جست‌وجوی استاد و پژوهشگر

• Computer Vision
• Image Analysis
• Machine Learning
• +۴ مورد دیگر

Dr Shahana Bano is a Lecturer in the School of Computing, Engineering & Technology at Robert Gordon University, specializing in interdisciplinary applications of Artificial Intelligence. Her research spans biomedical imaging, environmental monitoring, infrastructure analytics, and socio-technical systems through the Machine Vision Research Group and Cybersecurity Research Group. Her educational background includes a PhD in Computer Science and Engineering, M.Tech in Computer Science and Engineering, MSc in Information Systems, and BCA - all completed full-time. Her research philosophy centers on convergence, bringing together diverse data types, technologies, and disciplines to create impactful, adaptive systems that bridge academic innovation with societal relevance. Dr Bano's research interests focus on Computer Vision, Image Analysis, Machine Learning, Data Analytics, Internet of Things, Text to Speech Systems, and Social Media Threat Intelligence. Her recent work demonstrates strong application of these interests to medical diagnostics (CAR-T cell classification), environmental monitoring (geothermal reservoir modeling), infrastructure analytics (pipeline defect detection), and social systems (hate detection in football communities). Her publication record shows consistent output with 32 research outputs from 2015-2025, demonstrating increasing focus on medical and environmental applications of AI in recent years. The work spans theoretical computer vision advancements to practical implementations addressing UN Sustainable Development Goals. Associate Fellow (AFHEA) 2023 from Advance HE Dr Bano actively supervises PhD students and mentors interns on diverse projects. Current PhD supervision includes research on morphological classification of CAR-T cell images for leukemia diagnosis and acoustic emission-based pipeline defect detection. She also guides students on projects involving AR-based navigation, NDVI vegetation mapping, hate detection in football communities, multimodal sensor fusion, and airport runway object detection. Her lab resources are supported through university research groups and collaborations focused on machine vision and cybersecurity applications.

• Pavement Infrastructure Systems
• Climate Change Effects on Pavements
• Sustainable Materials
• +۲ مورد دیگر

Dr. Mohammad (Imran) Hossain is an Associate Professor in the Department of Civil Engineering & Construction at Bradley University's Caterpillar College of Engineering & Technology. With a Ph.D. from the University of New Mexico and over a decade of academic experience, his career includes roles as Assistant Professor at Bradley (2014-2020) and research positions at multiple institutions. His research integrates civil engineering with sustainability and AI: Pavement Systems : Climate resilience, smart city integration Materials Innovation : Recycled additives, waste valorization Environmental Impact : Hazard mitigation, pollution analysis Computational Modeling : Neural networks for performance prediction, molecular dynamics Dr. Hossain has secured significant external funding, including: $85,000 from Illinois DOT for concrete sensing (2025-26) $338,000 for rural road evaluation (2016-19) $70,500 for pavement management systems (2019-21) Honors include the 2025 Phi Kappa Phi Faculty Achievement Award, 2022 Outstanding Faculty Award, and 2017 Caterpillar Teaching Award. He has mentored 73+ students and maintains professional membership in the American Society of Civil Engineers.

• Digital Communications
• Signal Processing
• Specific Emitter Identification
• +۷ مورد دیگر

Donald R. Reising serves as a Guerry and UC Foundation Professor of Electrical Engineering in the College of Engineering and Computer Science at the University of Tennessee at Chattanooga (UTC). He holds appointments in both the Electrical Engineering department and the Computational Science program, with active roles in university governance as Faculty Senate Chair (2022-2025) and member of multiple strategic committees including the PhD Computational Science Committee. B.S. in Electrical Engineering, University of Cincinnati (2006) M.S. in Electrical Engineering, Air Force Institute of Technology (2009) Ph.D. in Electrical Engineering, Air Force Institute of Technology (2012) Dr. Reising's research spans three interconnected domains: wireless security through Specific Emitter Identification (SEI) and RF fingerprinting, smart grid intelligence for real-time disturbance analysis, and radiation effects characterization in microelectronics. His work integrates machine learning with signal processing to solve critical infrastructure protection challenges, particularly in adversarial environments where traditional security measures fail. Recent publications demonstrate increasing focus on deep learning countermeasures against SEI spoofing attacks and edge-computing solutions for power grid resilience. His 15 most recent publications reveal strong emphasis on adversarial machine learning (6 articles), SEI robustness under environmental stressors (5 articles), and smart grid data analytics (3 articles), with growing interdisciplinary work in quantum correlations and transportation safety. This trajectory shows evolution from foundational RF fingerprinting techniques toward comprehensive security frameworks for critical infrastructure. IEEE Chattanooga Chapter's Outstanding Engineer Award (2022) UTC’s Outstanding University Service Award (2018) AFRL Sensors Directorate Dr. Samuel M. Burka Award (2013) Association of Old Crows Research Excellence Award (2009) MASINT Committee Academic Excellence Award (2009) Dr. Reising leads multiple research initiatives including the RF Security Lab and Smart Grid Analytics Group, securing consistent funding from DoD agencies (AFRL, ARL), NSF, and industry partners like EPRI. His service extends to advising graduate students through the Computational Science PhD program and directing undergraduate research in radiation effects characterization. Current projects focus on SEI resilience against deep learning attacks, quantum-enhanced signal processing, and edge-computing solutions for grid cybersecurity.

• Spatial Audio
• Machine Learning for Audio
• Environmental Soundscapes
• +۳ مورد دیگر

Dr. Marc C. Green serves as a Postdoctoral Research Fellow within the School of Science, Engineering & Environment at the University of Salford, affiliated with the Acoustics Innovation Institute. His research bridges acoustic engineering, machine learning, and environmental psychology with focus on unmanned aircraft systems noise impact assessment. PhD in Music Technology, University of York (2020) Dr. Green's research investigates how drone noise interacts with urban soundscapes through innovative methodologies including soundwalk assessments in controlled environments, psychoacoustic laboratory testing , and deep learning model development . His work specifically examines time-variant noise characteristics, flight operation impacts, and environmental interactions (such as pine tree barriers in urban parks) to understand human annoyance responses. The integration of spatial audio techniques with machine learning enables novel approaches to predicting UAV sound affect beyond traditional sound pressure level metrics. Analysis of his 11 recent publications (2024-2025) reveals a strong focus on practical solutions for urban drone integration, with 55% dedicated to psychoacoustic modeling, 27% to field assessment methodologies, and 18% to technical noise characterization. His work consistently addresses the tension between societal benefits of drone technology and community noise impacts. EPSRC connected nation pioneers prize for 'Creative Computing for the Digital Economy' (for EigenScape database development) Currently leading the RefMap project to reduce UAS environmental impact, Dr. Green's research receives direct institutional support through the Acoustics Innovation Institute. His EigenScape database continues to serve as a foundational resource for global soundscape researchers. The systematic review framework he developed for UAS noise impact testing provides regulators with evidence-based assessment protocols. Dr. Green operates within the Acoustics Innovation Institute's collaborative ecosystem, leveraging specialized recording equipment and computational resources. His research group maintains comprehensive drone noise datasets across multiple platforms and develops open methodologies for community noise assessment in evolving urban air mobility scenarios.

• Telecommunications
• Voice over IP (VoIP)
• Network Design
• +۳ مورد دیگر

Juan Manuel Vozmediano Torres is a Full Professor in the Department of Telematics Engineering at the University of Seville. His research spans telecommunications, VoIP systems, network design, and educational technology. He leads the TIC-154 Research Group and has secured numerous grants, including the ongoing PID2023-149683OB-I00 project on aerial robotics and IoT. Research interests include: Telematics and network protocol optimization VoIP traffic characterization and QoS enhancement Cost-effective infrastructure design (e.g., fiber optics) Virtualized learning environments for engineering His publications focus on VoIP efficiency, network modeling, and educational innovations. Recent works analyze hospital network reliability (2019) and smartphone codec selection (2014). He has supervised four doctoral theses and holds a patent for an ISDN access server prototype. Industry collaborations include projects with Alcatel, telecommunications infrastructure planning, and IoT systems for commercial platforms.

Wei Chenمشاهده پروفایل

استاد

• Software Engineering
• Intelligent Software Engineering
• Network Distributed Computing
• +۶ مورد دیگر

Wei Chen is a Research Fellow at the Institute of Software, Chinese Academy of Sciences, where he serves as a PhD and Master's supervisor. He leads the Software Engineering Technology R&D Center and maintains affiliations with the University of Chinese Academy of Sciences and its Nanjing College. Dr. Chen has established himself as a leading figure in intelligent software engineering research within China's academic community. His primary research focuses on four interconnected areas: intelligent code maintenance and quality assurance (particularly Python ecosystem compatibility based on domain knowledge), reliability assurance of complex IoT systems in human-machine-object convergence scenarios, cloud-native system development with emphasis on Function-as-a-Service optimization, and quality assurance of deep learning frameworks in resource-constrained environments. Dr. Chen's work consistently bridges theoretical advances with practical applications, maintaining strong industry collaborations with major Chinese technology companies. Analysis of Dr. Chen's recent publications reveals a strategic integration of AI techniques with traditional software engineering challenges. His research shows increasing emphasis on leveraging large language models for IoT component synthesis, sophisticated dependency management solutions for Python ecosystems, and innovative approaches to testing autonomous systems. The work demonstrates both theoretical depth and practical utility, with many publications leading to implemented tools and systems. Second Prize of Science and Technology Progress Award of China Institute of Electronics (2022) First Prize of Science and Technology Progress Award of China Institute of Electronics (2021) ACM SIGSOFT Distinguished Paper Award (2023) Special Prize of the 4th China Software Open Source Innovation Competition (2021) First Prize in the 4th China Software Open Source Innovation Competition (2021) OW2 Programming Contest First Prize (2016) Dr. Chen has mentored over ten graduate students who have achieved notable success in academic competitions and industry placements. His laboratory (TCSE, http://tcse.cn/) currently manages multiple significant research projects including 'Complex IoT System Reliability Assurance Key Technology Research' (2025-2028), 'Intelligent Development, Testing, and Maintenance of Cloud-native Software Ecosystems' (2024-2027), and 'Traffic Infrastructure Digital Industrial Software Architecture and Core Technology Standard System' (2021-2024). The lab maintains active collaborations with Huawei, Alibaba, Tencent, and other leading technology enterprises.

Andry Razakamanantsoaمشاهده پروفایل

پژوهشگر

• Hydromechanical behaviors of geomaterials
• Durability of geomaterials
• Soil-atmosphere interactions
• +۷ مورد دیگر

Andry Razakamanantsoa is a Researcher at Gustave Eiffel University, serving as Sustainable Development Research Officer and Deputy Director of the Geomatériaux, Environmental Interactions Laboratory (GERS-GIE). He is affiliated with the Department of Geotechnical Engineering, Environment, Natural Hazards and Earth Sciences (GERS), specifically within the Geomatériaux and Environmental Interactions (GIE) research group. With 83 publications and over 1,184 citations, his work focuses on sustainable geotechnical solutions and environmental interactions. His research interests span hydromechanical behaviors of geomaterials, durability of treated soils, soil-atmosphere interactions, physical modeling of aerosols, material rheology, and sustainable construction techniques. Key research axes include multi-physical and multi-scale coupling around infrastructure and cities, valorization of waste materials in construction, durability of earth structures, and dust emission control from unpaved roads. Razakamanantsoa's publications demonstrate a strong focus on practical applications of geotechnical research, with particular emphasis on sustainable construction materials, soil treatment techniques, and environmental impact mitigation. His recent work shows increasing integration of machine learning techniques for environmental monitoring and analysis of construction material behavior. He has participated in numerous research projects including PROPER (European assessment of highway stormwater runoff pollution), OI2018_F2 (water economy), OI2019_F3 (mapping suitable lands for raw earth construction), and dust emission control studies for earthmoving sites. His research has practical applications in road construction, sustainable building techniques, and environmental protection. Razakamanantsoa collaborates extensively with industry partners including the French National Federation of Public Works (FNTP), the Union of Earth and Sea Professions (UMTM), and the Professional Syndicate of French Excavators (SPTF), ensuring his research has direct practical relevance to industry challenges.

Søren Ingvor Olsenمشاهده پروفایل

دانشیار

• Computer Vision
• Image Analysis
• Pattern Recognition
• +۳ مورد دیگر

Søren Ingvor Olsen is an Associate Professor in the Department of Computer Science at the University of Copenhagen's Faculty of Science. His research focuses on Image Analysis, Computational Modelling, and Geometry within the broader field of Computer Science. He maintains an active research profile with numerous publications and collaborations across various application domains. Dr. Olsen received his academic training at the University of Copenhagen, where he earned both his Master's degree in 1984 and his PhD in 1988, both from the Department of Computer Science. His academic career at the same institution began as an Assistant Professor from 1988-1991, followed by his promotion to Associate Professor. He served as Head of the Department from 1996-1999 and has held various significant roles including Visiting Professor at University Blaise-Pascal in France (2006) and involvement with the E-Science Center at the Faculty of Science (2008). Professor Olsen's primary research areas span 3D Computer Vision, Image Analysis, and Pattern Recognition. His work is characterized by its interdisciplinary nature, combining theoretical foundations with practical applications. Recently, he has focused on applying computer vision techniques to real-world problems such as railway sign detection, agricultural weed mapping using drone technology, and automation in food processing industries. His research bridges the gap between fundamental computer vision algorithms and their implementation in diverse industrial settings, demonstrating strong translational research capabilities. Analysis of his recent publication record reveals a strong trend toward applying computer vision and machine learning techniques to environmental monitoring and precision agriculture. His work demonstrates expertise in drone-based imaging systems, deep learning for object detection, and the development of practical solutions for agricultural and transportation infrastructure challenges. The interdisciplinary nature of his research is evident in collaborations spanning environmental science, agricultural engineering, and transportation systems. Throughout his career, Professor Olsen has contributed significantly to academic development, notably being responsible for the creation and accreditation of a cross-faculty bachelor's program in Science and IT in 2009. While specific grant information isn't detailed in the available materials, his extensive publication record and international collaborations suggest successful research funding throughout his career. His work appears to involve substantial student mentorship, though specific advisees aren't named in the provided information. Professor Olsen's research appears to be conducted through the Image Analysis group within the Department of Computer Science at the University of Copenhagen. His work with drone technology and agricultural applications suggests collaborations with agricultural research institutions and potentially industry partners in the railway and food processing sectors. The practical orientation of his recent work indicates strong connections between his academic research and real-world industrial applications.

Amarjit Singhمشاهده پروفایل

استاد

• Legal Affairs and Dispute Resolution in Construction
• Risk Analysis in Construction
• Construction Engineering and Management
• +۵ مورد دیگر

Amarjit Singh serves as Professor in the Department of Civil, Environmental and Construction Engineering at the University of Hawaiʻi at Mānoa, where he has held continuous faculty appointments since 1993, progressing from Assistant to full Professor. His academic leadership includes serving as Graduate Chair (2022-2023) and holding visiting positions at IIT Delhi, University of New South Wales, and Cornell University. His educational foundation includes: Ph.D. in Civil Engineering from Purdue University (1990) M.Eng. in Civil Engineering from Texas A&M University (1987) B.Tech. in Civil Engineering from I.I.T. Delhi (1976) Professor Singh's research pioneers the integration of legal frameworks with engineering practice , particularly in construction dispute resolution and risk analysis . His work spans concrete technology, construction safety, and infrastructure asset management, characterized by practical applications in international contexts. As Founding Editor of the Journal of Legal Affairs and Dispute Resolution in Engineering and Construction, he has shaped scholarly discourse at the law-engineering interface. His recent publications (2021-2025) demonstrate consistent focus on infrastructure failure analysis (dam failures, high-rise collapses, fuel storage incidents) and context-specific construction challenges (India's concrete practices, Afghanistan's conflict-zone projects). The work exhibits strong interdisciplinary connections between engineering, legal liability, and public policy. His distinguished recognition includes the Richard R. Torrens Award (2024) and multiple best paper awards across ASCE journals: Richard R. Torrens Award (2024) Construction Management Award (2019) Board of Regents’ Excellence in Teaching Award (2009) Seven Best Paper Awards (2007-2021) Professor Singh has secured over $5M in research funding from FHWA, USGS, NSF, and industry partners for infrastructure projects including Kahului Airport pavement monitoring, Honolulu water pipe networks, and harbor protection systems. His grants consistently address practical infrastructure challenges through engineering-economic analysis. His research collaborations with the Honolulu Board of Water Supply and Hawaii Department of Transportation focus on real-world asset management solutions, particularly in pipeline performance analysis and coastal protection engineering.