جست‌وجوی استاد و پژوهشگر

• Bioinformatics and Computational Biology
• Cancer Precision Medicine
• Computational Pathology
• +۵ مورد دیگر

Mattias Rantalainen is a Senior Lecturer and Docent at Karolinska Institutet's Department of Medical Epidemiology and Biostatistics, where he leads the Predictive Medicine research group. His work focuses on applying statistical machine learning, artificial intelligence, and big data analytics to medical research, with particular emphasis on computational pathology and cancer precision medicine. The research group maintains over 300,000 whole slide images for population-based studies, primarily focused on breast, prostate, and colorectal cancer. Dr. Rantalainen completed his PhD at Imperial College London developing multivariate pattern recognition methods with applications in metabonomics. He previously held a research fellowship (2009-2013) with joint affiliation at the Department of Statistics and the Wellcome Trust Centre for Human Genetics at the University of Oxford, where he was awarded the MRC Centenary Early Career Award (2012-2013) and a Medical Research Council Special Training Fellowship in Biomedical Informatics (2009-2012). He holds an undergraduate degree in Engineering Biology (combined BSc/MSc) from Umeå University in Sweden. His research interests span computational pathology, cancer precision medicine, and AI-driven medical research. The Predictive Medicine group develops and applies AI and machine learning methodologies for predictive modeling in biomedical applications. Their mission is to transform large biomedical datasets into clinically relevant predictions at the individual level, with a particular focus on precision pathology applications where the goal is to predict patient outcomes. Their work integrates comprehensive molecular profiling (DNA- and RNA-sequencing), clinical information, and medical imaging data. Analysis of his recent publications reveals a strong trend toward developing and validating deep learning models in computational pathology, particularly for breast cancer applications. His work focuses on risk stratification, histological grading, and gene expression prediction from histopathology images. There's a clear progression from method development to clinical validation and implementation, with increasing emphasis on real-world applicability and comparison with established clinical assays. His research bridges the gap between computational methodology and clinical practice in cancer diagnostics. MRC Centenary Early Career Award (2012-2013) Medical Research Council (MRC) Special Training Fellowship in Biomedical Informatics (2009-2012) Dr. Rantalainen serves as main supervisor for PhD students Philippe Weitz and Abhinav Sharma, and as co-supervisor for several other doctoral candidates including Dusan Rasic, Sandra Kristiane Sinius Pouplier, and Tewodros Yalew. He coordinates the Swedish AI Precision Pathology (SwAIPP) consortium, which focuses on translation and implementation of AI-based pathology. His group has received significant funding, including a recent 120 million SEK grant to the Department of Medical Epidemiology and Biostatistics from Swedish funding agencies. The Predictive Medicine group operates within the Department of Medical Epidemiology and Biostatistics at Karolinska Institutet, coordinating several national and international initiatives including the CHIMES study (www.chimestudy.se), ABCAP (www.abcap.org), and the Swedish AI Precision Pathology consortium (www.swaipp.org). The group has developed numerous AI-based tools that improve cancer diagnosis and risk prediction, with several projects advancing toward clinical implementation as regulatory-approved medical devices. Their work represents a significant contribution to the field of precision pathology and AI-driven cancer diagnostics.

• Telecommunications
• Network Security
• Computer Networks
• +۶ مورد دیگر

Prof. Christos Douligeris is a faculty member at the Department of Informatics of the University of Piraeus. He previously served as an Associate Professor at the University of Miami, USA, and holds a Diploma in Electrical Engineering (1984) from the National Technical University of Athens and a PhD (1990) from Columbia University. His career spans academia, industry, and policy-making, including leadership roles in Greek government agencies like Electronic Government S.A. and the Communications Privacy Authority. Diploma in Electrical Engineering, National Technical University of Athens (1984) MS, MPhil, PhD in Electrical Engineering, Columbia University (1985, 1987, 1990) His research focuses on computer networks, emphasizing security, protocols, and applications in precision agriculture, e-health, and IoT. He also explores the educational potential of information and communication technologies at all levels, from vocational training to higher education. His recent publications address cybersecurity in education, AI-driven threat landscape modeling, and immersive digital tools (AR/VR) for pedagogy and cultural heritage. Prof. Douligeris has received significant recognition, including the State Scholarship Foundation (IKY) award for transferring expertise from Greeks abroad to Greece (1987), a Fulbright scholarship (1988), and multiple honors for best work in telecommunications. His research has been funded by bodies such as the European Commission, National Science Foundation, and Greek General Secretariat for Research and Technology. He has supervised over 15 PhD theses and 100+ MSc theses, contributing extensively to academic training and mentorship. He co-authored the book Network Security: Current Status and Future Directions and edited special issues for the IEEE Communications Magazine. His work extends to policy development, curriculum design, and organizing international conferences in communications and security. Though not explicitly mentioning labs or teams, his activities include developing systems like NERO (Cybersecurity Awareness Ecosystem for SMEs) and ACSIS (Intelligent Medical System for Pre-hospital Healthcare).

Michael S. Leonardمشاهده پروفایل

استاد

• Improvement Science
• Medical Errors
• Patient Safety
• +۴ مورد دیگر

Michael S. Leonard is a Professor at the University of Rochester's School of Medicine and Dentistry , with joint appointments in the Department of Pediatrics and Department of Public Health Sciences . He is a board-certified pediatric hospitalist specializing in comprehensive, family-centered inpatient care for infants and young children, particularly emphasizing patient safety and quality improvement. Education: MD from SUNY at Buffalo (1996), Residency in Pediatrics (1997-1999), Internship (1996-1997). Research Interests : Dr. Leonard's work focuses on Improvement Science , aiming to (1) reduce medical errors and adverse events, (2) enhance patient care quality, and (3) integrate interprofessional education in healthcare. His research spans clinical diagnostics, healthcare policy, and systems management, with a strong emphasis on pediatric-specific challenges. Publications highlight advancements in patient safety metrics, quality improvement frameworks, and clinical training tools. Notable works include the RISE Assessment for safety competencies and studies on resource utilization in tertiary care. Scientific Awards : ICARE Bronze Star (2023, 2020, 2019) Meliora Award on behalf of SMH Employee Health (2021) ICARE Silver Star (2019) Hospital Association of New York State Pinnacle Award (2015) Board Service Excellence Team Award (2012) Additional Achievements : He has received accolades for patient and family-centered care, clinical service, and academic excellence, including Phi Beta Kappa (1991) and Summa Cum Laude (1992).

Alain Gauvinمشاهده پروفایل

مدرس

• Medical Imaging Informatics
• Medical Physics
• Radiology
• +۲ مورد دیگر

Alain Gauvin is a Lecturer affiliated with McGill University's Medical Physics Unit École Polytechnique de Montréal's Department of Continuing Education Université de Montréal's Department of Radiology . He holds advanced degrees in Physics, Medical Physics, and Management Sciences. His research focuses on Medical Imaging Informatics , particularly Digital mammography technology Quality control protocols for medical displays Imaging standards in public health programs . He has authored three key publications advancing clinical practice in diagnostic imaging. He is certified by the American Board of Medical Physics, American Board of Radiology, and American Board of Imaging Informatics. In 2017, he was named a Fellow by the Canadian College of Physicists in Medicine. His work bridges clinical imaging, technology evaluation, and healthcare management.

• Environmental Science
• Geospatial Informatics
• Machine Learning
• +۳ مورد دیگر

Hamid Mehmood serves as an Adjunct Assistant Professor at McMaster University's School of Earth, Environment & Society, contributing to interdisciplinary environmental and societal research through computational methods. His scholarly focus spans multiple domains: Environmental Science (flood/reservoir mapping, carbon cycle analysis) Geospatial Informatics (GNSS/WLAN positioning, Landsat/GIS platforms) Machine Learning (neural networks for urban/environmental applications) Public Health (AMR, cardiovascular coping, clinical trials) ICT for Development (Urdu systems for farmers, mobile scaling) Recent publications demonstrate a shift toward urgent global challenges: 2024 machine learning-driven urban slum mapping in Indonesia, 2022 environmental health reviews on antimicrobial resistance, and 2021 geospatial platforms for flood management. His work consistently bridges technical innovation (e.g., Google Earth Engine, IVIG trials) with socio-economic contexts in Pakistan, Saudi Arabia, and Southeast Asia, while earlier research (2013-2015) established foundations in neural network-optimized positioning systems.

Janna Hastingsمشاهده پروفایل

استادیار

• Medical Knowledge Systems
• Artificial Intelligence in Healthcare
• Ontology Development
• +۴ مورد دیگر

Janna Hastings is Assistant Professor for Medical Knowledge and Decision Support at the Institute for Implementation Science in Health Care (Faculty of Medicine) at the University of Zurich since August 2022, while also serving as Vice-Director of the School of Medicine at the University of St. Gallen. Her research focuses on digitalization in clinical contexts, examining how AI-driven knowledge systems reshape clinical practice, professional identity, and doctor-patient relationships. Education: PhD in Computational Biology (University of Cambridge, 2019), part-time MSc in Computer Science (University of South Africa, 2011), MSc in Philosophy (Open University, 2012) Prior Roles: Group Coordinator at European Bioinformatics Institute (2006-2015), Postdoctoral Researcher at Otto-von-Guericke University Magdeburg (2019-2022), Co-Leader of Human Behaviour-Change Project at University College London (2017-2022) Her research spans ontology development for biomedical domains (ChEBI, Human Behaviour Ontology), AI applications in healthcare decision-making, and behavior change interventions. Key projects include: Building ChEBI molecular ontology Developing Human Behaviour-Change Project knowledge system Ontology-driven mental health frameworks LLM applications in radiation oncology Time-series modeling of metabolism in ageing She explores the capabilities and limitations of clinical AI systems, with publications in JMIR and Lancet Digital Health , covering topics like bias prevention in generative AI and proteomic biomarker discovery. Her work bridges biomedical research with implementation science and digital ethics.

Sabrina Heike Kesslerمشاهده پروفایل

پژوهشگر

• Science Communication
• Health Communication
• Digital Media
• +۳ مورد دیگر

Dr. Sabrina Heike Kessler is a Senior Research and Teaching Associate at the Department of Communication and Media Research, University of Zurich (Faculty of Arts and Social Sciences). She holds a PhD in Communication Science from the University of Jena and focuses on digital science & health communication, AI literacy, and misinformation research. Her work combines empirical methods like eye tracking, content analysis, and surveys with theoretical frameworks from communication science. Education: PhD in Communication Science (University of Jena, 2015), Master's in Media Science, Psychology, and German Linguistics Research Areas: Specializing in digital health communication, the impact of AI on information search, scientific uncertainty communication, and combating misinformation through empirical studies. Her work addresses digitalization, user behavior on online platforms, and evidence-based communication strategies. Article Trends: Recent publications examine AI's role in science communication, misinformation mechanisms on YouTube, and digital literacy interventions. Collaborative work highlights cross-disciplinary approaches to health communication and political information seeking. Scientific Awards: UZH Teaching Fund for AI course (2025) DIZH grants (2024) Swiss Young Academy grants (2023-2025) Media Authority of NRW grant (2023) OFCOM Switzerland grant (2022-2023) Grants & Projects: AI in Science and Society (Swiss Young Academy) Digitale Resilienz durch Storytelling (DIZH) SciComm meets Comedy (DIZH) Effect of Disinformation on Opinion Formation (Media Authority NRW) Teaching: Undergraduate: Digital Literacy, AI in Health Communication, Fake News Analysis Postgraduate: Content Analysis, Eye Tracking Research Labs & Teams: Leader of peer-mentoring group 'MFG' (2019-2021) Co-founder of DOCA database Collaborations with Swiss Young Academy, ECREA, DGPuK

• Pediatric Surgery
• Minimally Invasive Surgery
• Robotic Surgery
• +۳ مورد دیگر

David E. Skarda, MD, MBA, serves as Associate Professor (Clinical) in the Department of Surgery and Adjunct Assistant Professor in Pediatrics at the University of Utah School of Medicine. As a board-certified pediatric surgeon at Primary Children's Hospital (Salt Lake City and Lehi, Utah) and St. Vincent Hospital (Billings, Montana), he is the sole DaVinci robot-certified pediatric surgeon in the Intermountain West, specializing in minimally invasive and robotic techniques for children from infancy through adolescence. His educational background includes: B.S. in Molecular Biology/Chemistry from Brigham Young University M.D. from Albert Einstein College of Medicine of Yeshiva General Surgery Residency at University of Minnesota Medical Center Pediatric Surgery Fellowship at The Ohio State University - Nationwide Children's Hospital Additional fellowships in Minimally Invasive Surgery, Surgical Infectious Disease, and Surgical Critical Care Research at University of Minnesota MBA from University of Utah Dr. Skarda's clinical expertise spans elective procedures including hernia repairs, cholecystectomy, G-tube management, and robotic surgeries for reflux, MALS, SMA, and chest wall deformities, alongside emergent care for appendicitis, intestinal obstructions, and congenital anomalies. His research focuses on quality improvement in pediatric surgical outcomes , with particular emphasis on opioid stewardship, appendicitis management protocols, and health disparities. He actively employs natural language processing for surgical complication surveillance and contributes to environmental sustainability initiatives in operating rooms. Analysis of his 15 most recent publications (2019-2024) reveals consistent themes in surgical outcomes research, including: Development of evidence-based protocols for antibiotic use and CT scan reduction in appendicitis Examination of racial disparities in post-discharge surgical care Innovation in machine learning applications for infection surveillance Business and operational aspects of pediatric surgical practice Pandemic-era adaptations in surgical management Dr. Skarda collaborates extensively through national organizations including the American Academy of Pediatrics Section on Surgery and APSA Quality and Safety Committee. His leadership in multidisciplinary teams addresses complex conditions like median arcuate ligament syndrome (MALS) and superior mesenteric artery syndrome (SMA), emphasizing patient education and telemedicine accessibility. He maintains active clinical practice with 2025 patient reviews highlighting his compassionate care and thorough consultations.

Daniel Leungمشاهده پروفایل

استاد

• Mucosal Immunology
• MAIT Cells
• Cholera
• +۷ مورد دیگر

Daniel Leung is a Professor of Internal Medicine and Adjunct Professor of Microbiology and Immunology at the University of Utah . He holds a B.Sc. and M.Sc. from the University of British Columbia and an M.D. from Wake Forest University School of Medicine . His research focuses on Mucosal-Associated Invariant T (MAIT) cells in infections like cholera , sepsis , and diarrheal diseases , with emphasis on their immune regulatory roles and vaccine implications. Education: B.Sc., University of British Columbia M.Sc., University of British Columbia M.D., Wake Forest University School of Medicine Leung's work examines how MAIT cells contribute to B cell help , antibody production , and mucosal immunity . His team investigates these cells in human tonsil germinal centers and mouse models , particularly in cholera vaccine development using MAIT-activating ligands . Recent publications highlight his efforts in serosurveillance for cholera and SARS-CoV-2 , integrating statistical and machine learning approaches to estimate disease incidence from cross-sectional data. He also develops electronic clinical decision support tools (eCDST) for diarrhea management in low- and high-resource settings , aiming to reduce antibiotic misuse and improve patient outcomes. Key collaborations include the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) , GHESKIO (Haiti) , and institutions like Johns Hopkins and University of Florida . His research is funded by NIH (R01AI130378, R01AI135114, R01AI135115) and the Bill & Melinda Gates Foundation (OPP1198876).

• Trauma Surgery
• Surgical Critical Care
• Emergency General Surgery
• +۱ مورد دیگر

Dr. Toby M. Enniss is an Associate Professor of Surgery at the University of Utah, where he serves as the Trauma Medical Director of the University of Utah Level 1 Trauma Center and Director of the Acute Care Surgery Service. He joined the Department of Surgery in 2010 and has been instrumental in developing the Acute Care Surgery system at the university across clinical, educational, administrative, and research domains. His educational background includes: B.A. in Mathematics (with minors in Chemistry and Biology) from the University of Utah M.D. from the University of Utah School of Medicine MBA from the University of Utah General Surgery Residency at Wake Forest University-Baptist Medical Center Surgical Critical Care Fellowship at Wake Forest University-Baptist Medical Center Acute Care Surgery Fellowship at Wake Forest University-Baptist Medical Center Dr. Enniss' clinical and research expertise centers on Trauma Surgery, Surgical Critical Care, Emergency General Surgery, and Acute Care Surgery. His work focuses on improving trauma systems, including trauma triage, tourniquet use, management of traumatic brain injury in geriatric patients, and the development of clinical guidelines through national organizations. His research bridges clinical practice with system-level improvements in acute care delivery. Analysis of his recent publications reveals a dominant focus on multi-institutional trauma research, particularly in trauma triage protocols, extremity trauma management, geriatric trauma assessment, and hepatobiliary emergencies. Key contributions include validation of the Trauma-Specific Frailty Index and refinement of acute cholecystitis grading systems through AAST collaborations, demonstrating his leadership in evidence-based guideline development. Professional recognition includes: Fellow of the American College of Surgeons (FACS) Dr. Enniss actively shapes national trauma standards through committee service in the American Association for the Surgery of Trauma (AAST) and Eastern Association for the Surgery of Trauma (EAST), where he leads clinical guideline development and multi-institutional research initiatives. His administrative leadership as Trauma Medical Director encompasses oversight of research protocols, educational curriculum development for trainees, and implementation of quality improvement programs within the Level 1 Trauma Center. He directs the University of Utah's Acute Care Surgery Service, integrating trauma, emergency surgery, and critical care teams into a cohesive system that handles over 3,000 annual trauma activations. His operational leadership has established protocols for prehospital care coordination, geriatric trauma management, and interfacility transfers that serve as regional benchmarks.

• Machine Learning
• Medical Imaging
• Computational Modelling
• +۳ مورد دیگر

Martin Lillholm is a Professor at the Department of Computer Science , University of Copenhagen, specializing in Image Analysis, Computational Modelling, and Geometry . His research focuses on leveraging machine learning and deep learning for medical imaging , particularly in breast cancer risk stratification and COVID-19 adverse outcome prediction . He has co-authored numerous high-impact journal articles in Radiology , Scientific Reports , and other venues, often collaborating with clinical researchers. Research Trends & Fields Lillholm’s work bridges computer science and healthcare , with recent publications emphasizing: AI-driven mammography screening for early breast cancer detection Texture analysis in medical images to enhance risk prediction Domain adaptation for robust cross-vendor imaging systems Health registry analysis using machine learning for recurrent cancer identification Pandemic risk modeling for COVID-19 outcomes Collaborations & Impact He collaborates across disciplines, including with Department of Clinical Medicine researchers and international partners . His studies have been widely cited, with significant visibility via Mendeley , X , and news outlets . While no formal awards are listed, his research has driven clinical protocol innovations and policy discussions.

Norbert Maggiمشاهده پروفایل

استاد

• Computer Science
• Bioengineering
• Pharmacy
• +۷ مورد دیگر

Norbert Maggi is a Contract Professor affiliated with the University of Genoa, Italy. He contributes to teaching in multiple departments, including the Department of Pharmacy (DIFAR), Department of Experimental Medicine (DIMES), and the Department of Computer Science, Bioengineering, Robotics, and Systems Engineering (DIBRIS). His academic appointments span diverse fields such as Computer Engineering, Psychological Sciences, Pharmacy, and Biotechnology. His research focuses on metabolite profiling for plant characterization sustainable agrochemical applications bioactivity studies against plant pathogens health informatics initiatives interdisciplinary collaborations between Spain and Italy . Recent publications highlight his work on Ligurian aromatic plant ecotypes, garlic bioactivity, and the FAIR4Health to 1+MG Initiative transition. These studies employ techniques like NMR spectroscopy and targeted metabolomics to advance agricultural and health data research.

Douglas Manuelمشاهده پروفایل

استاد

• Public Health Policy
• Epidemiology
• Population Health
• +۴ مورد دیگر

Douglas Manuel is a Distinguished University Professor at the Faculty of Medicine, University of Ottawa, with joint appointments in the C.T. Lamont Primary Health Care Research Centre (Family Medicine) and the School of Epidemiology and Public Health. His research focuses on public health systems, primary care effectiveness, and health equity, examining both real-world impacts of interventions and predictive modeling of community health outcomes. Education includes: Fellow Royal College of Physicians and Surgeons of Canada, Public Health (University of Toronto, 1998) MSc in Epidemiology (University of Toronto, 1997) Medical Doctor (Dalhousie University, 1988) His research integrates epidemiology, health policy, and population health to address preventable health determinants. Key interests include: Public health policy evaluation and health system effectiveness Preventive care strategies for immunization and healthy living Health equity and community health improvement Predictive modeling of Canadian healthcare utilization Recent publications (2022-2025) demonstrate strong focus on: Pandemic surveillance methodologies (wastewater genomics, built environment testing) Health policy impacts (cannabis legislation, sugary drink taxation) Chronic disease management and end-of-life care patterns Machine learning applications in diagnostics and risk prediction Current supervision includes PhD/Master's student Mary Scott. Research infrastructure includes leadership of: Population health modeling lab (Project Big Life initiative) Multi-institute collaborations across ICES, Ottawa Hospital Research Institute, and Statistics Canada

• Machine Learning
• Deep Learning
• Computer Vision
• +۷ مورد دیگر

Guy Hembroff serves as an Associate Professor in the College of Computing at Michigan Technological University, where he directs both the MS in Health Informatics program and the interdisciplinary PhD in Computational Science & Engineering program. His academic leadership spans computational health sciences and biomedical data science initiatives. Education: PhD in Computational Science and Engineering, Michigan Technological University MPA in Public Administration, Northern Michigan University BS in Finance and Economics, Michigan Technological University Hembroff's research focuses on human health applications of artificial intelligence, particularly in medical image analysis, natural language processing, and cybersecurity. His work bridges clinical needs with computational solutions through projects like fracture risk prediction from radiographs, lung nodule classification, and mental health intervention modeling. The Biomedical Data Science (BDS) Lab he founded integrates expertise across medicine, data science, and cybersecurity to tackle healthcare challenges. His recent publications demonstrate strong trends in applying deep learning to medical imaging (35%), natural language processing for health literacy (20%), and mental health analytics (15%), with growing emphasis on generative AI applications since 2023. Key methodological approaches include multitask learning, transformer models, and ensemble techniques tailored for healthcare data. Doctoral Advising: Harikrishnan C. (Medical Image Segmentation using AI) Chethana Kadirimangalam (Mental Health Intervention Modeling) Abel Reyes (Medical Image Segmentation and Computer Vision) Tim Van Wagner (Blockchain for Patient Data Auditing) Hembroff leads multiple externally funded research initiatives including the Tick-Talk geographical tick disease monitoring system (MI-SAPPHIRE grant), FHIR-enabled health information exchanges, and mental health intervention optimization models. His BDS Lab maintains active collaborations with Henry Ford Hospital and nonprofit healthcare networks for real-world implementation of health informatics solutions. The Biomedical Data Science Lab operates as a multidisciplinary hub combining clinical expertise with computational innovation. Current projects span physical and mental health domains, with particular focus on disease progression modeling, clinical decision support systems, and secure health data architectures. The lab's work directly informs both graduate curriculum development and healthcare industry partnerships.

Jenna Khanمشاهده پروفایل

استادیار

• Transfusion Medicine
• Blood Banking
• Medical Informatics
• +۲ مورد دیگر

Jenna Khan, M.D., serves as Assistant Professor of Pathology and Medical Director of the Blood Bank at the University of Virginia School of Medicine. Her clinical expertise centers on Blood Banking and Transfusion Medicine within the Department of Pathology at UVA Health. Her academic training includes: Medical Degree from University of Maryland School of Medicine (2006-2010) Clinical Pathology Residency at University of Washington Medical Center (2015-2018) Transfusion Medicine Fellowship at Dartmouth-Hitchcock Medical Center (2019-2020) Dr. Khan's research program focuses on optimizing blood utilization through informatics-driven solutions to enhance transfusion safety and efficiency. Her work addresses critical challenges in blood product management, including reduction of unnecessary transfusions, implementation of evidence-based protocols, and mitigation of transfusion-related complications. She investigates how data analytics can improve clinical decision-making in transfusion medicine while maintaining patient safety standards. Analysis of her 15 most recent publications (2016-2022) reveals consistent contributions to evidence-based transfusion practices, with emphasis on pediatric trauma transfusion, septic reaction protocols, national blood shortage management, and health equity in transfusion support. Her work demonstrates how operational interventions like passive order auditing directly impact blood conservation during critical shortages. As Medical Director of the Blood Bank, Dr. Khan leads clinical operations ensuring safe blood product provision while integrating research findings into practice. Her leadership spans quality improvement initiatives, regulatory compliance, and implementation of novel informatics systems to modernize blood bank workflows across the academic medical center.