جستجوی استاد راهنمای دانشگاهی

• Marine Biology
• Ocean Acidification
• Plankton Ecology
• +۳ مورد دیگر

Maria Alguero-Muniz is a Researcher at the University of Glasgow , affiliated with the School of Biodiversity, One Health & Veterinary Medicine . Her work focuses on ocean acidification impacts , plankton community dynamics , and marine ecosystem responses to environmental stressors. Her research spans plankton physiology , trophic interactions , and climate change adaptation in marine systems. Recent projects include eDNA metabarcoding for aquaculture monitoring and upwelling simulations to study carbon cycling. Maria's publications (2012–2025) reveal a thematic focus on marine biogeochemistry , zooplankton ecology , and novel species taxonomy . Key collaborations include institutions studying pelagic food webs and CO2-driven ecological shifts . Scientific awards include funding from The Royal Society of Edinburgh (2021–2022) for planktonic threat monitoring in salmon aquaculture. Her work has been published in Nature Climate Change , Global Biogeochemical Cycles , and Frontiers in Marine Science .

Matthew Adamsمشاهده پروفایل

دانشیار

• Civil Engineering
• Sustainable Construction Materials
• Concrete Technology
• +۳ مورد دیگر

Matthew Adams is an Associate Professor in the Department of Civil & Environmental Engineering at New Jersey Institute of Technology (NJIT). He holds a B.S. in Civil Engineering from the University of New Hampshire (2006) and M.S. (2012) and Ph.D. (2016) degrees in Civil Engineering from Oregon State University. His research focuses on sustainable construction materials, durability of infrastructure, and advanced cementitious systems. He is a Fellow of the American Concrete Institute and a member of ASTM International. Awards include the 2021 Excellence in Upper-Level Undergraduate Teaching Award (NJIT), 2020 Richard P. Nathan Fellowship (Rockefeller Institute), and 2019 ASTM Emerging Professional Award. His work emphasizes recycled materials, low-carbon concrete, and corrosion-resistant systems. Adams leads the NJIT Materials Lab (https://sites.google.com/njit.edu/njitmatslab/home), focusing on experimental and computational studies of material behavior under environmental and mechanical stresses. His research integrates numerical modeling, data-driven approaches, and sustainability principles to address challenges in civil infrastructure longevity.

Marco Molinariمشاهده پروفایل

دانشیار

• Computational Chemistry
• Materials Science
• Nanoparticle Morphology
• +۳ مورد دیگر

Marco Molinari is an Associate Professor (Reader) at the University of Huddersfield, affiliated with the School of Applied Sciences and the Department of Physical and Life Sciences. He is a member of the Centre for Functional Materials and associate member of the Pharmaceutics and Drug Delivery Centre and Structural, Molecular and Dynamic Modelling Centre. His research focuses on computational chemistry and materials science, particularly energy and environmental materials, surface science, and nanomaterials. Education: BSc from the University of Pavia (Italy, 2006), PhD in computational chemistry (2009) through a collaboration between the University of Pavia and Bath (UK). Postdoctoral research at the University of Bath, funded by the EPSRC, focused on surface science and materials chemistry. Research interests include computational modeling of mineral and oxide materials, surface adsorption and reactivity, nanoparticle morphology, and catalytic properties. His work contributes to UN Sustainable Development Goals related to clean energy and environmental protection. He leads projects such as 'Computational Design and Engineering of Metal Oxide Nanozymes' (2018–2019) and 'NanoCeO2: Design of CeO2 Nanostructures with Enhanced Catalytic Properties' (2017–2017). Publications span over 100 peer-reviewed articles, with recent studies on cerium oxide nanoparticles, surface engineering, and computational methods like density functional theory. He actively participates in conferences and serves on committees like the EPSRC-funded Materials Chemistry Consortium and the RSC local section. Molinari supervises PhD students and collaborates on datasets and software tools like SurfinPy for phase diagram generation. His research bridges computational modeling, experimental validation, and real-world applications in energy storage, environmental remediation, and biomedical materials.

• Theoretical Chemistry
• Computational Chemistry
• Polymer Chemistry
• +۵ مورد دیگر

Dr. Beverly Stewart is a Lecturer in the Theoretical & Computational Chemistry Area at the School of Chemistry & Biosciences, part of the Faculty of Life Sciences at the University of Bradford. Her research focuses on computational chemistry, polymer chemistry, and photonic devices, with particular emphasis on self-assembly processes, high-pressure material behavior, and nanotechnology applications. She has contributed to advancements in conjugated polymers, surfactant interactions, and materials science through experimental and computational methodologies. Her work explores the synthesis and characterization of novel materials, including phosphiranium salts and functional polymers for optoelectronic applications. Notable projects include studies on 3D fabrication with integrated electronics, high-pressure phase transitions in organic semiconductors, and the design of photonic devices. Dr. Stewart’s research frequently intersects with nanotechnology, aiming to develop functional materials with practical applications in sensors and electronics. Dr. Stewart has published extensively on topics such as molecular dynamics simulations of polymer self-assembly, high-pressure chemistry of thiophene derivatives, and the synthesis of air-stable primary phosphanes. Her articles highlight trends in materials design, including the optimization of electronic and photonic properties through structural modifications and environmental conditions. While no specific awards are listed, her contributions to polymer science and computational chemistry reflect a strong research trajectory. She collaborates on interdisciplinary projects, though specific grants or lab affiliations are not detailed in the provided text.

• Experimental astroparticle physics
• Dark matter detection
• WIMP detection
• +۴ مورد دیگر

Matthew Szydagis is an Associate Professor in the Department of Physics at the University at Albany, State University of New York, where he conducts cutting-edge research in experimental astroparticle physics with a focus on dark matter detection. Education: PhD, University of Chicago, 2010 Postdoctoral Associate, University of California Davis, 2010-2014 Dr. Szydagis leads research efforts centered around the LZ (LUX-ZEPLIN) Dark Matter Experiment, the world's largest direct dark matter search project operating at the Sanford Underground Research Facility. His expertise lies in the physics of two-phase Xenon time-projection chambers and the development of sophisticated Monte Carlo simulation techniques to understand detector responses. In 2011, he created the NEST (Noble Element Simulation Technique) software package, which has become an essential tool for the broader scientific community working with noble element detectors. His research spans multiple disciplines including particle physics, astrophysics, and computational physics, with applications extending beyond dark matter research into neutrino physics and medical physics. Dr. Szydagis is an active member of the international LZ collaboration and leads the Dark Matter Research Group at the University at Albany. His work contributes significantly to establishing the world's most sensitive limits on dark matter interactions across a wide range of particle masses.

Sharmin Sultanaمشاهده پروفایل

استادیار

• Multimodal Image Processing
• Artificial Intelligence
• Computer Vision
• +۳ مورد دیگر

Sharmin Sultana, PhD, is an Assistant Professor in the Department of Information Sciences and Technology at George Mason University's College of Engineering and Computing. Her research focuses on developing advanced computational methods for medical imaging, particularly in artificial intelligence, computer vision, and deep learning applications to improve healthcare diagnostics and treatment. PhD, Computational Modeling and Simulation, Old Dominion University (2017) Postdoctoral Research Fellow, Radiation and Oncology, Johns Hopkins University School of Medicine (2017–2020) MS and BS, Computer Science and Engineering, University of Dhaka, Bangladesh Dr. Sultana specializes in Multimodal Image Processing , Artificial Intelligence , and Medical Imaging , with a focus on creating AI-driven solutions for biomedical image analysis. Her work includes state-of-the-art techniques for image-guided cancer treatment and multimodal image registration. The 15 most recent publications highlight her contributions to prostate cancer imaging , cranial nerve segmentation , and environmentally sustainable materials . Key methodologies include convolutional neural networks, deformable models, and dual contouring for precise surgical planning and simulation.

Kim Bernardمشاهده پروفایل

استاد

• Polar Zooplankton Ecology
• Marine Ecosystems
• Climate Change Impacts
• +۳ مورد دیگر

Kim Bernard is a Professor at Oregon State University (OSU), affiliated with the College of Earth, Ocean, and Atmospheric Sciences (CEOAS). She leads the Bernard Zooplankton Ecology Lab, focusing on how climate change and anthropogenic factors influence polar zooplankton ecology, particularly Antarctic krill. Her work integrates physical oceanography and ecological dynamics to understand ecosystem responses to environmental changes. Education: BSc(Hons), MSc, and PhD from Rhodes University, South Africa (2001–2007). Her research spans krill physiology, predator-prey interactions, and the role of physical oceanographic features in structuring marine ecosystems. She has pioneered projects like Project SWARM and collaborates on initiatives such as Polar STEAM to enhance public engagement in polar science. Key research areas include krill reproductive biology, humpback whale-krill relationships, and the impacts of climate change on Antarctic ecosystems. Her work emphasizes the importance of subsurface eddies and Lagrangian coherent structures in sustaining biological hotspots. She actively promotes interdisciplinary approaches, bridging science with education and art. Grants and projects include collaborative efforts on Antarctic krill recruitment, ecosystem-based management, and the ecological role of invasive species like Pyrosoma atlanticum. Her lab’s outreach efforts aim to broaden participation in polar research through STEAM collaborations with educators and artists.

• Machine Learning
• Bioinformatics
• Materials Science
• +۷ مورد دیگر

Pengyu Hong is a Professor of Computer Science at Brandeis University's Michtom School of Computer Science and an affiliated faculty member at the Benjamin and Mae Volen National Center for Complex Systems. His expertise spans Machine Learning, Bioinformatics, Materials Science, and FinTech, with a focus on interdisciplinary applications in healthcare, molecular biology, and complex systems analysis. Education: Ph.D. in Computer Science, University of Illinois at Urbana-Champaign M.E. in Computer Science, Tsinghua University B.Eng. in Computer Science, Tsinghua University Research Interests: Hong's lab develops advanced machine learning techniques for analyzing heterogeneous data (images, text, financial data), with notable contributions in glycomaterials analysis, clinical outcome prediction, and active nematics modeling. His work bridges computational methods with biomedical and material science challenges, including NMR spectroscopy analysis and molecular property prediction. Publications: Recent work focuses on machine learning applications in glycan sequencing, fairness analysis in medical algorithms, and optical flow techniques for fluid dynamics. The lab also maintains benchmark datasets like GlycoNMR for carbohydrate analysis. Labs & Teams: Hong leads research at the Volen National Center for Complex Systems, integrating computational approaches with experimental systems biology and materials science.

Vladimir Okhmatovskiمشاهده پروفایل

استاد

• Electromagnetics
• Computational Electromagnetics
• High-Performance Computing
• +۴ مورد دیگر

Dr. Vladimir Okhmatovski is a Full Professor in the Department of Electrical and Computer Engineering at the University of Manitoba, affiliated with the Price Faculty of Engineering. His research focuses on fast algorithms in electromagnetics, quantum computing, and high-performance computing. He holds a Ph.D. from the Moscow Power Engineering Institute and has held academic and industry roles globally. He has received prestigious awards including the 2017 Intel Outstanding Researcher Award. Education: Ph.D., Antennas and Microwave Circuits, Moscow Power Engineering Institute, 1997 M.S., Radiophysics and Electronics, Moscow Power Engineering Institute, 1996 Research Interests: Dr. Okhmatovski develops advanced computational methods for electromagnetics, including tensor train decompositions and quantum algorithms. His work addresses challenges in signal integrity, layered media analysis, and inverse scattering. He leads efforts in applying quantum computing to solve matrix equations and has pioneered fast direct solvers using H-matrices. Awards: 2017 Intel Outstanding Researcher Award 1996 Best Young Scientist Report (VI International Conference on Mathematical Methods in Electromagnetic Theory) 2007 Outstanding ACES Journal Paper Award Advising & Grants: He mentors students in climate change research through collaborations with the Centre for Earth Observation Science. His funded projects include quantum computing applications and Arctic sea ice remote sensing. He chairs technical committees for IEEE MTT-S and AP-S. Labs/Teams: His research group focuses on electromagnetic modeling, quantum algorithms, and layered media analysis. Collaborations include the Churchill Marine Observatory for Arctic studies.

Yunhua Luoمشاهده پروفایل

استاد

• Finite Element Method
• Computational Mechanics
• Composite Materials
• +۴ مورد دیگر

Dr. Yunhua Luo is a Professor & Associate Head (Graduate Program) in the Department of Mechanical Engineering at the University of Manitoba (Price Faculty of Engineering). His expertise lies in computational mechanics, finite element methods, and biomechanical modeling. He holds a PhD from Stockholm, Sweden (1999), a Licentiate (MSc) from Stockholm (1997), and a B.Eng. from Beijing, China (1985). His research focuses on three core areas: Development of advanced finite element methods for composite materials Multilevel biomechanical modeling of bone strength and hip fracture mechanisms Mechanistic analysis of brain injury and helmet design optimization Over 30 years of academic progression includes roles from Research Associate (2000–2006) to full Professor (2019–present). His recent publications (2022–2025) emphasize voxel-based modeling, osteoporotic fracture risk prediction, and helmet performance evaluation. Current research seeks MSc/PhD students in computational micromechanics.

• Materials Science
• Corrosion Engineering
• Electrochemistry
• +۵ مورد دیگر

Prof. Robert Meißner is a Professor at the Department of Surface Physics and Technology at TUHH. His research focuses on molecular simulation techniques applied to corrosion processes, energy storage systems, and nanomaterials. He develops computational tools like ELECTRODE and i-PI for electrochemical and advanced molecular dynamics simulations. His work addresses challenges in magnesium battery performance, structural health monitoring of composite materials, and interfacial phenomena in nanoscale systems. Education details are not explicitly provided in the text, but his professional trajectory reflects extensive academic and industrial experience in materials science. Research interests span from fundamental studies (e.g., water imbibition in nanopores, magnetite oxidation dynamics) to applied innovations (e.g., corrosion protection via layered double hydroxides, data-driven electrolyte design). His recent publications highlight trends in data-driven materials discovery, structural health monitoring via vibro-acoustic methods, and computational prediction of corrosion inhibitors. He collaborates on projects involving graphene-based supercapacitors, epoxy resin curing dynamics, and peptide-surface interactions. Advising and grants: While student names are not listed, his research group actively explores corrosion engineering, battery technology, and nanomaterials. Projects include EU-funded initiatives and industry partnerships. Technical expertise includes ATR-FTIR spectroscopy, molecular dynamics, and machine learning for sparse data scenarios. He leads teams focused on surface science and energy storage, maintaining lab facilities for in situ electrochemical analysis and advanced computational modeling. His work bridges theoretical insights with practical applications in materials durability and energy systems.

Shaghayegh Bagheriمشاهده پروفایل

استادیار

• Advanced Manufacturing
• Multi-functional Materials
• Biomechanics
• +۳ مورد دیگر

Shaghayegh Bagheri is an Assistant Professor in the Department of Mechanical Engineering at George Mason University and an Affiliate Scientist at Toronto Rehabilitation Institute. She specializes in advanced manufacturing of multi-functional materials for healthcare applications, including rehabilitation, injury prevention, and orthopedic implants. Her research integrates biomechanics, material science, and 3D printing techniques. Education: PhD in Mechanical Engineering, Ryerson University (now Toronto Metropolitan University) MSc in Materials Engineering, Ferdowsi University of Mashhad BSc in Materials Engineering, Ferdowsi University of Mashhad Research focuses on composite materials for anti-slip footwear, biomedical implants, and additive manufacturing. Notable projects include surface-textured composites for anti-slip applications and polymer-based bone scaffolds. Her work has been funded by organizations like NEC and supported by awards from the Ontario Centres of Excellence and Mitacs Accelerate. Key Research Trends: Articles emphasize 3D printing parameters, composite material design, and biomechanical analysis of orthopedic implants. Recent studies explore surface-textured composites for slip resistance and lattice structures in PEEK materials. Awards: Ontario Centres of Excellence Federal Economic Development Agency for Southern Ontario Mitacs Accelerate Current projects address surgical fixation methods for acetabular fractures, anti-slip footwear for home care workers, and biomechanical plate designs. She collaborates with Toronto Rehabilitation Institute and iDAPT Centre for advanced rehab research.

Tom Henzingerمشاهده پروفایل

استاد

• Formal Methods
• Software Engineering
• Computer Science
• +۵ مورد دیگر

Tom Henzinger is a Professor at the Institute of Science and Technology Austria (ISTA), leading the Tom Henzinger Group. His research focuses on formal methods to enhance software quality, addressing challenges in concurrent systems, real-time and embedded systems, quantum computing, neural networks, and biochemical reaction networks. He has advised numerous PhD students and postdoctoral researchers, contributing to advancements in these fields. His work emphasizes mathematical rigor in software analysis and verification. Current projects include VAMOS (Middleware for best-effort third-party monitoring) and SPyCoDe (Semantic and Cryptographic Foundations of Security and Privacy by Compositional Design). Past projects involved model checking and runtime verification techniques. Research interests span concurrent software synthesis, quantitative modeling of reactive systems, predictability of real-time systems, and formal methods applied to quantum computation and neural networks. He is also engaged in exploring hardware-optimal solutions for quantum algorithms. Administrative Assistant Ksenja Harpprecht supports the group. Courses taught include 'Formalisms Every Computer Scientist Should Know,' focusing on logics, automata, and semantics. The group hosts regular seminars, such as the Tuesday group seminar and the Wednesday joint formal methods seminar with TU Wien's FORSYTE group.

Clemens V. Verhooselمشاهده پروفایل

دانشیار

• Computational Mechanics
• Isogeometric Analysis
• Fluid Dynamics
• +۵ مورد دیگر

Clemens V. Verhoosel is an Associate Professor in Computational Methods for Model- and Data-Driven Engineering at Eindhoven University of Technology (TU/e). He holds positions in the Department of Mechanical Engineering under the Energy Technology and Fluid Dynamics section, and is affiliated with the EAISI Foundational initiative. His research focuses on scan-based immersed isogeometric analysis, uncertainty quantification, and Bayesian inference for complex engineering problems. He leads the Group Verhoosel and manages the Engineering Mechanics Graduate School since 2018. Education: MSc (Aerospace Engineering, TU Delft, 2005, cum laude PhD, TU Delft, 2009). Postdoctoral research at University of Texas at Austin (2009-2010). Awarded NWO VENI Grant (2011). Research interests include numerical methods for solid mechanics, fluid dynamics, coupled problems, and applications in biomedical engineering (e.g., cardiac mechanics). He develops open-source tools like the Nutils toolkit and collaborates with industry partners such as Evalf Computing. Key contributions include isogeometric analysis for fracture mechanics, phase-field models, and mesh-free simulation workflows. Honors: NWO Veni Award (2011). Teaching includes Advanced Discretization Techniques and Scientific Computing courses. Active in professional activities, including invited talks on cardiac mechanics and computational methods.

Xinzhao Chuمشاهده پروفایل

استاد

• Remote Sensing
• Atmospheric Science
• Space Physics
• +۵ مورد دیگر

Xinzhao Chu is a Professor of Aerospace Engineering Sciences at the University of Colorado Boulder and a Fellow at the Cooperative Institute for Research in Environmental Sciences (CIRES). He holds a Ph.D. and B.S. in Physics and Electrical Engineering from Peking University (1996 and 1991). His research focuses on lidar remote sensing, atmospheric and space sciences, and the dynamics of the mesosphere and lower thermosphere. Chu’s work includes developing novel lidar technologies, studying gravity waves, and exploring space-atmosphere interactions. Affiliations: CIRES Fellow, Department of Aerospace Engineering Sciences Key Roles: Director of the NSF Lidar Consortium, Principal Investigator of multiple grants Research Interests: Lidar instrumentation, atmospheric dynamics, metal layer formation in thermosphere, and climate variability studies. His group has pioneered Antarctic lidar campaigns, including record-breaking 174-hour observations and discoveries of thermospheric Fe layers. Awards & Recognition: CEDAR Prize Lecture Award (2019), MRI and CAREER Awards (2007), and Antarctic Service Medal (2001). His team has consistently won CEDAR Student Poster Competitions. Advisees: Notable students include Zhibin Yu, Weichun Fong, and Cao Chen, who have contributed to groundbreaking lidar data and numerical models. Labs & Projects: Leads the Chu Research Group, developing advanced lidar systems (e.g., OASIS Initiative) and collaborating globally on atmospheric observations. The group operates facilities like the McMurdo Station lidar in Antarctica.