جست‌وجوی استاد و پژوهشگر

• Fluid network dynamics
• Partial differential equation solvers
• Hydraulic network characterization
• +۴ مورد دیگر

Dr. Aaron Zecchin is a Senior Lecturer in Environmental Engineering at the University of Adelaide, affiliated with the School of Architecture and Civil Engineering under the Faculty of Sciences, Engineering and Technology. His research focuses on fluid network dynamics, hydraulic system modeling, and evolutionary algorithm applications in engineering problems. His expertise includes transient analysis in pipeline networks, fault detection using statistical methods, and optimization techniques for water distribution systems. He actively investigates fluid-structure interactions, Laplace-domain characterizations, and sparse linear solvers for steady-state simulations. His work integrates advanced computational methods with practical engineering challenges, emphasizing infrastructure resilience and sustainability. Research Themes: Hydraulic transients, pipeline condition assessment, system identification Key Tools: Method of characteristics, Kalman filtering, ant colony optimization Applications: Water distribution systems, flood mitigation, wildfire risk modeling Recent publications emphasize anomaly detection in pipe systems, burn probability prediction using dimensionality reduction, and optimizing municipal infrastructure rehabilitation. His work bridges theoretical modeling with real-world infrastructure challenges, contributing to safer and more sustainable engineering solutions.

• Signal and Information Processing
• Energy Disaggregation
• Non-Intrusive Load Monitoring (NILM)
• +۱۵ مورد دیگر

Professor Vladimir Stankovic is a leading academic in the Department of Electronic and Electrical Engineering within the Faculty of Engineering at the University of Strathclyde, UK. His research focuses on signal and information processing to tackle global sustainability challenges such as energy efficiency, net-zero transition, electrification of transport, and landslide monitoring. He is actively involved in multiple high-impact research initiatives and holds leadership roles in major AI and engineering conferences. PhD (Dr-Ing), University of Leipzig, Germany, 2003 MEng (Dipl-Ing), Electrical Engineering, University of Belgrade, 2000 His research interests center on applying signal processing and AI to smart homes, micro-seismic analysis, health monitoring, remote sensing, and computer vision. He has developed innovative methods in energy disaggregation, graph signal processing, and interpretable machine learning. His work bridges engineering with sustainability, contributing to UN Sustainable Development Goals. He teaches core courses including image/video processing, communication systems, signals and systems, and information theory. The recent publications highlight a strong trend in applying AI and machine learning to energy analytics in buildings and agriculture (e.g., dairy farms), landslide monitoring using seismic data, and equitable EV charging planning. These works leverage advanced techniques such as graph neural networks, transformers, and human-in-the-loop deep learning, demonstrating a consistent focus on real-world impact, interpretability, and sustainability. He has received notable scientific awards: Finalist of the World first 10K Best paper Award (Top 3%) IEEE Multimedia Signal Processing Workshop (MMSP) top 10% best paper award 2010 Professor Stankovic has been a Principal or Co-Investigator on numerous research and knowledge exchange projects, including JED-AIs (Justice, Energy, Demand flexibility and AI for Sustainability), REMINDA, and multiple Digital Dairy Chain Innovation Vouchers. These projects are funded by EPSRC and other UKRI councils, focusing on AI-driven energy analytics, community energy sharing, and sustainable farming. He serves in key editorial roles, including Area Editor for IEEE Transactions on Communications and Associate Editor for Nature Scientific Data, and has organized major conferences such as IEEE MMSP 2017 and IJCNN 2025. He is actively involved in research teams and collaborative networks focused on AI for sustainability, energy systems, and environmental monitoring. His lab works on datasets such as the Plegma Dataset and REFIT, supporting open science in energy and seismic analytics.

• Geophysical Engineering
• Applied Geophysics
• Electro Magnetic and Electrical Methods
• +۱۱ مورد دیگر

Özgür Aktürk is an Assistant Professor in the Department of Geological Engineering at Akdeniz University, Faculty of Engineering, where he has been serving since 2011. His academic journey began at Ankara University, continued with a master's and doctorate at Middle East Technical University, and includes research experience at the University of Tennessee. He is actively involved in teaching and research in geotechnical and geophysical engineering, with strong industry collaboration through his R&D company. Doctorate: Middle East Technical University, 2010 Undergraduate: Ankara University, 2001 His research interests span Applied Geophysics , Engineering Geology , Electrical Resistivity Imaging , Soil and Rock Mechanics , Seismic Hazard Assessment , and Numerical Modeling . He applies these to practical problems such as tunnel stability, dam safety, karst investigations, and urban infrastructure. His work integrates field geophysics with computational models to assess geotechnical risks. The recent articles reflect a consistent focus on geophysical subsurface characterization, particularly using electrical resistivity methods, and geotechnical stability analysis. Key themes include urban geophysics for subway systems , karst cavity detection , soil liquefaction , and statistical analysis of geological materials . His collaborations with researchers like V. Doyuran, K. Kayabalı, and F. Uçar highlight interdisciplinary and applied research trends. He has supervised multiple master's students on topics related to tunnel deformation, landslide hazards, and geophysical site assessment. Although no formal scientific awards are listed, his extensive publication record and participation in funded projects indicate active research engagement. He is a member of the Engineering Geology Association and the Chamber of Geological Engineers, and has served on thesis juries. Özgür Aktürk has founded JeoTasarım Proje ve Mühendislik under Akdeniz University TEKNOKENT, demonstrating a commitment to applied research and technology transfer. His work bridges academic research and practical engineering solutions, particularly in water resources and geohazard mitigation projects.

Ivo Furnoمشاهده پروفایل

استاد مدعو

• Plasma Physics
• Fusion Energy
• Applied Physics
• +۳ مورد دیگر

Ivo Furno is an Adjunct Professor at the École Polytechnique Fédérale de Lausanne (EPFL) within the School of Basic Sciences ( SB ) and affiliated with the Swiss Plasma Center ( SPC ). He holds a joint appointment with the SPH-ENS unit and previously contributed to EDPY-ENS teaching initiatives. His research spans fundamental plasma physics, tokamak experiments (TCV program), and applied plasma technologies including plasma agriculture. Key Collaborations: AWAKE Run 2, DEMO Neutral Beam Injectors, SPIDER, RAID linear device Teaching: General Physics (Thermodynamics), Plasma Diagnostics in Tokamaks Research focuses on plasma turbulence , negative ion sources , self-modulation of relativistic proton bunches , and plasma-seed treatments . His work includes experimental validation of edge turbulence codes , microwave interferometer design , and helicon plasma characterization for fusion applications. Publications highlight 3D plasma dynamics , Langmuir probe analysis , and ion transport phenomena . He has supervised numerous PhD students, including those working on fast ion transport , negative hydrogen ion dynamics , and millimeter-wave diagnostics . Scientific Awards: No explicit awards listed in the data. Students & Collaborations: Mentored PhD candidates such as Riccardo Agnello (helicon plasmas), Rita Agus (plasma diagnostics), and Fabio Avino (dielectric barrier discharges). Past advisees include researchers in plasma agriculture (e.g., Alexandra Waskow) and tokamak experiments (e.g., Federico Nespoli).

Rémy Lequesneمشاهده پروفایل

استاد

• Structural Engineering
• Reinforced Concrete Systems
• Earthquake-Resistant Design
• +۷ مورد دیگر

Rémy Lequesne serves as Professor and Associate Dean for Faculty and Staff Affairs in the Civil, Environmental and Architectural Engineering (CEAE) department at the University of Kansas. With over a decade of experience since joining the faculty in 2013, he leads research in structural engineering with a focus on reinforced concrete systems and earthquake-resistant design. Dr. Lequesne earned his educational credentials from the University of Michigan, completing his B.S. in Civil Engineering in 2005, M.S. in Civil Engineering in 2007, and Ph.D. in Structural Engineering in 2011. His academic journey has positioned him as a leading researcher in concrete mechanics and seismic design. His research program at the LeQuenne Lab investigates reinforced concrete mechanics through experiments, numerical models, and field data to improve structural design. His work specifically targets earthquake-resistant design, identification and mitigation of structural vulnerabilities, and the use of advanced materials including fiber reinforced concrete and high-strength steel. Recent research has expanded into emergent technologies such as 3D printing applications in construction and AI-based damage detection methods. Analysis of his recent publications reveals a strong focus on high-strength materials in concrete structures, with particular attention to coupling beams, walls, and seismic performance. His work bridges theoretical mechanics with practical applications, often involving large-scale testing and direct contributions to building codes through the American Concrete Institute. Extensive research on high-strength steel reinforcement applications Studies on structural performance after disasters including the 2019 EF4 Linwood, Kansas tornado Investigations into earthquake-resistant wall systems Development of improved design methodologies for concrete structures Dr. Lequesne actively mentors graduate students, with several appearing as co-authors on his publications. His research is supported by various funding sources including the University of Kansas Center for Research, Electrical Power Research Institute, and the Engineer Research and Development Center Geotechnical and Structures Laboratory. The LeQuenne Lab serves as the hub for his research activities, focusing on experimental testing of reinforced concrete systems. The lab's work has direct applications to improving building safety in seismic and tornado-prone regions, with recent studies examining performance after the 2019 EF4 Linwood, Kansas tornado and the 2023 South-East Turkey earthquake sequence.

Aziz Diniaمشاهده پروفایل

استاد

• Materials Science
• Photovoltaics
• Thin Film Deposition
• +۳ مورد دیگر

Aziz Dinia is a Professor of Inorganic Materials Chemistry at the European School of Chemistry, Polymers and Materials of Strasbourg (ECPM), University of Strasbourg, and is affiliated with the Institute of Physics and Chemistry of Materials of Strasbourg (IPCMS). He has held this position since 1999 and previously served as an Assistant Professor at the University of Strasbourg starting in 1989. His research focuses on functional oxide materials for energy applications, particularly photovoltaic technologies. Dr. Dinia earned his PhD in 1987 from the University of Grenoble, Center of Nuclear Study of Grenoble (CENG), with a dissertation on "Study of the magnetic and superconducting properties of Chevrel phases compounds" under Dr. Jean Rossat-Mignod. In 1995, he received accreditation to supervise research from the University of Strasbourg for his work on "structural, magnetic and transport properties of Co/Ru multilayers." Professor Dinia's research centers on functional oxide thin films with emphasis on photovoltaic applications. His work spans: functional oxides in thin films, thin film oxides for photonic conversion, transparent conducting oxides for photovoltaic applications, and perovskite oxides and hybrid organic/inorganic materials for photovoltaics. His group investigates materials like ZnO, SnO2, BiFeO3, and CZTS thin films, exploring structural, optical, and electrical properties for solar energy conversion. Analysis of recent publications reveals strong focus on silicon clathrate films, ferroelectric oxides (Bi2FeCrO6, BiFeO3), and transparent conducting oxides. His work demonstrates expertise in thin film deposition techniques including spray pyrolysis, magnetron sputtering, and solution processing. A recurring theme is material modification through doping (Yb, Er, Nd) and ion implantation to enhance photovoltaic performance. Professor Dinia maintains extensive collaborations with University of Strasbourg colleagues, IPCMS researchers, and various Moroccan institutions. His research has been supported by numerous grants focused on renewable energy materials development, though specific grant details aren't provided. Based at IPCMS in Strasbourg, Professor Dinia works within a multidisciplinary research environment combining chemistry, physics, and materials science. His laboratory maintains capabilities for thin film deposition, materials characterization, and photovoltaic device fabrication and testing, supporting both fundamental research and applied technology development.

• Scientific Computing
• Numerical Analysis
• Numerical Methods for PDE
• +۴ مورد دیگر

Professor Talal Rahman is a faculty member at the Western Norway University of Applied Sciences, where he works in the Department of Computer Science, Electrical Engineering and Mathematical Sciences. His office is located at Bergen KRONSTAD D305, and he can be reached at phone number +47 55 58 72 46. Professor Rahman's research spans several key areas in computational mathematics and scientific computing. His primary research interests include: Scientific Computing Numerical Analysis Numerical Methods for Partial Differential Equations Preconditioning Finite Element with Domain Decomposition Methods Variational Image Processing Artificial Intelligence and Machine Learning applications Professor Rahman's extensive publication record demonstrates a strong focus on domain decomposition methods, particularly Schwarz methods and their applications to multiscale problems. His recent work shows an increasing integration of machine learning techniques with traditional numerical methods, as evidenced by publications on neural network applications for environmental modeling and capelin migration patterns. His research also extends to biomedical applications, including computational analysis of biodegradable materials and bone tissue engineering scaffolds. He has made significant contributions to the development of adaptive preconditioners and parallel algorithms for solving complex numerical problems, with his work on the TV-Stokes model for image processing representing an important contribution to the field of variational image processing. Professor Rahman has supervised numerous research projects and students, though specific student names are not provided in the available information. His research appears to be supported by grants related to computational science and engineering, though specific grant details are not mentioned in the provided text. Based on his research areas, Professor Rahman likely collaborates with various research groups focused on computational science, with potential connections to biomedical engineering labs and environmental research teams studying the Barents Sea ecosystem.

Robert Bergevinمشاهده پروفایل

استاد

• Cognitive Computer Vision
• Pattern Recognition
• Artificial Vision
• +۷ مورد دیگر

Robert Bergevin is a Full Professor in the Department of Electrical Engineering and Computer Engineering at Laval University's Faculty of Science and Engineering, where he has been employed since 1990 and achieved full professor status in 2001. He is also a member of CeRVIM (Research Center in Robotics, Vision and Machine Intelligence) and actively participates in graduate recruitment. Dr. Bergevin's educational background includes: Ph.D. in Electrical Engineering from McGill University (1985-1990), with thesis titled "Primal Access Recognition of Visual Objects" under Professor Martin D. Levine M.Sc.A. in Biomedical Engineering from École Polytechnique de Montréal (1982-1984), with thesis on "Modeling and numerical simulation of a nuclear magnetic resonance imaging system" under Professor Robert Guardo B.Sc.A. in Electrical Engineering (Communications specialty) from École Polytechnique de Montréal (1978-1982) Professor Bergevin's research spans cognitive computer vision, pattern recognition, and information systems design methodologies. His work is guided by a unique methodology that progresses "from the general to the particular" to achieve "simply communicable and universally applicable understanding." He has been a researcher in cognitive computer vision since 1985, with particular focus on ontology, methodology, and categorization. His research interests include Ontology of Cognitive Digital Vision, Cognitive Digital Vision Development Methodology, Categorization in cognitive digital vision, Analysis and understanding of images and videos, and Understandable artificial intelligence. As a generalist, he is also a proponent of the science of global anticipatory design (R. Buckminster Fuller) and general semantics (Alfred Korzybski). Analysis of Professor Bergevin's recent publications reveals a strong focus on video anomaly detection, carried object detection, and human activity recognition. His work consistently applies cognitive principles to computer vision problems, often developing novel methodologies for segmentation, tracking, and recognition. The research shows progression from foundational work on image analysis to more complex spatio-temporal understanding of video content, with increasing integration of deep learning techniques in recent years while maintaining a focus on interpretable and cognitively-inspired approaches. Among his professional recognitions: Teaching Star, Faculty of Science and Engineering (2019, 2012) Professor Bergevin has supervised numerous graduate students throughout his career, including four PhD candidates and four Master's students in recent years. His current research includes the "Cyber-physical systems and materialized machine intelligence" project funded by Université Laval, École de technologie supérieure, and Fonds de recherche du Québec - Nature and technologies, running from 2019 to 2026. He was also the director of the bachelor's program in computer engineering from 2001 to 2010 and served as Area Editor for the journal Computer Vision and Image Understanding from 2002 to 2017. As a member of CeRVIM (Research Center in Robotics, Vision and Machine Intelligence), Professor Bergevin collaborates with researchers across multiple disciplines to advance the fields of robotics, computer vision, and machine intelligence. His work bridges theoretical foundations with practical applications, particularly in the analysis of human activities and object recognition in complex visual scenes.

Alireza Khaniمشاهده پروفایل

دانشیار

• Transportation Engineering
• Public Transit Systems
• Network Optimization
• +۵ مورد دیگر

Alireza Khani is an Associate Professor in the Department of Civil, Environmental, and Geo-Engineering at the University of Minnesota's College of Engineering. His research focuses on modeling the impacts of emerging technologies on public transit systems and optimizing these systems for greater efficiency and reliability. Dr. Khani actively contributes to transportation research through numerous publications and substantial grant-funded projects. Dr. Khani's research interests center on transportation engineering with a particular emphasis on public transit systems. His work utilizes network modeling and optimization techniques to integrate public transit with autonomous mobility-on-demand services and electric fleets using renewable energy. His research spans urban mobility challenges, focusing on sustainable transportation solutions that address both passenger and freight transportation needs. His work increasingly incorporates machine learning techniques to analyze travel behavior and optimize transportation networks. His recent publications demonstrate a strong focus on electric bus systems, autonomous mobility-on-demand services, and optimization of transit networks. The research trends show progression from traditional transit modeling to integrating cutting-edge technologies like AI algorithms and autonomous vehicles. His work addresses critical transportation challenges including last-mile connectivity, rural transit solutions, and the transition to electric fleets, with growing emphasis on data-driven approaches to transportation planning. Dr. Khani actively mentors students and seeks undergraduate researchers for software development projects related to transportation systems. His research is supported by multiple substantial grants including projects funded by the National Science Foundation and the Minnesota Department of Transportation. Current projects include MobiliSlice: A Personalized Car-sharing System for Smart Urban Mobility , Estimating Likely Mode Shift and VMT Reduction Potential using TBI Data and AI Algorithms , and Transitioning to EV Fleets: Best Practices and A Decision Tool . Dr. Khani leads the UMN Transit research group, which focuses on developing mathematical, computational, and data analytic tools to evaluate and optimize transit systems. The group's research activities center on creating innovative solutions for modern transportation challenges, particularly those involving the integration of emerging technologies with traditional public transit infrastructure. The lab maintains strong connections with transportation agencies and actively contributes to practical solutions for real-world transit problems.

• Naval Architecture
• Yacht Design
• Fluid-Structure Interaction
• +۳ مورد دیگر

Olivia D'ubaldo serves as a Contract Professor in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering at the University of Genoa, specializing in yacht design and naval architecture. She currently teaches YACHT RIGGING (code 66397) for the Master's Degree in YACHT DESIGN for both the 2024-2025 and upcoming 2025-2026 academic years. Her research focuses on the complex interaction between fluid dynamics and structural mechanics in marine applications, particularly for high-performance sailing yachts. Dr. D'ubaldo's work addresses critical challenges in yacht appendage design where aero/hydro-elastic instabilities can significantly impact performance and safety. Her publication record demonstrates expertise in experimental hydrofoil testing, model design procedures for low mass ratio systems, and computational simulations of fluid-structure interactions. These research areas represent cutting-edge approaches to optimizing yacht performance through advanced engineering principles. As a Contract Professor, she brings specialized industry knowledge to the academic environment, bridging theoretical engineering concepts with practical yacht design applications.

Barb Cutlerمشاهده پروفایل

دانشیار

• Computer Graphics
• Interactive Visualization
• Computational Geometry
• +۳ مورد دیگر

Barb Cutler is an Associate Professor in the Computer Science Department at Rensselaer Polytechnic Institute (RPI) and an affiliated faculty member at EMPAC (Experimental Media and Performing Arts Center). She specializes in computer graphics, interactive visualization, computational geometry, and open-source educational software. Previously, she was a student and Post-Doctoral Lecturer at MIT's Department of Electrical Engineering and Computer Science. Education: PhD in Electrical Engineering and Computer Science, MIT, August 2003 MEng in Electrical Engineering and Computer Science, MIT, June 1999 Research Interests: Her research spans computer graphics , interactive visualization , computational geometry , and the development of open-source educational tools . She has made significant contributions to architectural daylighting design, spatially augmented reality, and procedural modeling. Her work often integrates advanced visualization techniques with practical applications in education and architecture. Scientific Awards: NSF Early CAREER Award (2009) Rensselaer School of Science Outstanding Teaching Award (2017) Rensselaer Trustees' Outstanding Teacher Award (2019) Teaching & Advising: Barb Cutler has taught a wide range of courses including Data Structures, Advanced Computer Graphics, Interactive Visualization, and Computational Geometry. She has advised numerous PhD and MS students, many of whom have gone on to positions at leading companies and institutions. She is currently advising Evan Maicus, a PhD student in Computer Science. Lab & Projects: She leads the development of Submitty , an open-source homework submission, autograding, and TA grading system used widely in computer science education. Her lab focuses on innovative educational technologies and advanced visualization systems.

Alex Whiteمشاهده پروفایل

مدرس ارشد

• Thermofluids
• Two-Phase Flow
• Thermodynamics
• +۶ مورد دیگر

Dr. Alex White is a Senior Lecturer in Thermofluids at the Department of Engineering, Cambridge University, and a Fellow and Director of Studies at Peterhouse. He earned his undergraduate and PhD degrees from King's College, Cambridge, and conducted postdoctoral research in Cambridge, Lyon, and Toulouse before returning to Cambridge in 2000 as part of the Energy Group. His research focuses on two-phase flow (vapour-droplet flows), thermodynamics of power generation, Computational Fluid Dynamics (CFD), and heat pumps. His work includes theoretical and numerical studies on warm dense matter, electron transport, and energy storage systems like pumped thermal and compressed air storage. Recent publications emphasize warm dense matter physics, inertial confinement fusion, and thermal energy storage innovations. His theoretical analyses and simulations span high-energy-density plasmas, nonlocal electron stopping power, and hybrid energy systems. While no scientific awards are documented, his contributions to thermofluids and extreme condition physics are significant.

• Artificial Intelligence
• Strategic Reasoning in Multi-Agent Systems
• Formal Verification
• +۱۰ مورد دیگر

Aniello Murano is a Professor in Computer Science at the Department of Electrical Engineering and Information Technology of the University of Naples Federico II. He serves as Scientific Director of the ASTREA (Automated Strategic REAsoning) Laboratory and has been actively involved in numerous research projects including H2020-MSCA project SEAL as Principal Coordinator and PNRR Research Unit Coordinator on Resilient Strategic Reasoning in AI (2023-2025). His primary research interests focus on Artificial Intelligence, Formal Aspects for Strategic Reasoning in Multi-Agent Systems under Perfect and Imperfect Information, Specification, Verification, and Synthesis of Reactive Systems, Model Checking and Module Checking, Formal Languages, Automata Theory, Real-time Systems, Pushdown and Hierarchical Systems, Temporal and Modal Logics, Logics for Strategic Reasoning in AI, Game Theory, Parity Games, Solution Concepts, and Automated Mechanism Design. His work bridges theoretical computer science with practical applications in AI systems. Murano has published extensively in top-tier venues, with recent publications spanning KR, IJCAI, AAAI, AAMAS, and other premier conferences. His research shows strong trends in strategic reasoning frameworks, verification techniques for multi-agent systems, and applications of game theory to mechanism design. He has made significant contributions to Strategy Logic and its extensions. JPMorgan Faculty Research Award 2022 Best Paper Award PRIMA 2015 Vigevani Research Project Prize 2010 In KR Top 100, best AI-2000 world researchers Italian Scientific Abilitation as Full Professor in Engineering Computer Science (March 2018) Italian Scientific Abilitation as Full Professor in Computer Science (April 2017) Royal Society Award 2016 Murano has supervised numerous PhD students including Silvia Stranieri, Antonio Di Stasio, Vadim Malvone, and Giuseppe Perelli. He has served as Program Chair for major conferences including ECAI 2025 (Program co-chair), KR 2024 (Area chair), and CSL 2024. His research has been supported by significant grants including Horizon 2020 projects, JPMorgan funding, and Italian national research programs. He leads the ASTREA Laboratory focused on automated strategic reasoning and has been instrumental in establishing collaborative research initiatives with institutions worldwide.

• Food Engineering
• Nonthermal Food Processing
• Food Preservation Technologies
• +۴ مورد دیگر

Professor Gustavo Barbosa-Cánovas is a leading figure in Food Engineering at Washington State University (WSU), where he serves as Director of the Center for Nonthermal Processing of Food (CNPF). His work focuses on advancing nonthermal technologies for food preservation, balancing safety, quality, and sustainability. B.S. in Mechanical Engineering, University of Uruguay M.S. and Ph.D. in Food Engineering, University of Massachusetts-Amherst (Fulbright Scholar) Honoris Causa Doctorate, Polytechnic University of Cartagena, Spain Dr. Barbosa-Cánovas specializes in nonthermal methods such as High Hydrostatic Pressure (HHP), Pulsed Electric Fields (PEF), and Ultrasound (US), which aim to maintain food quality while extending shelf life and reducing energy use. His research emphasizes microbial and enzyme inactivation, physical properties of foods, and powder technology. His laboratory, the CNPF at WSU, is the only facility of its kind in the U.S., fostering interdisciplinary collaboration and hosting visiting scholars. It plays a critical role in solving technical challenges in modern food processing. IFT Nicholas Appert Award (Highest Award in Food Science and Technology) IFT International Award Fulbright and JSPS Fellowships Member of the Uruguayan Academy of Engineering Dr. Barbosa-Cánovas has advised numerous graduate students and postdocs, including Daniela Bermúdez-Aguirre, Pablo Juliano, and Federico Harte. He has also served as Editor-in-Chief for multiple journals and book series, contributing to global food science discourse.

Mohammad Zubairمشاهده پروفایل

استاد

• High performance computing
• digital libraries
• autonomic computing
• +۳ مورد دیگر

Mohammad Zubair is a Professor in the Department of Computer Science at Old Dominion University's College of Sciences, specializing in high performance computing, digital libraries, autonomic computing, and peer-to-peer networks. His work bridges scientific computing and information systems with significant federal and industry collaborations. Education: Ph.D. in Computer Science, Indian Institute of Technology Delhi (1987) B.S. in Electrical & Electronics Engineering, University of Delhi (1981) Research Interests: Dr. Zubair's expertise centers on high performance computing for scientific applications and large scale data analytics. He develops scalable algorithms for scientific simulations (e.g., particle physics, structural health monitoring) and advances digital library systems through autonomic computing, collaborative classification, and metadata extraction. His work integrates parallel computing with domain-specific challenges in finance, physics, and digital preservation. Publication Trends: His recent publications (2017-2008) show strong focus on GPU-accelerated scientific computing (particle colliders, structural monitoring) and computational finance (binomial option pricing), while maintaining digital library research in collaborative classification and metadata extraction. The work increasingly addresses energy efficiency in cloud systems and leverages parallel architectures from multicore CPUs to GPUs. Scientific Awards: IBM Faculty Award (2006) IBM Faculty Award (2005) Grants and Funding: Dr. Zubair has secured over $800,000 in research funding since 2004, including projects like 'Design AMD Impl Scalable Opt Kernels for Lrg Sc Simu USN Fund3d On Emer' ($24,890, 2017-2018), 'Graduate Research Award Program On Public Sector Aviation Issues' ($35,519, 2016-2018), and foundational digital library work with the Library of Congress and NASA. He frequently collaborates with K. J. Maly and R. Mukkamala on autonomic systems and metadata extraction. Labs and Teams: His research integrates with ODU's high performance computing initiatives and digital library projects, particularly through collaborations with federal agencies (NASA, Library of Congress) and industry partners like IBM. Current work focuses on GPU-accelerated scientific simulations and energy-efficient cloud management systems.