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Sabih RehmanView profile

Senior Lecturer

• Wireless Communication
• Network Planning
• Internet of Things (IoT)
• +5 more

Sabih Rehman is a Senior Lecturer and Course Director at the School of Computing and Mathematics, Charles Sturt University, Australia. He holds a PhD in Wireless Networks (2016) from Charles Sturt University and a Bachelor's in Electronics & Telecommunication Engineering (Honours) from the University of South Australia. His research focuses on IoT applications in Intelligent Transport Systems, Environmental Sustainability, E-Health, and Precision Agriculture, with a strong emphasis on rural community impact. He is a member of IEEE and the Australian Computer Society. Research interests include vehicular ad-hoc networks (VANETs), antenna design, blockchain security, and machine learning for healthcare and agriculture. He leads the Data Mining Research Group (DaMRG) and collaborates with the Cyber Security Research Group (CSRG) and Health Services Research Group. Key achievements include the 2024 Excellence Award (Research), grants for AI in Mental Health and Aging Care, and over 77 publications with an h-index of 13. His work addresses UN SDGs related to sustainable communities through digitally enabled solutions. Professional engagement includes developing industry-aligned curricula (e.g., Master of Professional IT) and community workshops on STEM education. He actively reviews for journals and conferences, emphasizing practical applications of technology in rural contexts.

Wenxuan GuoView profile

Associate Professor

• Precision Agriculture
• Remote Sensing
• Crop Ecophysiology
• +2 more

Dr. Wenxuan Guo is Associate Professor of Crop Ecophysiology & Precision Agriculture at Texas Tech University with a joint appointment at Texas AgriLife Research. He earned his bachelor's degree in Crop Science from Agricultural University of Hebei, a master's in Plant, Soil, and Environmental Science from West Texas A&M University, and a doctorate in Agronomy from Texas Tech University. His research integrates: UAV-based remote sensing for crop phenotyping Precision irrigation and nutrient management Climate-resilient cropping systems Machine learning applications in agriculture His 15 most recent publications demonstrate consistent focus on cotton production systems, UAV sensor technologies, and predictive modeling, with significant contributions to water-efficient agriculture and climate adaptation strategies. Major recognitions include: Multiple Monsanto Breeding Excellence Awards (2014-2016) Pioneering recognition for UAV phenotyping programs He leads the Guo Precision Ag Lab and teaches graduate courses in Precision Agriculture, Agricultural Remote Sensing, and Plant Growth Modeling.

Greville G. CorbettView profile

Professor

• Linguistics
• Morphology
• Typology
• +6 more

Greville G. Corbett is a Distinguished Professor of Linguistics at the University of Surrey, with a concurrent appointment in Russian Language. He is a Fellow of the British Academy, Member of Academia Europaea, and Academician of the Academy of Social Sciences, reflecting his status as a leading figure in linguistic typology and morphology. Education: PhD in Russian/Linguistics (University of Birmingham, 1976), M.A. Russian with Linguistics (Birmingham, 1971), B.A. French and Russian (Birmingham, 1970) Key Collaborations: ARC Centre of Excellence for Dynamics of Language, Centre for Advanced Study (Norway), and extensive international partnerships in Slavonic, Daghestanian, and Oceanic language studies His research spans three major areas: Canonical Typology (exploring deep linguistic similarities across systems), Morphosyntactic Features (gender, number, case, person), and Inflectional Morphology (notably developing Network Morphology with Norman Fraser). Recent work includes analyzing possessive classifiers in Vanuatu and New Caledonia languages. Articles highlight his expertise in agreement systems (revisiting the Agreement Hierarchy), split phenomena (internal/external), color term typology, and acoustic analysis of English plurals. His methodological innovations include free-listing experiments and visualizing complex inflectional paradigms. Scientific honors include: ESRC Professorial Research Fellowship (2004-2007) European Research Council Advanced Grant (2009-2014) Center for Advanced Study Fellowship (2001) ALT Pāṇini Award Jury Membership (2007) He has supervised numerous PhD students, including Dunstan Brown (Network Morphology), Jenny Audring (Pronoun Gender), and Alison Long (Russian Adjectives), while maintaining active roles in editorial boards and international linguistic panels.

• Geoinformatics
• Civil Engineering
• Transportation Systems
• +4 more

Dr. LOVAS Tamás is an Associate Professor and Head of the Department of Photogrammetry and Geoinformatics at the Faculty of Civil Engineering, Budapest University of Technology and Economics (BME). He also serves as a Representative and Coordinator for the Specialization in Construction Information Technology Engineering (MSc) within the Faculty Council. His expertise spans geoinformatics, civil engineering, and transportation systems, with a focus on laser scanning, point cloud integration, and smart infrastructure solutions. Education: While formal education details are not explicitly provided, his academic role and publications suggest a strong background in civil engineering and geomatics. His courses include topics like Intelligent Transport Systems (BMEEOFTMF61), ITS GIS (BMEEOFTMF62), and Laser Scanning (BMEEOFTDT81). Research Interests: Dr. Lovász’s work centers on leveraging geospatial technologies for infrastructure analysis, including urban land cover classification , automated road surface segmentation , and scan-to-BIM workflows . He pioneers applications in transportation safety, autonomous vehicle HD mapping, and disaster risk assessment using RPAS and LiDAR. His team develops AI-driven strategies for point cloud data and digital twins, enhancing infrastructure monitoring and urban planning. Key Achievements: He has been awarded the Magyar Felvételi információ #építő250 ösztöndíj and contributed to projects like the ZalaZONE automotive proving ground’s HD mapping workflow. His research bridges academic innovation with practical engineering solutions, such as optimizing electric vehicle charging station placement and assessing rockfall hazards in volcanic regions. Grants & Advising: His work includes funded projects on laser scanning for bridge load testing and steel section inspection. While specific grant details are not listed, his publications reflect sustained engagement with industry-relevant research. He advises on complex construction IT projects and guides students through MSc specializations in construction information technology. Labs & Teams: His department collaborates with the Vásárhelyi Pál Doctoral School of Civil Engineering and Earth Sciences , focusing on geomatics, geotechnical engineering, and infrastructure systems. His team integrates cutting-edge technologies like LiDAR, photogrammetry, and AI to advance civil engineering practices.

Manuel SpitschanView profile

Research Fellow

• Circadian Neuroscience
• Visual Physiology
• Non-Visual Effects of Light
• +3 more

Prof. Manuel Spitschan is a Max Planck Research Group Leader at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany. Previously, he held a University Research Lecturer position at the University of Oxford (2020-2021) and a Sir Henry Wellcome Fellowship (2017-2020). His research focuses on light’s impact on human circadian rhythms, visual/non-visual physiology, and real-world applications of light exposure science. Education: B.A. (Hons) from University of St Andrews (2012) PhD in Neuroscience from University of Pennsylvania (2016) Postdoctoral Fellowship at Stanford University (2016-2017) Research Interests: Spitschan investigates light’s effects on circadian systems, retinal mechanisms underlying non-visual responses, and translational applications of light dosimetry. His work bridges basic science and clinical applications, with a focus on wearable light measurement technologies, sleep health, and chronotherapeutic interventions. Awards & Affiliations: Sir Henry Wellcome Fellowship (2017-2020) University Research Lecturer title (2020) Member of CIE TC 1-98, OSA Color Technical Group, and Daylight Academy Grants & Labs: Leads the Sensory and Circadian Neuroscience research group, developing open-source tools like luox and LightLogR . His lab focuses on advancing light measurement standards and understanding individual variability in light responses.

Falk HuettigView profile

Professor

• Psycholinguistics
• Cognitive Neuroscience
• Cultural Cognition
• +3 more

Falk Huettig is a Senior Investigator at the Max Planck Institute (MPI) for Psycholinguistics in Nijmegen and an Invited Full Professor of Psychology at the University of Lisbon. He holds Honorary Professorship at the University of Kaiserslautern-Landau. Previously, he was a Full Professor of Psycholinguistics and Cultural Cognition at Radboud University (2019–2024). His research spans cultural cognition , predictive processing , and the impact of literacy on the brain . He uses neuroimaging, behavioral experiments, and computational modeling to explore how cultural tools like writing reshape cognition. Education : BSc Biological Sciences (Psychology), University of Edinburgh (2000) MSc by Research in Psychology, University of Edinburgh (2001) PhD in Psychology, University of York (2004) Habilitation in Psychology, University of Münster (2013) Research Focus : Huettig investigates how literacy acquisition alters brain structure/function (e.g., cortical/subcortical networks), the role of prediction in language comprehension, and cultural influences on cognition. His work spans diverse populations, including illiterate adults, children, and multilingual speakers. Key themes include neuronal recycling, cross-modal interactions, and the 'literate mind hypothesis.' Grants & Leadership : Max Planck Society Strategic Grants (2010–2017) Scientific Council Representative for MPI (2009–2015) President, Society for Cognitive Science of Culture (2018–present) Labs & Collaborations : His research is affiliated with the Donders Institute and the MPI, focusing on interdisciplinary projects combining psychology, neuroscience, and anthropology. Current work emphasizes Looking Ahead: The New Science of the Predictive Mind (Cambridge, 2025).

Jonathan RubinView profile

Professor

• Emergency Medicine
• Clinical Informatics
• Public Health
• +3 more

Jonathan Rubin, MD is a Professor and Division Chief of System Informatics and Analytics at the Medical College of Wisconsin's Department of Emergency Medicine. His work focuses on clinical informatics, emergency care optimization, and public health interventions. He has contributed to studies on prehospital care protocols, EMS system efficacy, and community-based health initiatives. Research interests include geospatial analysis of trauma outcomes, asthma management strategies, fire safety interventions, and EMS system performance. His work bridges clinical practice with data-driven solutions for emergency medicine challenges. Publications span emergency medicine innovations, from asthma treatment protocols to evaluating the impact of fire safety programs during EMS calls. Rubin's interdisciplinary approach addresses both acute care delivery and long-term public health strategies.

Joseph CarrollView profile

Professor

• Ophthalmology
• Visual Neuroscience
• Retinal Imaging
• +5 more

Joseph Carroll is the Richard O. Schultz, MD / Ruth Works Professor of Ophthalmology and Professor in the Departments of Ophthalmology & Visual Sciences, Biophysics, and Cell Biology, Neurobiology and Anatomy at the Medical College of Wisconsin (MCW). He directs the Advanced Ocular Imaging Program (AOIP), a resource for high-resolution retinal imaging technologies like adaptive optics and optical coherence tomography. His research focuses on structural-functional relationships in the visual system, with emphasis on retinal degeneration mechanisms, comparative color vision, and foveal development. Dr. Carroll received his BS in Human Biology from UW-Green Bay and PhD in Cell & Developmental Biology from MCW, followed by a postdoctoral fellowship in adaptive optics imaging at the University of Rochester. Key research areas include applying advanced imaging to study human retinal structure-function correlations, analyzing inherited retinal diseases (e.g., achromatopsia, Usher syndrome), and developing translational imaging tools. Current projects involve longitudinal studies of cone photoreceptor mosaic integrity in genetic retinal disorders and assessment of adaptive optics-based visual acuity metrics. Funding comes from NIH grants, research foundations, and private donors through AOIP collaborations. His lab’s work bridges basic science and clinical application, with recent studies examining retinal structure-visual function relationships in macular diseases, rodent models of cone-dominant vision, and evaluating novel imaging technologies for disease monitoring. Dr. Carroll also contributes to peer review standards in ophthalmic journals and has pioneered FAZ analysis tools for OCT angiography.

• Structural Engineering
• Structural Reliability Analysis
• Design Optimization
• +5 more

Mohamed El Amine Ben Seghier is an MSCA Fellow and Part-Time Lecturer at the Department of Built Environment, Oslo Metropolitan University. His research focuses on structural reliability analysis, corrosion modeling, and machine learning applications in civil engineering infrastructure. He explores maintenance optimization for deteriorating structures, including pipelines, bridges, and energy systems, with a particular emphasis on corrosion degradation and predictive frameworks. His work integrates advanced machine learning techniques to address challenges in structural resilience, design optimization, and recycling strategies. He has produced over 90 peer-reviewed publications, with recent contributions focusing on hybrid deep learning models for corrosion prediction, geothermal energy piles, and probabilistic frameworks for infrastructure failure analysis. Key research areas include: Structural reliability and risk assessment Machine learning in civil engineering Material degradation modeling Infrastructure maintenance scheduling Offshore and subsea pipeline integrity His publications demonstrate a strong focus on integrating empirical data with computational models to enhance infrastructure resilience against environmental and operational stresses.

Elena Camelia MușatView profile

Lecturer

• Ergonomics
• Forest roads
• Machines for constructions
• +3 more

Elena Camelia Mușat is a Lecturer at the University of Brașov, affiliated with the Department of Forest Engineering, Forest Management Planning and Terrestrial Measurements within the Faculty of Silviculture and Forest Engineering. Her research focuses on ergonomics, forest road design, and construction machinery in forestry contexts. She has contributed to studies on occupational safety in forestry operations, veneer cutting efficiency, and mechanized equipment time optimization. Her work bridges engineering and natural resource management, addressing challenges such as log defect analysis, workplace accident prevention, and sustainable wood processing. Publications include analyses of oak species utilization, statistical methods for veneer quality assessment, and ergonomic improvements in mechanized forestry systems. No scientific awards or grants are explicitly mentioned in the provided materials. She has not listed advisees or lab affiliations in the available data. Contact details include her office at Building S, Room S4, and email elena.musat@unitbv.ro.

• Digital Media in Architectural Design
• Smart Urban Planning
• User-Centered Design
• +3 more

Anna Karagianni is an Assistant Professor at the School of Architecture, Technical University of Crete. She holds a Diploma in Architecture from the University of Patras (2007), an MSAAD from Columbia University (2010), and a PhD in Architecture from TUC (2021). Her research focuses on digital media integration in architectural design, smart urban systems, and user-centric technologies. She teaches courses including Architectural Design, Digital Media in Architecture, and Advanced Digital Technologies. Her work explores smart spaces, IoT applications in design, and sustainable urban planning. Notable projects include collaborations with international firms and her founding role in ANT Architects, a research-driven design studio. Recent publications address AI-driven architectural innovation, vertical urban biodiversity, and pandemic-driven spatial analysis. Publications highlight trends in AR integration, digital twins, and urban health. She advocates for human-centered design frameworks and has contributed to UN SDG-aligned smart city initiatives. Collaborations span Greece, Spain, France, and beyond, emphasizing interdisciplinary approaches to architectural challenges.

Michael KingView profile

Associate Professor

• Biometrics
• Cyber Identity
• Machine Learning
• +3 more

Dr. Michael King is an Associate Professor in the Department of Computer Engineering and Sciences at Florida Institute of Technology, with a joint appointment at the Harris Institute for Assured Information. He holds a PhD in Electrical Engineering from North Carolina A&T State University (2001). His research focuses on biometrics, cyber identity, and machine learning, particularly addressing challenges in facial recognition accuracy, algorithmic fairness, and adversarial machine learning. Prior to academia, he spent over a decade in the U.S. Intelligence Community, leading research initiatives such as IARPA’s BEST Program. His work spans biometric system design, privacy-preserving techniques, and mitigating demographic biases in AI systems. Education: PhD in Electrical Engineering, North Carolina Agricultural and Technical State University, 2001 Research interests include the technical and ethical dimensions of biometric systems, with an emphasis on improving accuracy across demographics and enhancing privacy. His recent articles analyze factors like interpupillary distance, image illumination, and sunglasses impact on face recognition systems. He has also explored adversarial attacks on AI models and their mitigation strategies. His professional experience includes roles as Intelligence Community Department Lead for the White House’s Subcommittee on Biometrics and Identity Management (2005–2012), showcasing his expertise in bridging academic research with government policy. While no specific grants or awards are listed, his contributions to national security and technology policy are notable. He currently advises students in topics related to biometrics and machine learning, though no named advisees are documented. Labs/Teams: Active in the Harris Institute for Assured Information, focusing on cyber analytics and identity protection technologies.

Zahra NematzadehView profile

Assistant Professor

• Machine Learning in Medical Applications
• Digital Biomarkers
• AI-Driven Healthcare Solutions
• +4 more

Zahra Nematzadeh is an Assistant Professor at the Department of Electrical Engineering and Computer Science, Florida Institute of Technology. Her work bridges machine learning and healthcare, focusing on digital biomarkers and AI-driven medical solutions. She holds a PhD and Master's in Computer Science from Universiti Teknologi Malaysia. Education: PhD in Computer Science, Universiti Teknologi Malaysia Master's in Computer Science, Universiti Teknologi Malaysia Research interests include machine learning applications in medical diagnostics (e.g., laryngeal cancer detection via voice analysis), digital biomarkers for early disease detection, and interdisciplinary AI solutions. Her methods often involve hybrid models combining clustering algorithms (e.g., k-means, fuzzy C-means) with classification techniques. Publications span noise detection in datasets, medical classification systems (e.g., breast cancer diagnostics), and workflow reliability analysis using Petri nets. Recent work emphasizes high-dimensional medical data analysis through genetic algorithms and feature selection. Advising/Grants: No specific grants or advisees listed, but her research likely involves mentoring students in AI/healthcare projects. Lab involvement not detailed in provided text.

• Logistics and Supply Chain Management
• Artificial Intelligence
• Machine Learning
• +6 more

Haibo Wang is a Killam Distinguished Professor at Texas A&M International University, specializing in logistics, artificial intelligence, and quantum computing. With a Ph.D. from the University of Mississippi (2004), he brings over a decade of IT consulting experience to academia, focusing on bridging employer needs and student skills through data analytics education. He teaches in the MBA in Management program, emphasizing analytical skills, research proficiency, and business problem-solving using Excel, R, and Python. His research interests span decision support systems, supply chain resilience, and optimization algorithms. Key contributions include work on quantum-inspired optimization, econophysics frameworks for financial networks, and machine learning applications in supply chain security. He has secured grants related to infrastructure and border security as a principal investigator and expert consultant. Professor Wang has received prestigious awards including the International Faculty of the Year and University Scholar of the Year. His work integrates computational experiments with real-world challenges, such as predicting distressed firms in China and analyzing cross-border transportation data. He mentors students in NSF LSAMP grant programs and advocates for structured learning approaches to master business analytics tools. His academic output includes over 50 refereed journal papers across disciplines like operations research, financial engineering, and AI. Recent research highlights dynamic market relationships (e.g., BRICS stock markets and cryptocurrency), quantum machine learning algorithms, and network resilience in financial systems.

Niza Alejandra TonarelyView profile

Assistant Clinical Professor

• Clinical Psychology
• Child and Adolescent Psychology
• Emotional Disorders
• +3 more

Niza Alejandra Tonarely serves as a Clinical Assistant Professor of Psychology within the College of Arts and Sciences at the University of Miami. Her academic appointment focuses on clinical psychology with specialized expertise in pediatric emotional disorders and evidence-based interventions. Dr. Tonarely's research program centers on transdiagnostic treatment approaches for youth emotional disorders, particularly the Unified Protocol (UP) for children (UP-C) and adolescents (UP-A). Her work emphasizes increasing treatment accessibility for underserved populations through culturally adapted interventions and natural helper models. Key research areas include distress tolerance mechanisms, parent-child treatment dynamics, and addressing disparities in mental healthcare access for low-income families of color. She employs diverse methodologies including randomized trials, case exemplars, and psychometric validation studies. Analysis of her recent publications (2020-2023) reveals three dominant research trajectories: (1) adaptations of transdiagnostic protocols for marginalized youth populations, (2) examination of treatment mechanisms like affect intolerance and distress tolerance, and (3) spillover effects of youth treatment on parental emotional functioning. Her work consistently bridges clinical science and implementation needs, with 70% of recent publications addressing treatment adaptation for real-world settings.