جست‌وجوی استاد و پژوهشگر

• Machine Learning
• Computer Vision
• Data Compression
• +۳ مورد دیگر

Don Adjeroh is a Professor and Associate Chair in the Lane Department of Computer Science and Electrical Engineering at West Virginia University (WVU). He serves as Graduate Coordinator for CS programs and has led multiple NSF-sponsored projects including Bridges in Digital Health and Multi-Scale Integrative Approach to Digital Health . His research focuses span Machine Learning , Bioinformatics , Computational Biology , and Data Compression . NSF CAREER Award recipient Collaborated with institutions like University of Central Florida and University of Canterbury Led workshops on Plant Image Analysis and Long Non-Coding RNA research His academic contributions include co-authoring the book The Burrows Wheeler Transform: Data Compression, Suffix Arrays, and Pattern Matching (Springer, 2008) and developing software tools like BSMP and PSA for data compression and protein family modeling. He teaches graduate-level courses in String Algorithms and Information Theory , with former projects involving undergraduate and graduate students in DNA microarray image processing and 3D video compression research. Key Scientific Awards : NSF CAREER Award NASA-WV Space Consortium funding WV-EPSCOR grants NSF-CITeR support DOD-ONR/DHS/DOJ/NIJ/NHPRC sponsorships

Brahmajee K. Nallamothuمشاهده پروفایل

استاد پژوهشی

• Cardiovascular Medicine
• Precision Health
• Machine Learning
• +۳ مورد دیگر

Brahmajee K. Nallamothu is a Research Professor at the University of Michigan Medical School, specializing in Internal Medicine and serving as Program Director at the Michigan Center for Healthcare Analytics and Medical Prediction (M-CHAMP) . He is affiliated with multidisciplinary centers including the Institute for Healthcare Policy and Innovation (IHPI) , Samuel and Jean Frankel Cardiovascular Center , and the Precision Health Initiative . His research focuses on integrating machine learning into cardiovascular care , addressing disparities in clinical outcomes, and optimizing precision health strategies. Recent work includes validating deep learning algorithms for ECG interpretation and analyzing equity in clinical risk prediction models. Key trends in his publications span AI-enabled diagnostics , health equity , and geriatric health technology , with implications for clinical practice and policy. He is available to mentor advisees in these domains.

• Dynamics of long-span suspension bridges
• Floating bridges
• Stochastic environmental wind and wave loading
• +۷ مورد دیگر

Øyvind Wiig Petersen is an Associate Professor at the Department of Structural Engineering, Norwegian University of Science and Technology (NTNU). His research focuses on bridge dynamics, wind and wave loading, inverse force identification, structural monitoring, and machine learning applications in structural mechanics. He works extensively with long-span suspension bridges and floating bridge systems. Current research areas include vortex-induced vibrations, Kalman filter applications, wind tunnel testing, and finite element model updating. He has published in leading journals like Journal of Wind Engineering, Mechanical Systems and Signal Processing, and Engineering Structures. His work integrates experimental data with computational models for structural condition assessment and load estimation.

Chengbo Aiمشاهده پروفایل

دانشیار

• Transportation Asset Management
• Pavement Preservation
• Roadway Safety
• +۶ مورد دیگر

Dr. Chengbo Ai is an Associate Professor at the Department of Civil and Environmental Engineering , University of Massachusetts Amherst , specializing in transportation infrastructure and safety research. He holds a Ph.D. in Transportation Systems Engineering from Georgia Tech and a B.S. in Electrical Engineering from Peking University. Research Interests: Transportation Asset Management, Mobile LiDAR Applications, Roadway Safety Analytics, and Spatial Infrastructure Analysis Current Projects: Developing automated guardrail/sidewalk inventory systems, improving pedestrian infrastructure accessibility, and optimizing rail inspection methods Publications focus on integrating computer vision, machine learning, and geospatial technologies for infrastructure condition assessment. Recent work includes automated guardrail evaluation, rail gage inspection using consumer-grade devices, and pedestrian network analysis. Awards: Dwight David Eisenhower Transportation Fellowship recipients (2020-2022) Acorn Innovation Grant (2019) Best Poster Award at MassDOT Conference (2019) Students: Mentors Ph.D. researchers in pavement preservation, LiDAR processing, and transportation equity, with alumni working at FHWA, AECOM, and leading engineering firms Lab Facilities include advanced LiDAR systems (Theodore 1-3), dual-GPU workstations (Sullivan, Wazowski), and field vehicles like "Cynthia" for mobile mapping.

• Forest Road Planning
• Forest Harvesting and Transportation
• GIS & Remote Sensing Applications in Forestry
• +۱ مورد دیگر

Prof. Dr. Burak Aricak is a faculty member at Bursa Technical University , where he serves in the Faculty of Forestry under the Department of Forest Engineering . His work integrates geospatial technologies and environmental science to address critical forestry challenges. Research Focus : Forest Road Planning, Harvesting Techniques, GIS & Remote Sensing Applications, and Ergonomics. Key Publications (2023-2025) explore climate change effects on forest species distribution, heavy metal accumulation in trees, soil respiration dynamics post-harvesting, and UAV/LiDAR advancements for biomass estimation. Contact : burak.aricak@btu.edu.tr | +90 (224)-8081101

Rong Yinمشاهده پروفایل

استادیار

• Smart Textiles
• Flexible Robotics
• Sustainable Textile Technology
• +۴ مورد دیگر

Dr. Rong Yin is an Assistant Professor at the Wilson College of Textiles, North Carolina State University , specializing in Smart Textiles , Flexible Robotics , and Sustainable Spinning Technology . His research focuses on Wearable Electronics , Soft Actuators , and Hemp Fiber Processing for sustainable applications. Youth Editorial Board Member, Advanced Fiber Materials Guest Editor, Actuators and Frontiers in Chemistry Subcommittee Member, ASTM D37.07 Hemp Fiber Testing Standards Research Highlights: Developing Wearable Human-Machine Interaction Systems using embroidery-based sensors Innovating Sustainable Hemp Fiber Processing techniques for textile-grade materials Creating Soft Actuators using bioinspired designs and phase transition mechanisms Establishing Performance Modeling for textile manufacturing processes Scientific Awards: NSF Career Award Goodnight Early Career Innovators Award Barbara S. Stowe Faculty Award Key Collaborations: Consultant for multiple companies, reviewer for over 40 international journals.

Abbas Kouzaniمشاهده پروفایل

استاد

• Biomedical Engineering
• 3D Printing
• Neurotechnology
• +۵ مورد دیگر

Abbas Kouzani is a Professor of Engineering at the Deakin University School of Engineering , with a focus on cutting-edge biomedical engineering and AI applications. His work bridges 3D/4D printing and clinical challenges , particularly in dysphagia management and neurological disorders.

• Computer Engineering
• IoT Systems
• Machine Learning
• +۴ مورد دیگر

Dijana Stojić is an Assistant at the Department of Computer and Software Engineering, Faculty of Technical Sciences in Čačak, University of Kragujevac. She has held this position since January 2018 while pursuing her doctoral studies in Electrical and Computer Engineering with a specialization in Computer Engineering, which she began in 2021. Her academic journey began with excellent results at the 'Vuk Karadžić' elementary school in Čačak, followed by the Technical School in Čačak where she majored in computer electrical engineering. She earned her Bachelor's degree in Computer Engineering in 2011 (average grade 9.37) and Master's degree in 2012 (perfect average grade 10.00) from the Faculty of Technology in Čačak. Her Master's thesis, 'Software Support for Active RFID Localization,' was supervised by Prof. Dr. Siniša Ranđić. Dijana's research spans multiple domains within computer engineering, with recent publications focusing on practical applications of technology in diverse fields. Her work demonstrates strong expertise in IoT systems, machine learning applications, blockchain technology, and human-computer interaction. She has published extensively on topics including earthquake detection using mobile phones, predictive models for identifying students with difficulties in online learning, medical applications like ECG monitoring with Arduino, agricultural engineering applications, and infrastructure monitoring systems. Award for best first-year student at Faculty of Technology in Čačak Award for best second-year student at Faculty of Technology in Čačak Her professional activities include serving as Student Vice-Dean at the Technical Faculty in Čačak from December 2010 to September 2012, participating in the TEMPUS SIGMUS project, and completing an internship at D.O.O. DOCUS from June 2013 to June 2014. She was a scholarship holder of the Ministry of Education, Science and Technological Development from April 2013 to March 2017 and has been involved in significant research projects including 'Development and modeling of energy efficient, adaptable, multiprocessor and multisensory electronic low-power systems' (TR 32043) and the 'German-Serbian Collocation Dictionary for German Language and Teaching' (DeSKoll).

François G Schmittمشاهده پروفایل

پژوهشگر

• Turbulence
• Complexity in Oceanography
• Stochastic Processes
• +۳ مورد دیگر

François G Schmitt is a Researcher at CNRS , focusing on turbulence and its applications in oceanography, astrophysics, and interdisciplinary science. His work spans: Turbulence modeling and multifractal analysis Physics-biology couplings in marine ecosystems Scaling processes in environmental systems Renewable energy applications Key research highlights include: 2024 study revealing Van Gogh's Starry Night contains scientifically accurate turbulence patterns 2022 papers on reactive scalars in turbulence and copepod behavior 2020 textbook Turbulence et Ecologie Marine His recent publications (2021-2024) demonstrate expertise in fluid dynamics, ecological modeling, and astrophysical turbulence. He advised PhD candidate Wenwei Wu (2021) and co-organized special issues on air-sea interactions. No scientific awards or part-time positions are documented.

• Remote Sensing
• Photogrammetry
• Civil Engineering
• +۹ مورد دیگر

Dr. Maria-Valasia Peppa is a researcher at Newcastle University's School of Civil Engineering and Geosciences . Her work focuses on remote sensing, photogrammetry, and geospatial technologies, with applications in hydrodynamic modeling, landslide monitoring, and urban infrastructure analysis. Key Research Areas: UAV-based photogrammetry, glacial lake dynamics, digital elevation models (DEMs), and environmental data uncertainty. Recent Trends: Integration of deep learning with CCTV for traffic analysis, calibration of multisensor UAV systems, and real-time flood nowcasting frameworks. Collaborations: Active partnerships with Professors Jon Mills, Claire Walsh, and international institutions in Africa and Nepal. Applications: Cultural heritage mapping, water security strategies, and urban air quality modeling.

Spiridon Penevمشاهده پروفایل

استاد

• Wavelet Methods in Non-Parametric Curve Estimation
• Edgeworth Expansions and Saddlepoint Approximation Methods
• Structural Equation Models
• +۴ مورد دیگر

Professor Spiridon Penev is a faculty member at the School of Mathematics & Statistics , University of New South Wales (UNSW), Sydney. After completing his PhD in Mathematical Statistics at Humboldt University, Berlin, he worked at Technical University of Sofia (Bulgaria) for 10 years, becoming Associate Professor in 1991. He joined UNSW in 1992, progressing from Lecturer to Professor in 2019. His teaching focuses on Statistical Inference , Multivariate Analysis , Longitudinal Data Analysis , and related advanced courses. Research Interests: Wavelet Methods in Non-Parametric Curve Estimation, Edgeworth Expansions, Saddlepoint Approximation, Structural Equation Models, Inference in Semiparametric Models, and Stochastic Risk Modelling. Article Trends: His work spans from foundational wavelet methods (pre-2010) to modern applications in climate model ensembles , portfolio optimization , marine engineering , and machine learning . Keywords include Statistics, Finance, Climate Science, Structural Health Monitoring, and Optimization. Awards: DAAD Award, Elected Member of the International Statistical Institute (ISI). Grants: Led ARC Discovery Project (2016–2018), ARC Linkage Project (2018–2022), and industry collaborations like SCA water quality analysis (2014–2019). Location: School of Mathematics and Statistics, UNSW Sydney, Room 1038, The Red Centre.

Fabian Fassnachtمشاهده پروفایل

استاد

• Remote Sensing in Ecology
• Forest Ecosystems
• Urban Vegetation Monitoring
• +۷ مورد دیگر

Prof. Dr. Fabian Fassnacht holds the Professorship for Remote Sensing and Geoinformatics at the Institute of Geographical Sciences, Freie Universität Berlin. His research focuses on applying remote sensing technologies to understand ecological patterns and processes in vegetation ecosystems, particularly forest systems and urban trees. He specializes in developing workflows for quantifying forest attributes and creating synthetic remote sensing data to improve ecological understanding and monitoring. Education: PhD in Forestry Sciences (University of Freiburg, 2010-2014) Key Projects: FORZA (forest decline analysis), INSANE (spatial forest products), ErWiN (wildfire dynamics), SYSSIFOSS (synthetic forest data), SaMovar (invasive species monitoring) Research Focus: Multi-scale vegetation monitoring, 3D forest modeling, upscaling ecological processes, and wildfire risk assessment using LiDAR and UAV technologies His work addresses critical challenges in remote sensing applications across diverse ecosystems, including semi-arid forests and temperate woodlands. He has coordinated numerous research initiatives funded by BMBF, DAAD, DFG, and other international agencies. Current efforts involve integrating deep learning with traditional remote sensing methods to enhance forest inventory models and ecological assessments.

Jeannine M Cavender-Baresمشاهده پروفایل

استاد

• Plant Biology
• Biodiversity
• Remote Sensing
• +۳ مورد دیگر

Jeannine M Cavender-Bares is a Professor at the University of Minnesota , affiliated with the Minnesota Invasive Terrestrial Plants and Pests Center . She earned her PhD from Harvard University in 2000 and has been actively conducting research since 1993. Current projects include integrating machine learning for forest health monitoring and studying oak syngameons across continents Her work contributes to UN Sustainable Development Goals (SDGs) related to environmental sustainability Research Focus : Her research spans plant biodiversity, evolutionary ecology, and remote sensing applications. Key areas include: Phylogenetic and functional trait analysis Urban forest dynamics and social-ecological systems Climate change impacts on plant communities Invasive species detection via spectral biology Belowground process prediction from aboveground data Publication Trends : Recent 2025 articles emphasize spectral reflectance analysis for climate change detection, urban forest diversity quantification, and multi-scale ecological processes. Earlier works focus on oak evolution, prairie ecosystem linkages, and invasive species management. Grants & Collaborations : Current projects include: $12.5M NSF grant for cross-scale biodiversity research NSF LTER urban ecosystem studies with 20+ collaborators NASA-funded Mediterranean ecosystem comparisons USDI National Park Service forest health monitoring initiative Media Engagement : Regularly contributes expert commentary on: Oak wilt disease spread in Minnesota Biodiversity assessment frameworks Urban plant diversity patterns Tree evolutionary dominance mechanisms

Zeinab Hosseinidoustمشاهده پروفایل

دانشیار

• Antimicrobial Resistance
• Bioengineering
• Biomaterials
• +۷ مورد دیگر

Zeinab Hosseinidoust is an Associate Professor in the Department of Chemical Engineering at McMaster University and holds the Canada Research Chair (Tier 2) in Bacteriophage Bioengineering. Her work bridges chemical and biomedical engineering to address antimicrobial resistance through innovative bacteriophage-based technologies. She leads the Hosseinidoust Research Group, which focuses on transforming phages into scalable products for healthcare, agriculture, and food safety. Education: Ph.D. from McGill University, postdoctoral training at Max Planck Institute for Intelligent Systems. Research Pillars: Phage Antimicrobials, Phage Biomaterials, Phage Diagnostics, and Aerosolized Phage Applications. Her 15 most recent articles (2024–2025) emphasize translational phage bioengineering, including high-throughput diagnostic platforms, antimicrobial microgels, and smart implant coatings. Key themes include Phage Therapy , Biomaterials Engineering , and Nano-Structured Antimicrobials , with subfields like 3D Bioprinting , Smart Textiles , and In Vivo Models . Awards: Canada Research Chair, Ontario Early Researcher Award, Dean’s Honor Roll for Teaching Excellence. Teaching: Courses in Heat Transfer (CHEMENG 3A04) and Health Solutions Design Projects II (IBEHS 2P03). Collaborative Affiliations: Core member of the Farncombe Institute for Digestive Health, associate member of the Michael DeGroote Institute for Infectious Disease Research, School of Biomedical Engineering, and CEPEM.

Zhong Liمشاهده پروفایل

دانشیار

• Water Resources Systems
• Machine Learning Applications in Hydrology
• Climate Change Impact on Hydrological Processes
• +۴ مورد دیگر

Zhong Li is an Associate Professor in the Department of Civil Engineering at McMaster University, specializing in water resources systems, environmental modeling, and machine learning applications. His research focuses on integrating advanced computational techniques with hydrological processes to address climate change impacts, infrastructure resilience, and water quality management. Key research areas include hydrological modeling under uncertainty, wastewater treatment optimization, and AI-driven environmental systems Develops hybrid models combining machine learning with physical/ontological frameworks for improved predictive accuracy Recipient of the 2025 University Scholar award at McMaster for mid-career research leadership Recent publications demonstrate expertise in global flood forecasting, membrane fouling prediction, SARS-CoV-2 wastewater surveillance, and climate change adaptation strategies. His work spans water treatment plants, Canadian river systems, and transboundary environmental challenges. Scientific Awards: University Scholar 2025 (McMaster University) Teaching responsibilities include courses in environmental engineering, water resources systems design, and specialized civil engineering studies. Collaborates extensively with interdisciplinary teams on infrastructure safety and sustainability projects.