting knowledge from massive astronomical datasets through advanced statistical and machine learning techniques, while also extending methodologies to finance and agricultural applications. Research interests center on developing machine learning algorithms (random forests, deep neural networks, Bayesian estimation) for astronomical data analysis, cosmological parameter constraints via n-point clustering measurements, and hardware acceleration using GPUs/cloud systems. His interdisciplinary approach spans source classification, transient phenomena detection in surveys like SDSS and DES, and applications in financial time-series analysis and agricultural remote sensing. Recent publications (2019-2025) reveal strong cross-domain expertise: astronomical catalogs for Rubin Observatory and Spitzer surveys coexist with financial market analysis using community detection methods and agricultural computer vision systems. Key methodological threads include spatio-temporal forecasting, multimodal learning for earnings calls, and anomaly detection via extended isolation forests, demonstrating consistent innovation in handling petascale datasets across scientific boundaries.

• Human Reinforcement Learning
• Neuroeconomics
• Decision-Making Under Uncertainty
• +۳ مورد دیگر

Stefano Palminteri is a researcher at the École Normale Supérieure in Paris, leading the Human Reinforcement Learning team at the Cognitive Neuroscience Laboratory (LNC2) since 2017. He holds a PhD in Cognitive Neuroscience from Université Pierre et Marie Curie (2012) and completed postdoctoral work at LNC2, University of Trento, and University College London. Education: Master in Pharmaceutical Biotechnology (University of Bologna, 2006); Master in Cognitive and Behavioral Neuroscience (Université Pierre et Marie Curie, 2007); PhD in Cognitive Neuroscience (UPMC, 2012). His research focuses on computational and neurobiological mechanisms of reinforcement learning, decision-making under uncertainty, and behavioral biases. He investigates how contextual factors (e.g., social influence, neurochemical states) shape learning processes in healthy and clinical populations (e.g., addiction, depression, Tourette syndrome). Recent work explores value normalization, metacognitive biases, and cross-cultural comparisons of reinforcement learning. Key trends in his publications include (1) computational modeling of reward/punishment sensitivity in psychiatric conditions, (2) neuroeconomic frameworks for decision-making under risk and ambiguity, (3) multi-agent reinforcement learning in financial market simulations, and (4) cross-domain comparisons of description vs. experience-based learning. He employs functional neuroimaging, pharmacological interventions, and behavioral experiments to uncover how brain circuits (e.g., striatum, prefrontal cortex) encode value signals. His lab offers internships in epistemic biases and reinforcement learning.

• Computational Physics
• Density Functional Theory (DFT)
• Atomistic Simulations
• +۹ مورد دیگر

Jaakko Akola is a Professor in the Department of Physics at the Norwegian University of Science and Technology (NTNU). His research focuses on computational materials science, particularly density functional theory (DFT) and atomistic simulations of materials, nanoparticles, molecules, and interfaces. He leads significant projects such as "SIDI" (inoculation in cast iron), "Infinity-RETIS" (chemical rare events), and "AllDesign" (rational alloy design), alongside coordinating EU-funded initiatives like "CritCat" for catalyst development. The Materials Theory group under Akola employs DFT, molecular mechanics, and Monte Carlo methods to explore atomic-scale structures and functions in technological applications. Key research areas include platinum-free catalysts for hydrogen energy, amorphous semiconductors for memory devices, noble metal nanoparticles in biological environments, and alloy design for cast iron and aluminum. Recent work integrates machine learning to advance theory-driven material design, reducing reliance on experimental trial-and-error. Akola's publications highlight advancements in hydrogen evolution catalysis, phase-change memory materials, and alloy precipitation. His projects often involve interdisciplinary collaborations with experimental teams. He teaches Quantum Physics 1 (FY2045) and Computational Physics (TFY4235) at NTNU, reflecting his commitment to education alongside research.

• Environmental Systems Analysis
• Water-Food-Energy Nexus
• Climate Change Impact Assessment
• +۳ مورد دیگر

Gordon Huang is an Adjunct Professor in the Civil Engineering department at McMaster University , specializing in environmental systems analysis and sustainable resource management. His research focuses on quantitative methods for addressing uncertainties in climate change, water-food-energy nexus planning, and contaminant remediation. Primary Affiliation : Civil Engineering, McMaster University His work integrates advanced computational models like Bayesian neural networks, factorial optimization, and copula-based downscaling to analyze complex environmental interactions. Recent projects examine CO2 emission pathways, microplastic impacts, and climate-driven drought risks. Key methodologies include stochastic programming , ecological network analysis , and machine learning for predictive modeling. Publications span topics from membrane technology for water treatment to large-scale hydropower socio-economic effects. Email : huangg31@mcmaster.ca

• Energy Systems Modeling
• Geothermal Energy
• Optimization Algorithms
• +۳ مورد دیگر

Smajil Halilovic is a Researcher at the Chair of Renewable and Sustainable Energy Systems at the Technical University of Munich . His work focuses on energy systems modeling and optimization, particularly for geothermal and renewable energy integration. Current projects include Geo.KW , a coupled hydrothermal and infrastructure model for urban-scale geothermal use Research emphasizes optimization techniques for groundwater heat pump systems Key contributions in PDE-constrained optimization and thermal resource assessment Halilovic has published extensively in Renewable Energy and Energy Conversion and Management , with recent work on spatial optimization of geothermal systems and urban heat planning. His collaborations with Prof. Thomas Hamacher and Kai Zosseder highlight his role in advancing sustainable energy infrastructure. He teaches Mathematical Modeling of Complex Systems in the Energy Field and contributes to interdisciplinary projects like the Interdisciplinary project internship: Concept development of a renewable energy system in a developing country . His publications demonstrate expertise in geothermal integration, optimization algorithms, and urban energy modeling.

Jeffrey Erochkoمشاهده پروفایل

استادیار

• Wood/Timber Engineering
• Structural Engineering
• Earthquake Engineering
• +۵ مورد دیگر

Jeffrey Erochko is an Assistant Professor in the Department of Civil and Environmental Engineering at Carleton University, Ottawa, Canada. His research and teaching focus on structural engineering, particularly seismic-resistant and self-centering systems for timber and hybrid structures, as well as innovative pedagogical techniques in engineering education. B.A.Sc. Engineering Science, University of Toronto Ph.D., Civil Engineering, University of Toronto Prof. Erochko’s research spans advanced seismic design for timber buildings, hybrid simulation methods, fire performance of structural systems, and nonlinear dynamic analysis of multi-hazard scenarios. His work integrates experimental testing with computational models to enhance resilience in civil infrastructure. Key trends in his publications include hybrid timber-steel/concrete systems, self-centering dampers, nonlinear modeling of seismic responses, and fire safety engineering. His pedagogical contributions emphasize technology-driven assessment tools like micro-video projects and weighted rubrics. He leads the Carleton Hybrid Simulation Research Group and collaborates with the university’s multi-hazard infrastructure protection facility, which explores integrated experimental and computational approaches to natural hazards such as earthquakes, fire, blast, and wind.