جست‌وجوی استاد و پژوهشگر

• Condensed Matter Physics
• Magnetism
• Spintronics
• +۴ مورد دیگر

Prof. Claus Michael Schneider serves as Head of the Electronic Properties Institute (PGI-6) at Forschungszentrum Jülich and maintains strong academic ties with the University of Duisburg-Essen where he teaches physics courses. His work bridges fundamental condensed matter physics with practical applications in spintronics and quantum technologies. As director of PGI-6, he leads a multidisciplinary team investigating the complex relationships between electronic structure and physical material properties. Dr. Schneider's research focuses on the intricate interrelations between electronic structure and physical properties of matter, with particular emphasis on magnetism, spintronics, and nanoscale phenomena. His group employs advanced photoelectron spectroscopic techniques ranging from high-resolution laboratory systems to synchrotron radiation-based nanospectroscopy, enabling unique combinations of high energy, spatial, and temporal resolution. Experiments are conducted at synchrotron facilities including DELTA (Dortmund), BESSY (Berlin), and ELETTRA (Trieste). Recent publications reveal a growing focus on quantum materials, with significant contributions to understanding orbital angular momentum in electrons for orbitronics applications and the development of 2D semimetals with spin-polarized conduction. His work spans fundamental quantum phenomena to practical applications in energy-efficient computing technologies. The research portfolio includes cutting-edge instrumentation development such as the Nano-Spintronics Cluster Tool and advanced microscopy techniques for nanoscale characterization. Under his leadership, PGI-6 maintains strong connections to the 2007 Nobel Prize in Physics awarded to Peter Grünberg for the discovery of giant magnetoresistance. The institute collaborates extensively with national and international academic and industrial partners, advancing the field of electronic materials for next-generation information technologies.

Rejhana Blaževićمشاهده پروفایل

دانشیار

• Energy Efficiency
• Renewable Energy
• Heating Systems
• +۵ مورد دیگر

Rejhana Blažević is an Associate Professor at the Faculty of Mechanical Engineering, University of Sarajevo, with a focus on energy efficiency and renewable energy systems. She earned her PhD in 2018 from the Department of Energy and Process Engineering, defending a dissertation on transient heating systems modeling. Bachelor’s and Master’s degrees in Energy, Process, and Environmental Engineering (2005-2010) Specialized in building energy modeling, wind energy potential, and climate change adaptation in heating systems Her research spans energy renovation of healthcare buildings, CO2 emission reduction strategies, and thermal energy storage solutions. Recent work includes: Wind velocity trends in Sarajevo (2025) Optimal refrigerant selection for data centers (2024) Levelized cost analysis for Bosnian wind farms (2023) Climate-informed heating design temperature updates (2023) Mathematical models for transient radiator heating (2018) She has collaborated on projects analyzing energy consumption in single-family houses, waste heat recovery in refrigeration, and pulse combustion heat transfer. Her work informs policy and technical standards in Bosnia and Herzegovina’s building sector.

• Semiconductor Photonics
• Optical Characterization of Semiconductors
• III-Nitrides
• +۵ مورد دیگر

Dr. Jūras Mickevičius is a Senior Researcher at the Institute of Photonics and Nanotechnology (IPN) , Vilnius University, specializing in semiconductor photonics. His work focuses on the optical characterization of III-nitride semiconductors, including carrier dynamics, photoluminescence, and Monte Carlo simulations. Research Interests: III-nitrides, photoluminescence, carrier localization, high-carrier-density effects, semiconductor heterostructures. Research Trends: His recent publications highlight advancements in GaN epitaxy via graphene interlayers, stimulated emission thresholds, and InGaN MQW optimization. Key disciplines include materials science, computational modeling, and optoelectronic device engineering. Scientific Awards: Young Scientists Award (Lithuanian Academy of Sciences, 2009) Best Dissertation Award (2009) Vilnius University Rector Award (2015) Project Leadership: Led projects on defect-carrier interaction in LEDs (2015-2018), light emission efficiency in nitrides (2012-2014), and II-VI scintillators for X-ray detectors (2012-2013) under Lithuanian research frameworks.

Meilan Huangمشاهده پروفایل

مدرس ارشد

• Computational Chemistry
• Biocatalysis
• Machine Learning
• +۵ مورد دیگر

Dr. Meilan Huang is a Senior Lecturer (Associate Professor) at the School of Chemistry and Chemical Engineering, Queen's University Belfast. Her research focuses on integrating computational chemistry and biology with machine learning to advance biocatalysis, photocatalysis, and theoretical catalysis. She leads interdisciplinary projects bridging computational methods with experimental and industrial applications for catalyst design. PhD in Computational Chemistry, Zhejiang University (2003) Postdoctoral research: University of Calgary (1999-2003), University of Oxford (2004-2006), University of British Columbia (2006-2007) Her work explores the structure-function relationships and catalytic mechanisms of enzymes to enable rational design of novel catalysts. She develops tools like ALDELE and BioStructNet using transfer learning and deep learning for biocatalyst function prediction. Her recent publications highlight advancements in computational biocatalysis, photocatalytic glycerol oxidation, and perovskite charge dynamics. Dr. Huang has secured over £2 million in research funding, including grants from Invest NI and the Royal Society, and supervised computational and machine learning workpackages in major projects. Awards include Fellow of the Royal Society of Chemistry (2021) and Biology (2022), the Queen's Student Union Education Excellence Award (2017), and the Innovation in Teaching Fund (2022) for VR chemistry labs.

Matthew Barryمشاهده پروفایل

دانشیار مهمان

• Engineering Education
• Space Power Generation
• Thermoelectric Systems
• +۳ مورد دیگر

Matthew Barry serves as a Visiting Associate Professor in the Mechanical Engineering and Materials Science Department at the University of Pittsburgh, where he bridges historical perspectives with advanced engineering through his dual academic background. His research program integrates thermoelectric energy conversion with space exploration challenges and innovative pedagogical approaches. Education: PhD, Mechanical Engineering, University of Pittsburgh (2012-2016) MS, Mechanical Engineering, University of Pittsburgh (2010-2012) BS, Mechanical Engineering, University of Pittsburgh (2005-2010) BA, History, University of Pittsburgh (2005-2010) Nuclear Engineering Certificate, University of Pittsburgh Research Expertise: Dr. Barry's work centers on Space Power Generation via thermoelectric systems for extraterrestrial environments and Engineering Education through example-based pedagogy. His thermoelectric research explores thermal-fluid-electric coupling in waste heat recovery systems, with applications ranging from automotive exhaust to cryogenic ice melting for planetary exploration. The Journal of Electronic Materials and Energy Conversion and Management feature his breakthroughs in device performance optimization under extreme conditions. Publication Trends: Analysis of his 15 most recent publications reveals 80% focus on thermoelectric energy conversion, characterized by sophisticated multi-physics modeling of heat transfer, fluid dynamics, and electrical phenomena. Secondary threads include biomedical device innovation (smart guidewires) and petroleum engineering applications, demonstrating remarkable interdisciplinary range while maintaining core focus on energy systems. Awards: Best Poster Award, International Conference on Thermoelectrics (2017) Department of the Army Achievement Medal for Civilian Service (2009) Educational Leadership: Dr. Barry actively shapes engineering education as faculty advisor for the Society of Astronautics and Rocketry, guiding student teams in space-related design challenges. His 2020 textbook Statics and Mechanics of Materials: An Example-based Approach revolutionizes core engineering instruction through practical problem-solving frameworks, reflecting his commitment to developing the next generation of aerospace engineers.

• Electrical engineering
• Electronics, sensors and digital hardware
• Distributed computing and systems software
• +۶ مورد دیگر

Masood Parvania is the Roger P. Webb Endowed Professor at the University of Utah in Electrical and Computer Engineering. He serves as Director of the Utah Smart Energy Laboratory (U-Smart) and Co-Director of the NSF WIRED Global Center . His research focuses on mathematical optimization , control theory , and machine learning applications in power system operation, resilience, and interdependent infrastructure modeling. His work addresses critical challenges including: Equity-aware grid restoration Climate-resilient energy systems Cyber-physical security analysis Hybrid energy storage coordination Extreme heat event mitigation strategies Key research trends across his 15 most recent publications reveal deep integration of: Renewable energy with storage systems Machine learning in real-time grid operation Cybersecurity frameworks for critical infrastructure Equity metrics in energy distribution Honors include: IEEE Outstanding Associate Editor Award (2022) University of Utah Presidential Scholar (2020) IEEE Utah Section Outstanding Educator Award (2017) Multiple Best Reviewer and Distinguished Service Awards As Associate Editor for IEEE Transactions on Power Systems , he actively shapes energy research discourse while leading NSF-funded initiatives like: U.S.-Canada Climate-Resilient Grid Center ($90M+ Western EV Infrastructure Scale-Up Wasatch Multi-Modal Corridor Electrification

• Structural and Multidisciplinary Optimization
• Mechanical Engineering
• Aerospace Technology
• +۳ مورد دیگر

Pierre Duysinx is a Full Professor and Vice-Rector for Mobility and International Affairs at the University of Liège , affiliated with the Faculty of Applied Sciences and Department of Aerospace and Mechanics . His research focuses on Structural and Multidisciplinary Optimization , Mechanical Engineering , and Additive Manufacturing , with applications in aerospace and automotive technologies. His work emphasizes stress-based topology optimization , fatigue resistance , and manufacturing-constrained design . Recent publications highlight innovations in electric vehicle systems, microstructural design, and 3D printing optimizations. He has developed frameworks for multi-material distribution and robust design methodologies. Professor Duysinx teaches courses in Mechanical Design Industrial Automation Vehicle Dynamics and leads research projects in lightweight material applications and sustainable mobility solutions.

Lilianne R. Mujica-Parodiمشاهده پروفایل

استاد

• Computational Psychiatry
• Neuroimaging
• Metabolic Neuroscience
• +۳ مورد دیگر

Lilianne R. Mujica-Parodi is Professor and Director of the Laboratory for Computational Neurodiagnostics at Stony Brook University, with additional appointments in the Departments of Neurology, Psychiatry, and Physics, and affiliations at the Laufer Center for Physical and Quantitative Biology and the Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital and Harvard Medical School. Her research integrates control theory and metabolic neuroscience to investigate neural circuit regulation across physiological systems in health and disease. A Niles G. Whiting Fellow and NIH Training Fellow , she received her PhD from Columbia University after undergraduate studies at Georgetown in mathematical logic and physics foundations. Key publication themes include brain aging , metabolic psychiatry , neuroimaging biomarkers , and computational modeling . Her work explores nonlinear brain dynamics, ketosis effects on neural function, and machine learning applications for neurodiagnostics. Scientific Awards : National Science Foundation CAREER Award Presidential Early Career Award for Scientists and Engineers (PECASE) Fulbright Distinguished Scholar Award Her lab develops novel neuroimaging methodologies, including motion correction algorithms and data-driven models for psychiatric disorders, while investigating metabolic interventions to counteract age-related cognitive decline.

Romeil Singh Sandhuمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Network Science
• +۴ مورد دیگر

Romeil Singh Sandhu serves as Assistant Professor in Biomedical Informatics at Stony Brook University with adjunct appointments in Computer Science and Applied Mathematics & Statistics, directing the Laboratory for Imaging, Networks, and Control (LINC) from the Health Sciences Center. His academic credentials include: B.S. from Georgia Institute of Technology (2006) M.S. from Georgia Institute of Technology (2009) Ph.D. from Georgia Institute of Technology (2010) Dr. Sandhu's research integrates geometry, statistics, and control theory to advance computer vision (3D reconstruction, satellite pose estimation), network science (hypergraph dynamics, Ricci curvature), and systems biology (protein interaction networks, cellular robustness). His methodological innovations span level-set methods, variational techniques, and curvature-based network analysis with applications in medical imaging and aerospace systems. Analysis of his 2019-2023 publications reveals three dominant trajectories: (1) geometric network analysis using Ricci curvature to quantify biological network fragility; (2) distributed reinforcement learning with communication-efficient multi-agent actor-critic frameworks; and (3) medical/satellite image reconstruction via radar-based variational methods and active surfaces. These threads consistently leverage differential geometry to solve inverse problems in complex systems. The Laboratory for Imaging, Networks, and Control (LINC) develops computational frameworks bridging theoretical mathematics with healthcare and aerospace applications, particularly focusing on shape analysis, network dynamics, and control systems for medical diagnostics and satellite imaging.

Tae Wan Kimمشاهده پروفایل

استاد

• Magnetic Sensors
• Magnetic Thin Films
• Magnetic Random Access Memory
• +۳ مورد دیگر

Tae Wan Kim is a Professor in the Department of Nanotechnology and Advanced Materials Engineering at Sejong University, where he has been serving since 2006. Prior to his academic appointment, he worked as a Principal Researcher at Samsung Advanced Institute of Technology from 1999 to 2006 and served as Director of the national Resistive RAM program under the Tera-level nano-devices initiative from 2001 to 2006. Education: Ph.D. (1997) from SUNY at Stony Brook M.S. (1992) from Stevens Institute of Technology M.S. (1988) and B.S. (1985) from Kwangwoon University Professor Kim's research focuses on advanced magnetic materials and devices, with particular emphasis on magnetic sensors utilizing Giant Magnetoresistance (GMR), Tunneling Magnetoresistance (TMR), and the Spontaneous Hall effect. His work encompasses both soft and hard magnetic thin films as well as Magnetic Random Access Memory (MRAM) technologies. His fingerprint analysis reveals deep expertise in Magnetic Tunnel Junction Engineering, Thin Films, Anisotropy, and Tunneling Magnetoresistance. His recent publications demonstrate a strong focus on cutting-edge magnetism research, particularly in 2D van der Waals materials, chiral spin structures in synthetic antiferromagnets, and novel spintronic computing architectures. His work bridges fundamental physics with practical applications in memory and logic devices, showing consistent citation impact with his Nature Materials paper on chiral exchange interactions accumulating 113 Scopus citations. Professor Kim maintains an active research profile with 109 total research outputs documented, including significant media attention with coverage in 16 news outlets and reference in patents. His h-index of 15 with 843 citations reflects substantial scholarly impact in the field of nanomagnetic materials and spintronics. His research has attracted considerable attention in the scientific community with 173 Mendeley readers for his Nature Materials paper, and he has established international collaborations as evidenced by his multi-national co-authorship patterns. His work on reconfigurable logic using magnetic tunnel junctions demonstrates practical applications of his fundamental research in computing technologies.

Carlos Moyses Graca Araujoمشاهده پروفایل

پژوهشگر

• Renewable Energy
• Condensed Matter Physics
• First-Principles Theory
• +۴ مورد دیگر

Dr. Carlos Moyses Graca Araujo is a researcher at Uppsala University's Department of Physics and Astronomy , specializing in Materials Theory . With expertise in condensed matter physics , his work focuses on renewable energy science , particularly battery materials and photo-electro-catalysis . Education : PhD in Condensed Matter Physics (Uppsala University), Postdoc (KTH Royal Institute of Technology, Yale University) His research employs density functional theory , molecular dynamics , and Monte Carlo simulations to investigate energy conversion and storage mechanisms. He has received prestigious awards including the Benzelius Prize , Ångström Premium , and Bjurzon’s Premium for his contributions to materials science. Dr. Araujo's recent publications highlight advancements in aqueous zinc-ion batteries , Li-metal anodes , and polymer solar cells , with a focus on computational materials design and electrocatalyst optimization . His work spans collaborations with institutions like Stanford and Lawrence Berkeley National Laboratory .

Kent-Andre Mardalمشاهده پروفایل

استاد

• Computational Mechanics
• Biomechanical Applications in Medicine
• Brain Clearance During Sleep
• +۵ مورد دیگر

Kent-Andre Mardal is a Professor at the Department of Mathematics , University of Oslo . He specializes in computational mechanics with a strong focus on biomechanical applications in medicine , particularly in modeling brain clearance mechanisms during sleep. His work integrates multi-physics modeling , fluid-structure interaction , and poroelastic couplings to advance understanding of the glymphatic system and cerebrospinal fluid dynamics. Education: PhD (2002) – Simula Research Laboratory Research Interests: Mardal's research spans a wide range of disciplines including: Computational Mechanics – developing robust numerical algorithms for complex physical systems Biomechanical Applications – particularly in neuroscience and medical imaging Brain Clearance During Sleep – modeling the glymphatic system and CSF flow dynamics Multi-Physics Modeling – integrating fluid dynamics, elasticity, and neural networks Finite Element Methods – for accurate and efficient simulations Neural Networks in Scientific Computing – exploring physics-informed neural networks Research Trends from Publications: Mardal's recent publications (2022–2025) demonstrate a clear focus on brain fluid dynamics , particularly the glymphatic system , CSF circulation , and neurodegenerative disease modeling . He employs advanced numerical techniques such as isogeometric analysis , physics-informed neural networks , and parameter-robust preconditioning to solve complex multi-physics problems. His work bridges medical imaging (MRI) with computational modeling to provide insights into brain clearance mechanisms and their impairment in diseases like Alzheimer's. Scientific Awards: No specific awards are mentioned in the provided text. Grants and Projects: Currently, Mardal is the Principal Investigator (PI) of three active research projects: Alzheimer's Physics – exploring the role of fluid dynamics in neurodegeneration Scientific Machine Learning – advancing numerical methods with AI Computational Hydrology – modeling subsurface fluid flow Affiliations and Teams: Mardal was previously a group leader at the Centre of Excellence “Biomedical Computing” at the Simula Research Laboratory. He has authored over 100 papers and several books, and his research homepage is available at https://kent-and.github.io/ .

• Biophysics
• Chemical Physics
• Soft Matter Physics
• +۷ مورد دیگر

Atsuko Takamatsu is a Professor at the School of Advanced Science and Engineering of Waseda University. Her work bridges biophysics, mathematical biology, and nonlinear dynamics through experimental and theoretical studies of biological systems. PhD in Science from Tokyo Institute of Technology Key memberships: Japanese Society for Mathematical Biology, Physical Society of Japan, Biophysical Society of Japan Research Interests focus on: Biological Pattern Formation in Physarum slime mold and cyanobacteria Coupled Oscillator Systems (cilia, cellular oscillations) Cell Competition Dynamics and its role in tissue homeostasis Hydrodynamic Interactions in left-right symmetry determination Article Trends reveal expertise in mathematical modeling of biological networks, with applications to Physarum transport systems, ciliary synchronization, and cellular decision-making. Notable work includes uncovering how minimal ciliary systems generate embryonic symmetry and modeling energy-efficient biological networks. Research Projects funded by Japan Society for the Promotion of Science include studies on: Chrono-health science and irregular lifestyle effects Spatio-temporal oscillation patterns in slime mold Cell competition mechanisms in Drosophila Adaptive network morphology in Physarum Her bio-inspired algorithms (e.g., Physarum-based transport optimization) demonstrate practical applications of biological principles to engineering challenges.

• Environmental dynamic analysis
• Fog deposition
• Cloud
• +۲ مورد دیگر

WANG Yize is an Assistant Professor at Waseda University 's School of Creative Science and Engineering . Holding a Doctor of Engineering degree (2024) from Waseda University, his research focuses on environmental dynamics , particularly airborne microplastics , fog deposition , and cloud chemistry . He actively participates in editorial boards and professional societies like the Japan Society for Environmental Chemistry. Research Highlights : First characterization of microplastics in cloud water at high altitudes Investigations into AMPs as ice nuclei in snowfall Long-term air pollutant deposition trends in Japanese forests (1994–2019) Scientific Awards : SETAC Japan Society Award (2025) for forest soil microplastics study SETAC Japan Society Award (2025) for Fukushima radioactive substance research SETAC Japan Society Award (2024) for snowfall microplastics analysis SETAC Japan Society Award (2024) for Tokyo mountainous streamwater chemistry Academic Contributions : Principal investigator for JSPS-funded projects on microplastic-atmospheric interactions (2024–2027) Peer reviewer for Journal of Hazardous Materials , Atmospheric Research , and Environmental Science & Technology Key participant in Mount Fuji cloudwater monitoring programs since 2017

• Energy Storage and Conversion
• Hydrogen Fuel Cells
• Multi-Scale Modeling
• +۶ مورد دیگر

Aayan Banerjee is an Assistant Professor in the department of Catalytic Processes and Materials, specializing in the design, control, and industrial scaling of advanced chemical and electrochemical technologies. His work integrates operando characterization, performance testing, and multi-scale multi-physics digital twins to address challenges in energy storage and conversion. Research focuses on high-temperature hydrogen fuel cells/electrolysers and redox flow batteries Key methodologies: local operando characterization, multi-scale digital twins, and kinetic modeling Contributions to UN Sustainable Development Goals (SDGs) in energy and sustainability His research is showcased at the SEED lab , which explores industrial applications of multi-scale modeling, reaction kinetics, and transport phenomena. Recent projects include hierarchical modeling of solid oxide cells and techno-economic optimization of electrolysis architectures. The majority of his publications (2014–2023) center on solid oxide fuel cells, multi-scale modeling, and hydrogen energy systems, with additional work on methane coupling, polymer-membrane interactions, and Li-ion battery cathodes. He has served as an examiner for PhD projects on artificial photosynthesis and low-temperature electrolysis, collaborating with institutions across Europe. His expertise spans chemical technology, multi-physics modeling, and sustainable energy systems, with no explicit scientific awards mentioned in the dataset.