Find Academic Supervisors

• Cloud Computing
• Internet of Things (IoT)
• Data Analytics
• +6 more

Richard Hill is an active professor with an extensive publication record spanning over four decades from 1978 to 2025. His academic career demonstrates significant contributions to computer science, particularly in cloud computing, Internet of Things (IoT), data analytics, and cybersecurity. He has authored two major textbooks: 'Guide to Cloud Computing - Principles and Practice' (2013) and 'Guide to Industrial Analytics - Solving Data Science Problems for Manufacturing and the Internet of Things' (2021). Dr. Hill's research interests focus on practical applications of computing technologies across multiple domains. His work bridges theoretical computer science with real-world industrial applications, particularly in manufacturing, healthcare, smart homes, and environmental monitoring. His research has evolved from early work in networking and community care systems to contemporary research in IoT security, edge computing, and machine learning applications. The trajectory of his work shows a consistent focus on solving practical problems through innovative computing solutions, with increasing emphasis on distributed intelligence and security in recent years. Analysis of his recent publications (2022-2025) reveals a strong focus on IoT security frameworks, machine learning applications for industrial settings, and data quality issues in sensor networks. His work demonstrates a pattern of addressing emerging technological challenges with practical, implementable solutions. The research spans multiple application domains including manufacturing, healthcare, energy management, and conservation, showing his ability to adapt core computing principles to diverse problem spaces. His collaborative approach is evident in the extensive co-author network he has developed over his career. Dr. Hill has maintained an active research program with consistent publication output, including 147 records in the dblp database. His work demonstrates a progression from foundational computing research to applied industrial analytics, reflecting the evolution of the computing field itself. His current research continues to address cutting-edge challenges in distributed systems and data analytics, indicating an ongoing active research program with significant impact in both academic and industrial contexts.

Rebecca BascomView profile

Professor

• Pulmonary Medicine
• Environmental Health
• Respiratory Diseases
• +5 more

Rebecca Bascom is a Professor in both the Department of Medicine and Department of Public Health Sciences at Pennsylvania State University’s College of Medicine. She is a practicing physician specializing in internal medicine, pulmonary and critical care, clinical immunology, and occupational/environmental medicine. She leads the Institute of Energy and Environment’s (IEE) Health and Environment theme, focusing on interdisciplinary research linking environmental factors to human health. Her work addresses inhalation toxicology, interstitial lung diseases, and climate change policy solutions. Her research spans clinical and environmental health domains, including bronchoscopy innovations (e.g., endobronchial ultrasound), lung fibrosis pathophysiology, and public health responses to wildfires and air quality challenges. Key projects include studying wildfire smoke impacts, developing safer cleaning product adoption strategies in disadvantaged communities, and improving healthcare accessibility for rural populations with interstitial lung disease. Bascom’s recent publications emphasize patient-specific models of airway deformation in fibrosis, policy engagement via climate science outreach, and AI-driven lesion detection in bronchoscopy. She collaborates with institutions like CUNY Medicine and ISSA on environmental justice initiatives. Her work bridges clinical practice, environmental science, and public health policy to address complex health challenges.

BUKET TOPTAŞView profile

Lecturer

• Machine Learning
• Medical Imaging
• Deep Learning
• +6 more

Buket Toptaş is a Lecturer at the Department of Software Engineering, Faculty of Engineering and Natural Sciences at Bandırma Onyedi Eylül University. She previously served as a Research Assistant (2019–2022) before transitioning to her current role. Her research focuses on machine learning, medical imaging, deep learning, and image processing, with applications in healthcare diagnostics and biomedical engineering. She has contributed to projects such as the Early Diagnosis of Diabetic Retinal Aneurysms with Retinal Image Analysis , completed in 2022. Her academic duties include teaching courses like Machine Learning, Data Mining, and Image Processing at both undergraduate and graduate levels. She is currently supervising a Master’s thesis on Colonoscopic Image Polyp Segmentation with Yaren Akgöl. Her work spans over 30 publications in journals like Soft Computing , Biomedical Signal Processing and Control , and IEEE Access , with a focus on retinal imaging, polyp detection, and algorithm optimization. Her conference contributions include papers on optimization algorithms (e.g., Biogeography-Based Optimization) and flame detection systems. She actively participates in university research projects and maintains an extensive portfolio of peer-reviewed articles addressing challenges in medical image analysis and deep learning.

Kjosev JosifView profile

Researcher

• Power Electronics
• Embedded Systems
• Circuit Design
• +3 more

Kjosev Josif is an academic affiliated with the Faculty of Electrical Engineering and Information Technologies at Ss. Cyril and Methodius University in Skopje. He holds a position in the Department of Electronics within the Institute of Electronics. His work focuses on practical applications of electronics in education and industrial systems, with a particular emphasis on power electronics, embedded systems, and circuit design. His research interests include developing educational tools using embedded systems (e.g., toys as teaching aids), optimizing power conversion techniques, and designing instrumentation for network infrastructure. He has contributed to advancements in switched-capacitor converters, stepper motor synchronization, and low-component-count power solutions. His publications reflect a blend of theoretical and applied electronics engineering, spanning from foundational circuit design (1996) to modern applications like 3D printer motor control (2018). While no formal awards are listed, his work demonstrates sustained engagement in both academic research and pedagogical innovation. He is currently active in the academic community, contributing to the Department of Electronics’ research and teaching activities without any indication of emeritus or retired status.

• Software Testing Education
• Machine Learning
• Metaheuristic Optimization
• +9 more

Tamara Živković is a researcher at the Faculty of Informatics and Computing, Singidunum University. She holds a PhD in Software Engineering from the School of Electrical Engineering in Belgrade (2024), with prior Master's and Bachelor's degrees in related fields. Education: PhD, Software Engineering (2012-2024), School of Electrical Engineering, Belgrade Master, Audio and Visual Technologies (2008-2010), School of Electrical Engineering, Belgrade Bachelor, Telecommunications and Information Technology (2001-2007), School of Electrical Engineering, Belgrade Her research focuses on software testing education, metaheuristic optimization for machine learning models, and AI applications in cybersecurity, medical diagnostics, and data analysis. She explores hybrid approaches combining neural networks (LSTM, GRU, CNN) with metaheuristic algorithms (PSO, Firefly, Crayfish) for complex prediction tasks. Recent publications span software defect prediction, phishing detection, Parkinson's disease diagnostics, and sentiment analysis. Her work integrates generative adversarial networks for dataset augmentation and applies attention mechanisms in NLP tasks. She has completed advanced certifications in software product management and agile practices from the University of Alberta, along with ISTQB testing certifications.

• Clinical Microbiology
• Infectious Diseases
• Molecular Diagnostics
• +3 more

Cristina R Costales is an Assistant Professor of Clinical Pathology at the University of Southern California (USC). She specializes in clinical microbiology, molecular diagnostics, and infectious diseases, with a focus on developing automated diagnostic tools and investigating emerging pathogens. Her work bridges laboratory medicine, virology, and public health, particularly in resource-limited settings and immunocompromised populations. Dr. Costales has contributed to advancements in metagenomic sequencing, SARS-CoV-2 diagnostics, and outbreak investigations involving Rift Valley fever and tuberculosis. Her research interests encompass the application of machine learning in pathology, the molecular mechanisms of viral immune evasion, and the clinical utility of novel diagnostic assays. Notable projects include the development of an automated vision transformer framework for blood culture analysis and the evaluation of Xpert Ultra for tuberculosis detection in Tanzania. She has also investigated immune responses to SARS-CoV-2 vaccination in immunosuppressed patients and vaccine-associated complications in measles. Dr. Costales’ publications span over a decade, reflecting expertise in both clinical and translational research. Her work frequently addresses diagnostic challenges in tropical diseases, pediatric infections, and rare tumor cases. Despite no listed awards or grants, her contributions to improving diagnostic accuracy and public health responses are evident through her extensive publication record.

• Allergy and Immunology
• Pediatrics
• Asthma Management
• +3 more

Neema Izadi is a Clinical Associate Professor of Pediatrics (Clinician Educator) at the University of Southern California. Their work focuses on allergy, immunology, and pediatric care with an emphasis on clinical diagnostics, primary immunodeficiency, and medical education. Research spans food allergy mechanisms, asthma management, and rare immune disorders. Key research interests include evaluating B-cell function through cellular assays, developing diagnostic tools for immunodeficiency syndromes (e.g., APDS), and investigating environmental factors influencing pediatric allergies. They also explore the transition of severe asthma patients from adolescence to adulthood, emphasizing longitudinal care challenges. Over 20+ publications highlight contributions to clinical practice guidelines, diagnostic protocol development, and case studies in refractory atopic dermatitis. Their work integrates genetics (e.g., FCGR3A variants) and neuroimaging (hippocampal volume studies) with clinical immunology. No scientific awards explicitly noted, but active involvement in CTSI initiatives reflects commitment to translational research. Teaching responsibilities include training future clinicians in allergy/immunology subspecialties, emphasizing evidence-based practices and patient adherence strategies.

James HartsfieldView profile

Adjunct Professor

• Orthodontics
• Craniofacial Genetics
• Tooth Resorption
• +5 more

James Hartsfield is an Adjunct Professor at the Dental School of The University of Western Australia and holds the E. Preston Hicks Endowed Professorship at the University of Kentucky since 2008. His expertise spans craniofacial genetics , orthodontics , and surgical outcomes , contributing to UN Sustainable Development Goals related to education and health. Education: PhD in Medical Sciences (University of South Florida, 1993) MMSc in Oral Biology (Harvard University, 1987) DMD in Dental Medicine (Medical University of South Carolina, 1981) Bachelor of Science in Biology (University of South Carolina, 1977) Research Focus: Dr. Hartsfield investigates genetic determinants of craniofacial disorders, orthodontic surgical techniques, and bone remodeling. His work bridges clinical practice and genetic research, addressing conditions like cleft palate and tooth resorption. Recent projects include evaluating surgical precision using CAD-CAM tools and analyzing genetic associations in Arab populations. Grants & Collaborations: Principal Investigator on a Johnson & Johnson-funded project (2019–2021) assessing mandibular surgery accuracy via customized surgical guides. Active collaborations in orthodontics, genetics, and surgical innovation across multiple institutions. Awards: E. Preston Hicks Endowed Professorship (University of Kentucky) High citation impact with 3,468 citations and an h-index of 33 (Scopus).

• Cognitive Psychology
• Social Psychology
• Communication Studies
• +3 more

Nicolas Fay is an Associate Professor at the University of Western Australia (UWA), affiliated with the School of Psychological Science. He holds academic qualifications including a BSc from the University of Stirling and a PhD from the University of Glasgow. His research focuses on cognitive psychology, social psychology, and communication studies, particularly in areas like misinformation mitigation, AI ethics, and symbolic communication evolution. Education: BSc (Stirling University), PhD (Glasgow University). Research Interests: Fay's work explores the intersection of technology and human behavior, including the impact of artificial intelligence on social perception, the evolution of symbolic communication systems, and strategies to combat misinformation. His studies often involve experimental simulations, cultural transmission models, and behavioral interventions in social media contexts. Grant Projects: He leads major research initiatives such as 'Developing Efficient Interventions to Combat Information Warfare' (2024–2026), investigating scalable solutions for disinformation. His project 'The Role of Large Language Models in Mitigating Disinformation' (2024–2025) examines AI’s dual potential as both a tool and a threat in information ecosystems. Advising & Grants: Fay has supervised 10 students and secured significant funding from institutions like the ARC Australian Research Council and UWA. His work emphasizes practical applications of psychological principles to real-world challenges like social media governance and historical myth analysis.

• Psychology
• Memory Studies
• Healthcare Technology
• +3 more

Michael Ross holds the academic rank of Adjunct Assistant Professor, though his institutional affiliation remains unspecified in the text. His research spans diverse fields including memory science, psychology, medical diagnostics, education, and cultural studies. His work frequently bridges disciplinary boundaries, such as integrating technology into education or analyzing the sociocultural dimensions of memory. Key research interests include the cognitive processes underlying memory validation, the role of self-representation in aging populations, and the ethical implications of historical injustices. He has contributed to advancements in immunoassay optimization for lymphoma detection and explored how visual imagery influences interpersonal conflict resolution. His publications reflect a commitment to interdisciplinary inquiry, addressing topics from cave geology to religious magnanimity. No specific grants, student advisement, or institutional affiliations are detailed in the provided text. Labs or teams are not mentioned, though collaborative work is evident in projects like optimizing medical diagnostic tools and studying cultural memory systems.

George MatsopoulosView profile

Professor

• Nonlinear Image Processing
• Medical Applications
• Medical Image Registration
• +4 more

George Matsopoulos is a tenured Professor at the Division of Information Transmission Systems and Material Technology, part of the School of Electrical and Computer Engineering at the National Technical University of Athens (NTUA). His research focuses on medical image processing, AI-driven healthcare systems, and telemedicine applications. He holds a diploma in Electrical Engineering from NTUA (1988), an M.Sc. (1989), and a Ph.D. (1993) from the Bioengineering Unit at the University of Strathclyde, U.K. His research portfolio includes over 300 peer-reviewed publications in journals, conferences, and books. Key areas include nonlinear image processing for medical diagnostics, 2D/3D medical image registration, computer vision applications in healthcare, and decision support systems for clinical workflows. He has pioneered frameworks for integrating AI into telemedicine, radiomics analysis for cancer detection, and robotic-assisted rehabilitation systems. Recent work emphasizes healthcare robotics ontologies (HERON), deep learning for MRI/PET analysis, and predictive models for neurological conditions like bipolar disorder. He leads interdisciplinary projects such as TeleRehaB DSS (balance rehabilitation) and the Retention Project (heart failure prediction). His contributions span clinical decision support, medical device design, and AI ethics in healthcare systems. Notable achievements include the development of automated segmentation algorithms for organs at risk in radiotherapy, machine learning models for early-stage disease prediction, and AR/VR tools for stroke rehabilitation assessment. His work bridges electrical engineering, computer science, and biomedical applications, addressing unmet clinical needs through technology innovation.

Magnus LöfstrandView profile

Professor

• Mechanical Engineering
• Product Development
• Production Development
• +7 more

Magnus Löfstrand is a Professor of Mechanical Engineering at Örebro University, Sweden. He holds a PhD in Computer-Aided Design (2007) from Luleå University of Technology and a Docent (2015) in Product and Production Development from Chalmers University of Technology. His academic career spans multiple institutions, including Uppsala University and Umeå University prior to his current role. Research focuses on industrial system availability, digital twin technology, and data-driven approaches for optimizing production systems. Key areas include simulation-driven design, predictive maintenance, and integrating mechanical engineering with information technology. His work emphasizes sustainability through resource-efficient production processes and competitive industrial advantages. Teaching responsibilities include courses in the Industrial Engineering and Management program at Örebro University, covering topics like Process Development, Reliability Engineering, and Academic Writing. He supervises bachelor's and master's theses across engineering disciplines. Collaborations with institutions like the University of Nottingham and Umeå University's Logic and Applications group highlight his interdisciplinary approach. He is a member of the American Society of Mechanical Engineers (ASME) and actively participates in international conferences and research projects, including the AVANS MAXI program and digital twin initiatives in mining innovation.

• Ophthalmic Epidemiology
• Patient-Reported Outcomes
• Ophthalmic Imaging
• +5 more

António Filipe Teixeira Macedo is a researcher at Linnaeus University within the Faculty of Health and Life Sciences and Department of Medicine and Optometry . His work focuses on ophthalmic epidemiology , patient-reported outcomes , and ophthalmic imaging , with active projects on myopia progression, AMD treatment pathways, and nerve segmentation in IVCM images. Current projects: Myopia risk factors, AMD therapies, AI for keratitis diagnosis Completed projects: Vision rehabilitation, Acanthamoeba detection AI, capture-recapture prevalence studies Research Interests span vision science , clinical psychophysics , eye movement analysis , and e-health innovations . His publications address myopia , AMD , low vision aids , and vision-related quality of life metrics . Collaborations include institutions in Sweden, Portugal, China, and Europe, with multidisciplinary teams from REVO and HOMe groups. Key methodologies involve AI , longitudinal studies , and capture-recapture epidemiology .

• Structural Engineering
• Railway Infrastructure
• Structural Health Monitoring
• +7 more

Gunnstein Thomas Frøseth is an Associate Professor at the Department of Structural Engineering, Norwegian University of Science and Technology (NTNU). His research focuses on predicting the remaining service life of steel railway bridges, particularly addressing challenges in fatigue analysis, structural health monitoring, and model updating techniques. He leads projects combining field measurements with numerical simulations to assess bridge conditions under evolving load conditions. Key research areas include fatigue life estimation, finite element analysis precision, and the integration of machine learning for infrastructure diagnostics. He collaborates with industry partners to develop practical solutions for railway infrastructure management, emphasizing cost-effective monitoring and predictive maintenance strategies. His team applies advanced techniques like operational modal analysis, photogrammetry, and deep learning to improve bridge safety and longevity. Recent work includes corrosion detection systems, rivet inspection algorithms, and vibration analysis methodologies. His contributions bridge theoretical modeling with real-world applications in transportation infrastructure.

• Tuberculosis Diagnosis
• HIV Testing and Treatment
• Public Health Interventions
• +3 more

Elizabeth Corbett is a Researcher in the Department of Immunobiology at Yale School of Medicine, Yale University. Her work focuses on infectious disease epidemiology, particularly tuberculosis (TB) and HIV diagnosis and intervention strategies in resource-limited settings. She leads studies on diagnostic test validation, community-based health program implementation, and healthcare system optimization in low-income countries. Her research addresses critical gaps in global health, including improving TB testing accuracy through novel assays, evaluating HIV self-testing models, and assessing the cost-effectiveness of rapid diagnostic tools in severe illnesses. Corbett’s interdisciplinary approach combines epidemiological analysis with implementation science, emphasizing real-world applicability in settings like Malawi, Nigeria, and Zambia. Key areas of contribution include: Development of diagnostic protocols for TB meningitis and pediatric TB Optimization of HIV-Schistosomiasis combined interventions Historical epidemiology studies informing modern TB control strategies Health system cost analyses for sustainable service delivery Her recent publications highlight advancements in computer-aided TB diagnosis, urine-based testing, and community engagement strategies to enhance disease detection rates. Corbett collaborates extensively with global health organizations, contributing to evidence-based policy recommendations for improving healthcare access in underserved regions.