جست‌وجوی استاد و پژوهشگر

Claire O'Neillمشاهده پروفایل

پژوهشگر ارشد

• Clinical Trials
• Qualitative Methods
• Health Services Research
• +۳ مورد دیگر

Dr Claire O'Neill is a Senior Research Fellow at the Swansea University Medical School, specializing in Health Data Science. She is the Manager of the South West Wales Research Design and Conduct Service, funded by Health and Care Research Wales, and has over 15 years of post-doctoral experience in health services research and clinical trials. Research Expertise: Trials, Qualitative Methods, Health Services Research Committee Involvement: Member of Swansea University Health Board’s Joint Scientific Research Committee Research Themes include the integration of clinical trials with qualitative data in emergency medicine, trauma care, and healthcare policy. Her work focuses on blunt chest trauma, self-treatment of COPD exacerbations, and sun safety policies in Welsh schools. Publications highlight trials like STUMBL and ELECT2, emphasizing feasibility studies and patient-clinician communication in trauma management. She also explores health-related quality of life assessments and third-sector influence on NHS Wales. Teaching: Leads module PM-353: Introduction to Clinical Trials , covering trial methodology and responsible reporting of outcomes. Supervision: Available for postgraduate supervision in health data science and clinical research areas.

Edward J. Schumacherمشاهده پروفایل

استاد

• Health Care Labor Markets
• Health Economics
• Labor Economics
• +۵ مورد دیگر

Edward J. Schumacher is a Professor at Trinity University's Health Care Administration department. His work focuses on healthcare labor markets, health economics, and quantitative methods. Education: Ph.D. from Florida State University, M.A. and B.A. from University of North Carolina at Greensboro Research Interests include empirical analysis of unions, labor markets for workers with disabilities, hospital competition, and technological change in healthcare. His publications explore wage differentials, monopsony power, and skill dynamics in nursing labor markets. Notable trends in publications involve union wage premiums, disability labor mobility, and hospital technology investment. His research spans labor economics, health informatics, and institutional finance. Professional Memberships include Academy Health, International Health Economics Association, and Society of Labor Economists.

Jeannine M. Roweمشاهده پروفایل

استاد

• Gerontology
• Social Work
• Family Caregiving
• +۵ مورد دیگر

Dr. Jeannine M. Rowe is a Professor in the Department of Social Work at the University of Wisconsin-Whitewater, College of Letters and Science. She holds a Ph.D. in Applied Gerontology (2010) and Master’s in Social Work (2001) from the University of Wisconsin-Milwaukee and a B.A. in Social Work and Sociology from the University of Nevada-Reno. National Academies of Practice – Social Work Fellow New York Academy of Medicine – Social Work Fellow Hartford Social Work Doctoral Fellow Hartford Foundation’s Pre-Dissertation Program awardee Her research focuses on gerontology, family caregiving, effectiveness of social work services in aging and health care, and interprofessional collaboration. Recent work explores aging and health at the intersection of artificial intelligence and privacy/security of smart medical devices for older adults. Over her career, she has published extensively on care management models, program evaluation, and team-based health care approaches. Dr. Rowe actively mentors undergraduate and graduate students in the University of Wisconsin-Whitewater’s Undergraduate Research Program and collaborates with colleagues in clinical health and informatics. She teaches courses in social work macro practice, group work, research, program evaluation, and co-leads an international study program in Costa Rica focused on health and aging. Key grant: Hartford Foundation’s Pre-Dissertation Program in Geriatric Social Work Research contributions: AIMS model evaluations, EHR documentation practices, interprofessional care training Community involvement: Consultant to health care organizations, board member roles

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۵ مورد دیگر

Prof. Dr. Mehmet Reşit Tolun is a full-time Professor in the Department of Software Engineering at Çankaya University (Turkey) since 2022. Previously held full-time professor positions at Konya Food and Agriculture University (2020-2022), Aksaray University (2013-2017), and TED University (2011-2013), along with a part-time professorship at Başkent University (2017-2020). Specializes in Artificial Intelligence , Machine Learning , and Data Mining , with a focus on deep learning applications in aerospace, biomedical data analysis, and software process improvement. PhD in Computer Science (University of Kent, 1985) MSc in Computer Science (University of Kent, 1982) BSc in Physics and Computer Science (University of Kent, 1981) Research Interests span deep learning frameworks, hybrid expert systems, software engineering methodologies, and biomedical signal processing. Publications emphasize practical implementations in medical diagnostics, robotics, and agricultural pest detection. Scientific Awards include the IEEE Third Millenium Medal (2000). Supervised over 55 graduate students, including Burak Çetin, Uğur Özotuk, and Mahinur Doğan. Collaborated with researchers from Orta Doğu Teknik Üniversitesi , Çankaya University , and Aksaray University .

• Artificial Intelligence in Healthcare
• Digital Health Interventions
• Chronic Disease Prevention
• +۱۵ مورد دیگر

Dr. Yoshimi Fukuoka is a Professor at the University of California, San Francisco (UCSF) School of Nursing , specializing in Physiological Nursing . She holds a PhD in Nursing and Postdoctoral Fellowship from UCSF, with a career focused on AI-driven health interventions , chronic disease prevention , and mobile health (mHealth) applications for diverse populations. Her research bridges artificial intelligence and behavioral health , emphasizing personalized physical activity programs , cardiovascular risk reduction , and diabetes prevention . She has developed AI chatbots to improve heart disease awareness and conducted clinical trials on metabolic syndrome and colorectal cancer survivorship . Recent publications highlight her work on: AI chatbots for heart attack knowledge and physical activity interventions Machine learning in diabetes risk prediction and microRNA analysis Cultural adaptations of mHealth for Asian Americans and Latinos Behavioral analytics in weight loss and exercise adherence Scientific awards include: 2014-2017: National Science Foundation EAGER Grant 2011-2013: UCSF Diabetes Family Fund Award 2010-2012: American Heart Association National Clinical Research Program Award 2008: Marie Cowan Promising Young Investigator Award Her work spans UCSF , with collaborations across NIH , Alzheimer's Association , and Noyce Foundation , addressing health disparities , digital health policy , and precision health through grants like NIH R01HL104147 and K24NR015812 . Media coverage includes USA Today , NHLBI News , and UCSF News for her AI in nursing innovations.

Janne Heikkiläمشاهده پروفایل

استاد

• 3D Computer Vision
• Algebraic Geometry
• Biomedical Image Analysis
• +۵ مورد دیگر

Janne Heikkilä is a Professor at the Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland. With over 30 years of experience in computer vision and machine learning, he leads the Center for Machine Vision and Signal Analysis (CMVS) and has contributed extensively to both theoretical and applied research. Research Interests: 3D computer vision, biomedical image analysis, computational photography, and deep learning. Scientific Leadership: IAPR Fellow, Senior IEEE Member, and former President of the Pattern Recognition Society of Finland. His work spans computer vision, radiotherapy planning, and biomedical imaging, with over 200 publications and 14,000 citations. He has secured funding from prestigious organizations like the Academy of Finland and Business Finland. His recent research focuses on debiasing AI models, 6D object pose estimation, and radiotherapy dose prediction. Scientific Awards: IAPR Fellow Senior Member of IEEE

• Global Health
• Public Health
• Epidemiology
• +۵ مورد دیگر

Mohsen Malekinejad is an Associate Professor at the University of California, San Francisco (UCSF) School of Medicine and serves as the director of the Center for Resilient Societies and Technology (CREST) . He is a core member of the RESILIENT network at the University of California system, focusing on pandemic intelligence and community resilience. His career spans 20 years of public health experience with expertise in evidence-based medicine, systematic reviews, and translating research into policy. Education: DrPH (UC Berkeley, 2008), MPH (UC Davis, 2003), MD (Tehran Azad University, 1999), Postdoctoral Studies (UCSF, 2009) Dr. Malekinejad's research addresses health disparities among marginalized populations globally, focusing on substance use disorders, HIV/HCV, and pandemic response strategies . His work includes methodological innovations for sampling hard-to-reach groups (e.g., homeless populations, drug users) and economic evaluations of public health interventions . Recent publications highlight systematic reviews on topics like COVID-19 exposure notification systems, TB testing cascades, and HIV risk behaviors . His methodological strengths include respondent-driven sampling, meta-analysis, and health equity frameworks. He has led major projects funded by NIH, CDC, and WHO, including the California Department of Public Health's COVID-19 Exposure Notification system implementation. Dr. Malekinejad also maintains an active role in graduate-level public health education and collaborates across disciplines to strengthen translational research.

• Sports Medicine
• Exercise Physiology
• Heat Stress
• +۶ مورد دیگر

Dieter Leyk serves as a Professor at the German Sport University Cologne within the Institute of Exercise Training and Sport Informatics, specifically in the Section Exercise Physiology and leading the Performance Physiology Research Group. His work focuses on translating exercise science into public health initiatives, with contact details including phone +49 221 4982-6163 and email leyk@dshs-koeln.de. His primary research areas include: Sports Medicine and Exercise Physiology Heat Stress and Thermoregulation in athletic performance Injury prevention and rehabilitation engineering Analysis of sedentary behavior and health promotion strategies Substance use in sports (analgesics and dietary supplements) Recent publications (2023-2025) demonstrate a shift towards large-scale epidemiological studies, particularly the ActIv project involving over 50,000 runners. His work bridges clinical sports medicine with public health policy, addressing critical issues like pain management and nutritional supplementation in athletic populations. The research consistently emphasizes practical applications for improving athlete safety and public health outcomes. Collaborative networks are evident through 88 shared publications with Thomas Rüther and partnerships with researchers like Stefanie Klatt. While specific grant details and student mentorship records aren't detailed in available sources, his leadership in major projects like ActIv-KV indicates substantial research funding and team management responsibilities.

Nikos Aletrasمشاهده پروفایل

استاد

• Natural Language Processing
• Machine Learning
• Computational Social Science
• +۲ مورد دیگر

Nikos Aletras is a Professor of Natural Language Processing at the University of Sheffield's School of Computer Science, where he serves as Head of the Natural Language Processing research group and is co-affiliated with the Machine Learning group. His academic journey began with a Bachelor's degree in Computer Science from the University of Crete, followed by a PhD in Natural Language Processing at the University of Sheffield. Prior to his current position, he worked as a research scientist at Amazon (Core ML and Alexa) and as a research associate at UCL's Department of Computer Science. Aletras' research spans multiple domains within AI, with particular emphasis on Natural Language Processing applications across social science, legal contexts, and data science. His work demonstrates a consistent focus on practical implementations of NLP techniques to solve real-world problems, especially in computational social science and legal technology. He has developed innovative text analysis methods that bridge traditional disciplinary boundaries, creating tools applicable across multiple scientific domains. His recent publications reveal a strong trend toward efficient and responsible AI, with significant work on model compression, hallucination mitigation in language models, and ethical considerations in computational social science research. The publications also show deep engagement with multilingual NLP challenges, explainable AI, and applications of NLP to social media analysis and legal contexts. Area Chair Award: Society and NLP (2023) Aletras has secured substantial research funding as both Principal Investigator and Co-Principal Investigator, including grants from EPSRC, ESRC, Leverhulme, EC Horizon 2020, and industrial partners like Amazon. His current projects focus on efficient deployment of large language models, addressing socio-technical limitations of LLMs for medical and social computing, and developing speech and language technologies. He actively supervises PhD students and collaborates with researchers across multiple disciplines. He leads the Natural Language Processing research group at Sheffield, which focuses on advancing NLP methodologies while applying them to diverse domains including computational social science, legal informatics, and healthcare technologies. The group maintains strong industry connections, particularly with technology companies working on language technologies, and collaborates with legal scholars and social scientists on interdisciplinary projects.

• Emergency Medicine
• Urgent Care Systems
• Health Services Research
• +۴ مورد دیگر

Suzanne Mason is a Professor of Emergency Medicine at the School of Medicine and Population Health , University of Sheffield, and a Consultant in Emergency Medicine at Sheffield Teaching Hospitals Trust. Her career spans over three decades, with a focus on evaluating complex interventions in urgent and emergency care, particularly for older adults and frail populations. Education: MBBS (1990), FRCS, FFAEM, MD (Emergency Medicine) Key Research Areas: Emergency care systems, clinical decision-making, geriatric emergency care, health informatics, and multi-centre mixed-methods studies Her research has directly influenced emergency care delivery, including studies on exit block in EDs , trauma networks , and digital ambulance records . She has led major projects such as Connected Health Cities (2016–2018) and RADOSS (risk prediction for seizures). Grants include £1.4 million from NIHR and £692,206 from the Department of Health . Scientific awards include an MD from Royal College of Surgeons Research Fellowship and leadership roles in NIHR-funded initiatives . She has pioneered collaborative models for ambulance services , care home integration , and frailty screening in EDs. Her work bridges clinical practice, policy evaluation, and digital innovation, with over 150 publications and mentorship in BMJ Open and Emergency Medicine Journal editorials.

Sneha Dasمشاهده پروفایل

استادیار

• Speech and Language Technology
• Machine Learning
• Data Privacy
• +۵ مورد دیگر

Sneha Das is an Assistant Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), specializing in Speech and Language Technology, Machine Learning, and Privacy-Preserving AI. Her research bridges technical innovation with applications in mental health and physiological signal analysis. Her work focuses on Speech Emotion Recognition , Distributed Speech Processing , and Explainable AI , with recent publications exploring model interpretability, speaker anonymization, and physiological data analysis for emotion detection. She actively supervises PhD students in projects involving AI for mental health and hydroacoustic modeling of fish behavior. Key Research Areas: Speech Emotion Recognition (SER) Privacy and Fairness in Speech Processing Transfer Learning with Physiological Time Series AI Applications in Health and Aquaculture Notable achievements include earning a DSc (Tech) degree for her thesis on robust distributed speech processing. She also contributes to educational activities, including teaching applied statistics and R programming to PhD students.

Ayah Ziriklyمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Health Informatics
• Mental Health
• +۵ مورد دیگر

Ayah Zirikly is an Assistant Research Scientist at the Center for Language and Speech Processing (CLSP) at Johns Hopkins University, specializing in Natural Language Processing applications for mental health and clinical informatics. Her work bridges computational linguistics with real-world healthcare challenges, particularly in suicide risk assessment and bias detection in medical documentation. Research Focus: Dr. Zirikly pioneers NLP solutions for mental health informatics, with landmark contributions including the UMD Reddit Suicidality Dataset for suicide risk assessment and NLP tools for Social Security Administration disability eligibility processes. Her expertise spans Arabic NLP (co-developer of MADAMIRA toolkit), transfer learning for low-resource settings, and analysis of stigmatizing language in clinical records. Recent work investigates social determinants of health through electronic health record analysis and develops frameworks for detecting AI dataset bias. Publication Trends: 2023-2025 publications reveal three dominant threads: (1) Suicide prevention via social media analysis and data warehouse modeling, (2) Linguistic bias detection in medical records with focus on race/gender disparities, and (3) Synthetic data generation for clinical communication. Her leadership in CLPsych workshops establishes her as a key contributor to clinical NLP benchmarking. Professional Background: Holds a PhD in Computer Science from George Washington University (Mona Diab's NLP lab) and completed postdoctoral training at the National Institutes of Health. Current research extends her NIH work on mobility/mental health status extraction for disability determination while addressing critical gaps in health equity through computational methods.

Liane Colonnaمشاهده پروفایل

استادیار

• AI Ethics
• Data Protection Law
• Algorithmic Regulation
• +۲ مورد دیگر

Liane Colonna is an Assistant Professor in Law and Information Technology at the Department of Law, Stockholm University , where she investigates ethical and legal challenges arising from AI-driven practices in higher education. She also engages in methodologically oriented research at the intersection of AI and Law, contributing to the Wallenberg AI, Autonomous Systems and Software Program – Humanities and Society. Additionally, Liane serves as the director of the Swedish Law and Informatics Research Institute (IRI) and is a member of the New York Bar since 2008. Primary Affiliation: Department of Law, Stockholm University Institute Leadership: Director, Swedish Law and Informatics Research Institute (IRI) Professional Status: Member of the New York Bar Research Interests: Ethical and legal challenges of AI in higher education Methodological approaches in AI and Law Data protection and privacy by design Regulatory frameworks for AI and emerging technologies Privacy implications of lifelogging and health IoT International data governance and surveillance law Publications demonstrate expertise in AI regulation, GDPR compliance, and privacy-preserving technologies, particularly for assisted living and educational contexts. Her work bridges technical implementation with legal accountability, emphasizing human oversight and ethical design.

Lilja Øvrelidمشاهده پروفایل

استاد

• Natural Language Processing
• Machine Learning
• Computational Linguistics
• +۳ مورد دیگر

Lilja Øvrelid is a Professor at the Department of Informatics, University of Oslo, leading the Language Technology Research Group. Her research focuses on syntactic and semantic text processing using machine learning techniques such as dependency parsing, negation analysis, and sentiment analysis. She teaches courses including IN1140: Introduction to Language Technology , IN5550: Neural Methods in NLP , and INF5830: Natural Language Processing . Her academic interests span natural language processing, machine learning, and computational linguistics, with a particular emphasis on Norwegian language technology. Recent publications highlight work in sentiment analysis (including patient feedback), event extraction from Norwegian news, benchmarking language models, emotion analysis for under-resourced languages (Pashto, Farsi-Dari), and bias detection in multilingual models. She actively contributes to the development of Norwegian language resources such as NorBench, NorQuAD, and NoReC. Current projects include BigMed and SIRIUS , focusing on biomedical text mining and AI infrastructure. Collaborations with colleagues like Erik Velldal, David Samuel, and Vladislav Mikhailov are frequent in her work. Despite no explicit mention of scientific awards, her contributions to NLP and computational linguistics are substantial through publications, datasets, and tool development.

• Computer Supported Cooperative Work (CSCW)
• Human-Centered Computing
• Human-Computer Interaction
• +۷ مورد دیگر

Pernille Bjørn is a Professor in Computer Supported Cooperative Work (CSCW) at the Department of Computer Science , University of Copenhagen (DIKU), where she has been since May 2015. Her research investigates collaborative work practices to design cooperative technologies, focusing on domains like healthcare, global software development, startup companies, and digital fabrication. Faculty of Science, University of Copenhagen Human-Centred Computing Section Research Interests : Bjørn’s work spans CSCW , Human-Computer Interaction , and Digital Fabrication , with applications in healthcare systems, cross-cultural software development, and inclusive technology design. She explores collaborative virtual reality training, FemTech, and crisis computing. ACM Distinguished Member (2024) Publications : Published in top venues like ACM Transactions on Computer-Human Interaction , CSCW , and CHI , her recent work examines hybrid work asymmetry, neurodiverse accessibility, and art-driven collaborative research.