جست‌وجوی استاد و پژوهشگر

Ben Barryمشاهده پروفایل

مدرس ارشد

• Digital Health
• Interprofessional Education
• Workforce Development
• +۸ مورد دیگر

Dr Ben Barry is an Honorary Senior Lecturer at the School of Nursing, Midwifery and Social Work within the University of Queensland , where he focuses on health professional education in areas like digital health , interprofessional education , and exercise physiology . He is also affiliated with the Queensland Digital Health Centre and Wesley Mission Queensland . Education : Bachelor of Science Bachelor (Honours) of Science (Advanced) Doctor of Philosophy Masters (Coursework) of Physiotherapy Studies His research spans digital health , interprofessional education , and exercise physiology , with a focus on aging, chronic fatigue, pain management, and medical curriculum innovation. He has developed tools like the CBL on FHIR platform for health professional training and explored interventions for chronic fatigue syndrome and Parkinson’s disease. Recent publications highlight his work in digital health literacy , interprofessional education , and exercise-induced hypoalgesia . His teaching innovations include electronic medical record integration, clinical placement enhancements, and online learning frameworks. Scientific Awards : Several teaching awards Dr Barry has supervised postgraduate research and secured external funding for projects on chronic pain , cancer survivorship , and medical education . He leads initiatives like Supervised Exercise Programs for medical student well-being.

Leah Marksمشاهده پروفایل

مدرس ارشد

• Medical Genetics
• Genomics
• E-learning
• +۴ مورد دیگر

Dr. Leah Marks is a Senior Lecturer in Medical Genetics at the University of Glasgow 's School of Medicine, Dentistry & Nursing. She serves as Programme Director for the MSc Genetic and Genomic Counselling and contributes extensively to both postgraduate and undergraduate medical education through innovative teaching methods. Key roles include MBChB Deputy Course Coordinator Lead academic for Glasgow's first MOOC: Cancer in the 21st Century Senior Fellowship in Higher Education (2016) Her research focuses on educational innovation in genetics, with particular emphasis on: MOOC pedagogy and student-created content Peer assessment effectiveness Digital literacy in healthcare education International student support systems Technology-enhanced learning environments Recent publications analyze: Virtual reality applications in microbiology teaching Digital literacy frameworks Online induction programs for medical students Feedback mechanisms in PGT education Scientific recognition includes: Best Postgraduate Teaching Team (2014) Enhancing Student Learning Award (2017) She also: Mentors staff through Glasgow's RET process Collaborates with College of Social Sciences Conducts science communication workshops Participates in international educational partnerships

Caitlin Dreisbachمشاهده پروفایل

استادیار

• Women's Health
• Pregnancy and Obstetrics
• Data Science in Nursing
• +۳ مورد دیگر

Caitlin Dreisbach, PhD, RN is an Assistant Professor at the University of Rochester School of Nursing with a dual affiliation at the Goergen Institute for Data Science. She maintains active clinical practice on the high-risk obstetrics unit at Strong Memorial Hospital while leading interdisciplinary research at the intersection of nursing science and data analytics. Her educational background includes a PhD in Nursing from the University of Virginia (2020), BSN from Johns Hopkins University (2013), and undergraduate studies at Cornell University. Her research interests span women's lifelong health trajectories , quantitative clinical assessment during pregnancy , microbiome dynamics , and social determinants of health in reproductive outcomes. She employs advanced data science techniques including natural language processing, machine learning, and microbiome analysis to address complex questions in maternal-child health. Analysis of her 15 most recent publications reveals a strong focus on leveraging large-scale datasets (particularly the All of Us Research Program) to investigate pregnancy outcomes, symptom science, and chronic disease patterns. Key methodological themes include predictive modeling of birth outcomes, extraction of clinical data from unstructured notes, and analysis of microbiome-diet interactions during gestation. Scientific awards and recognition include: Josephine Craytor Nurse Faculty Award (2024) Most Promising New Investigator (2023) Phyllis J. Verhonick Dissertation Award (2020) Wood Family Award for Data Science (2018) The Raven Society membership (2017) Dr. Dreisbach serves as Principal Investigator for multiple funded projects including an NIH/NINR grant on neural network approaches to fetal weight estimation (2022-2025) and a Heilbrunn Foundation grant examining surgical weight management before pregnancy (2024-2026). Her lab (DreisbachLab) develops open-source tools for reproductive health research, including the GAP_Projection repository for birthweight prediction algorithms. She also contributes as a data science consultant on projects like the Significance of Symptom Onset-To-Angiography Time study at CTSI. Her work bridges clinical practice, data science innovation, and nursing education through initiatives advancing data competencies for PhD students and exploring implications of generative AI in nursing science.

• Prostate Cancer
• Translational Research
• Biomarkers
• +۴ مورد دیگر

Anders Bjartell is a distinguished Professor and Principal Investigator at Lund University, holding multiple leadership positions including Manager of Urological Cancer Research in Malmö, Professor in the eSSENCE: The e-Science Collaboration, and Professor in EpiHealth: Epidemiology for Health. He serves as a Principal Investigator at the Lund University Cancer Centre (LUCC), where he directs significant research initiatives in prostate cancer. Dr. Bjartell's research focuses on translational prostate cancer studies, with particular emphasis on identifying molecular targets for therapies in chemo- and hormone-resistant prostate cancer. His work spans in vitro studies, animal models, biomarker development and validation in tissue, blood and urine (including circulating tumor cells), biobanking, and clinical studies on imaging biomarkers and robotic surgery. His fingerprint analysis reveals strong activity in Prostate Cancer (100%), Patient care (61%), Prostatectomy (29%), Therapeutic Procedures (23%), and Man-related studies (23%), with significant contributions to Prostate-Specific Antigen research (16%), Robot-Assisted Prostatectomy (12%), and Biological Markers (11%). The recent publication trends in Dr. Bjartell's work demonstrate a strategic shift toward integrating artificial intelligence with traditional prostate cancer research, particularly in digital pathology, imaging analysis, and risk stratification. His involvement in major international collaborations like the PIONEER big data platform shows commitment to leveraging real-world evidence for advancing prostate cancer care. The research spans from basic molecular investigations to large-scale clinical implementation studies, reflecting a comprehensive translational approach. EAU Frans Debruyne Life Time Achievement Award (2025) Referenced in multiple patents and Wikipedia pages Extensive scholarly impact with over 370 research outputs Dr. Bjartell has supervised 16 research projects and students, demonstrating strong mentorship capacity. His current projects include 'Biomarkers and targeted therapies for advanced prostate cancer' (2024-2028), 'Digital Optimisation of Gleason Scoring (DOGS)', and development of new imaging biomarkers for PET/CT. He actively organizes academic events including the LUCC - Malmö Cancer Seminars (March 2024), LUCC - UroCAN conferences, and AI-focused cancer research seminars, establishing himself as a central figure in the prostate cancer research community. His laboratory infrastructure supports comprehensive prostate cancer research from molecular analysis through clinical implementation, with particular strengths in biomarker validation, digital pathology, and integration of AI technologies into prostate cancer diagnostics and management.

Michael A. Grassoمشاهده پروفایل

دانشیار بالینی

• Clinical Informatics
• Biomedical Informatics
• Consumer Health Informatics
• +۸ مورد دیگر

Michael A. Grasso, MD, PhD, is a Clinical Associate Professor in the Department of Medicine and Emergency Medicine at the University of Maryland School of Medicine. He practices Emergency Medicine and serves as Director of the Clinical Informatics Group and Program Director for Clinical Informatics graduate programs at the University of Maryland Baltimore. His education includes: BS in Microbiology, University of Maryland (1983) MS in Computer Science, American University (1986) PhD in Computer Science, University of Maryland Baltimore County (1997) MD, George Washington University (2005) Internal Medicine Residency, University of Maryland (2008) Clinical Informatics Fellowship, University of Maryland (2013) Dr. Grasso's research focuses on knowledge representation and reasoning for large-scale clinical data systems. Key areas include: Big data analytics for chronic disease prediction (diabetes, rheumatoid arthritis, opioid misuse) Patient safety and quality improvement in emergency medicine Impact of online consumer health information on clinical decision-making His 13 recent publications (2011-2022) reveal strong trends in Veterans Health Administration data analysis, opioid prescribing patterns, and machine learning applications. Work emphasizes clinical decision support, predictive modeling for mortality/disease, and ICD-10 coding impacts in emergency settings. Scientific honors include: Fellow of the American College of Physicians (FACP) Fellow of the American Medical Informatics Association (FAMIA) Three medical/computing honor societies As Program Director for Clinical Informatics graduate programs, he mentors students in this emerging field. He has secured over $2,000,000 in grants from NIH, FDA, NIST, NASA, and DoD for: Knowledge representation with big clinical repositories Emergency department quality/safety initiatives Consumer health information impact studies He leads the University of Maryland Clinical Informatics Group, leveraging Veterans Health Administration data (35M patients) and University of Maryland Medical System's EPIC repository (14 hospitals) to develop semantic-enhanced machine learning for disease prediction and treatment efficacy.

• Patient Engagement in Healthcare
• Science and Technology Studies (STS)
• Medical Sociology
• +۳ مورد دیگر

Claudia Egher is a Researcher at the Copernicus Institute of Sustainable Development , part of the Faculty of Geosciences , Utrecht University, Netherlands. Her work synthesizes science and technology studies (STS) , medical sociology , innovation studies , and philosophy to analyze the social , cultural , and ethical dimensions of digital healthcare innovations and patient engagement in pharmaceutical development. She focuses on participatory practices, affective labor in expertise, and value reconfiguration in research infrastructures for rare cancers . Primary Affiliation: Utrecht University Sub-Units: Faculty of Geosciences, Copernicus Institute, Innovation Studies Her research explores: Patient engagement in drug development through dialogical problematization and standardization Affective labor in expert practices Moral labor and value negotiation in digital health infrastructures Knowledge representation in participatory healthcare Public participation dynamics in contemporary societies Digital biocommunities for mental health support Recent publications analyze co-creation of data infrastructures for rare diseases , ethics of AI in clinical settings, and hybrid expertise in online mental health forums . She contributes to journals like Science and Technology Studies , Science as Culture , and Health Expectations .

Ali Madooeiمشاهده پروفایل

استاد آموزشی

• Computer Science Education
• Software Engineering
• Instructional Design
• +۴ مورد دیگر

Ali Madooei is a Teaching Professor in the Department of Computer Science at Johns Hopkins University, affiliated with the Whiting School of Engineering. He specializes in computer science education, software engineering, instructional design, and learning technology, with a focus on hands-on project-based learning. Department: Computer Science School: Whiting School of Engineering Academic Rank: Teaching Professor Email: madooei@jhu.edu His research interests revolve around enhancing software development education through project-based learning environments. He established the Coding, Learning, and Application-Building Lab (COLLAB) , which provides students with unstructured, self-directed software project experiences. He also leads the AI-Assisted Instruction Lab , exploring how artificial intelligence can improve educational technology. Madooei's work emphasizes modern technology stacks, employability, and flexible remote collaboration, with projects often aligning with industry standards. Additionally, he has contributed to biomedical imaging through prior research in color modeling and hyperspectral analysis for skin lesion diagnostics. Ali Madooei has received the Whiting School of Engineering Excellence in Teaching Award (2024) , highlighting his commitment to pedagogical innovation in computer science education. As an educator, Madooei promotes independent learning, mentorship, and leadership development in his labs. His labs support a dozen students each term with academic credit and practical experience, offering paid, volunteer, and self-directed project opportunities. Projects are structured around sprint cycles and remote collaboration, with students encouraged to propose ideas or join existing initiatives. He has previously taught at the University of British Columbia, Simon Fraser University, and Kwantlen Polytechnic University, bringing diverse institutional experience to his current role.

Gavin Brownمشاهده پروفایل

استاد

• Machine Learning
• Statistics
• Information Theory
• +۳ مورد دیگر

Professor Gavin Brown is a faculty member in the Department of Computer Science, focusing on theoretical and methodological foundations of Machine Learning. His work bridges statistics, information theory, and information geometry to develop robust ML methods for reproducibility and hypothesis testing in non-standard scenarios. His research has been applied to predictive policing, clinical trials, and energy-efficient ML algorithms for plastic electronics. Key publications include A Unified Theory of Diversity in Ensemble Learning (JMLR, 2023) and On the Stability of Feature Selection in the Presence of Feature Correlations (ECML, 2019), supported by EPSRC funding. Recent work (2024) investigates the distinction between bias-variance and approximation-estimation error, alongside hardware-efficient ML solutions for FPGAs and flexible electronics. His book How to Get Your PhD (OUP, 2021) offers practical and emotional guidance for doctoral students, co-authored with 12 experts on career planning, diversity in science, and risk management in research. Developed theories for ensemble diversity (2020-2023) Created stability metrics for feature selection (2016-2022) Explored ML applications in healthcare and public safety Current activities include a research sabbatical (2021-2022) working on novel ML frameworks. He leads a research group at the Kilburn Building (Office G11) and contributes to pedagogy discussions, particularly around PhD training and conceptual understanding in deep learning.

Martha Pitmanمشاهده پروفایل

استاد

• Cytopathology
• Pancreaticobiliary Cytology
• Fine Needle Aspiration (FNA) Biopsy
• +۳ مورد دیگر

Martha Pitman, MD is a Professor of Pathology at Harvard Medical School and a Pathologist at Massachusetts General Hospital . As Director of the Cytopathology Laboratory and Fine Needle Aspiration Biopsy Service , she leads a team of eight cytopathologists and oversees clinical, educational, and research activities. Research Interests: Her work focuses on pancreaticobiliary cytopathology , including the clinical utility of fine needle aspiration (FNA) biopsy , preoperative diagnosis of pancreatic cysts , and development of international reporting standards. She is a principal author of the Papanicolaou Society System for Reporting Pancreaticobiliary Cytology and co-author of the WHO Classification of Tumours of the Digestive System . Publications highlight her leadership in standardizing diagnostic criteria for pancreatic and biliary tract diseases, with a focus on mucinous cysts, intraductal papillary neoplasms, and molecular assessment of brushing specimens. She has contributed to consensus guidelines and systematic reviews on pancreatic pathology. Scientific Awards: President-Elect, American Society of Cytopathology Labs & Teams: At Mass General, she directs a Cytopathology Laboratory staffed by cytopathologists, cytotechnologists, and medical technologists. The lab is accredited for cytopathology fellowships and emphasizes quality patient care, education, and translational research in cytological specimen procurement.

Răzvan Udroiduمشاهده پروفایل

دانشیار

• Additive manufacturing
• 3D printing
• Composite materials
• +۱ مورد دیگر

Răzvan UDROIU is an Associate Professor in the Department of Manufacturing Engineering at the University of Transilvania of Brașov, Faculty of Technological Engineering and Industrial Management. His research focuses on additive manufacturing, composite materials, and aerospace engineering applications. Academic affiliation: University of Transilvania of Brașov Department: Manufacturing Engineering Faculty: Technological Engineering and Industrial Management His work primarily investigates additive manufacturing technologies , particularly 3D printing and Polyjet , with applications in aerospace engineering and composite material fabrication. Research themes include quality control in polymer jetting, surface performance analysis, and mold manufacturing optimization. Publication trends show consistent contributions to additive manufacturing since 2011, with recent Q1 journal articles in Polymers and Materials focusing on aerospace applications and composite manufacturing. Key methodologies involve statistical process capability analysis, tooling optimization, and CFRP production.

Caroline Brallمشاهده پروفایل

دانشیار

• Bioethics
• Public Health Ethics
• Health Policy
• +۵ مورد دیگر

PD Dr. Caroline Brall is an academic researcher and manager at the Multidisciplinary Center for Infectious Diseases (MCID) at the University of Bern. Her work bridges bioethics , public health policy , and digital health governance , focusing on trust dynamics , data sharing , and ethical decision-making during health crises. Academic rank: Associate Professor Affiliation: University of Bern (MCID) Key roles: Research ethics, pandemic policy, biobanking governance Research interests span three domains: Ethical frameworks for public health emergencies, including quarantine ethics and resource allocation during pandemics; Digital health governance , examining data anonymity , biobank transparency , and health app ethics ; Clinical ethics support , analyzing how healthcare systems maintain ethical standards under strain. Recent publications (2021-2024) show evolving priorities from foundational biobanking ethics to nuanced analyses of pandemic policy and digital health integration , with keywords across public health , genomics , and health informatics .

Søren Knudsenمشاهده پروفایل

استادیار

• Information Visualization
• Human-Computer Interaction
• Data Visualization
• +۳ مورد دیگر

Søren Knudsen is an Assistant Professor at the Digital Design Department, IT University of Copenhagen and holds a Marie Curie Fellowship for postdoctoral work at the University of Copenhagen. He serves as Academic Director of the Human Data Interaction Lab. Positions: Assistant Professor, Marie Curie Postdoctoral Scholar Affiliations: IT University of Copenhagen, University of Copenhagen Key Roles: Academic Director, Human Data Interaction Lab His research centers on information visualization and human-computer interaction , particularly in face-to-face and online contexts. He explores how large-area displays and social media can enhance data comprehension and collaborative discussion. Notable work includes surveys on interactive visualization techniques for large displays, frameworks for data visualization education , and EMR-based algorithms for healthcare performance evaluation. His publications span journals like IEEE Transactions on Visualization and Computer Graphics and PLOS ONE . Awards and honors: Marie Curie Fellowship He collaborates across disciplines, with ties to healthcare analytics, educational technology, and computer science departments. His recent studies address challenges in visualization design handoff , proxemics , and ubiquitous data interaction .

• Building information modelling and management
• Cyberphysical systems and internet of things
• Geospatial information systems and geospatial data modelling
• +۷ مورد دیگر

Lecturer in Digital Construction Management at the University College London , where he also serves as Deputy Departmental Graduate Tutor. Previously held roles at the University of Cambridge (Research Associate) and Politecnico di Milano (Research Fellow). Focuses on Digital Twins , Building Information Modeling (BIM) , and Asset Management in the built environment. PhD in Architecture, Built Environment and Construction Engineering (Politecnico di Milano, 2020) MSc in Management of the Built Environment (Politecnico di Milano, 2015) BSc in Urban Planning (Politecnico di Milano, 2013) Research spans digital twin-based information management , process innovation , and decision-support tools for built asset sustainability. Combines BIM , GIS , and IoT to enhance facility operations across healthcare, education, and urban sectors. Funded by the Royal Academy of Engineering (2025) and EU Horizon (2022). Teaching includes modules on Digital Design , Data Delivery , and Digital Innovation for UCL postgraduate students. Professional certifications include Fellow of the Higher Education Academy (FHEA) . Collaborates with institutions like the Centre for Digital Built Britain and Politecnico di Milano , focusing on SDG 9 , 11 , and 13 for sustainable infrastructure and climate action.

• Clinical Informatics
• Artificial Intelligence in Healthcare
• Machine Learning Applications
• +۵ مورد دیگر

Dr. Thomas Durant is an Associate Professor of Laboratory Medicine at Yale School of Medicine with a secondary appointment in Biomedical Informatics & Data Science. He serves as Medical Director of Chemical Pathology and Laboratory Informatics at Yale-New Haven Hospital and Associate Director for the ACGME Chemical Pathology Fellowship. His dual expertise bridges clinical laboratory practice with cutting-edge informatics research. Dr. Durant's educational background includes: MD from University of Connecticut, School of Medicine (2015) MA in Physical Therapy from Quinnipiac University BA in Health Sciences from Quinnipiac University (2008) Winchester Clinical Microbiology Fellowship at Yale-New Haven Hospital (2019) Residency and Chief Residency at Yale-New Haven Hospital (2018) Board certified in Clinical Pathology (2018), Medical Microbiology (2019), and Clinical Informatics (2022), Dr. Durant's research focuses on practical applications of data science in laboratory medicine. His work centers on clinical informatics, quality care initiatives, and artificial intelligence applications including machine learning for automated image classification, quantum computing in healthcare, and laboratory data analytics. He investigates stream processing of interface data for sample identification and develops innovative data management technologies to improve laboratory operations and patient care. Analysis of Dr. Durant's publication record reveals a strong progression from traditional laboratory medicine into advanced computational methods. His recent work demonstrates expertise in ensemble learning for detecting IV fluid contamination, quantum computing applications, AI model verification protocols, and biomarker analysis for acute kidney injury prediction. The research spans multiple disciplines including clinical chemistry, informatics, and data science, addressing critical challenges in diagnostic medicine. Dr. Durant maintains extensive collaborations with Yale researchers including Wade Schulz (14 publications), Joe El-Khoury (10 publications), Harlan Krumholz (5 publications), and Richard Torres (4 publications). These partnerships support research on laboratory informatics, AI applications, and quality improvement initiatives that enhance diagnostic accuracy and healthcare delivery. As Medical Director of Laboratory IT Services, Dr. Durant oversees the technological infrastructure supporting laboratory operations at Yale-New Haven Hospital. His leadership in the Chemical Pathology Fellowship program trains future specialists, while his research continues to push the boundaries of how data science transforms diagnostic medicine.

Denis Newman-Griffisمشاهده پروفایل

مدرس ارشد

• Equitable AI
• Health Informatics
• Natural Language Processing (NLP)
• +۴ مورد دیگر

Dr. Denis Newman-Griffis is a Senior Lecturer & Theme Lead in AI for Health at the University of Sheffield's School of Computer Science . They completed a PhD in Computer Science and Engineering at the University of Pittsburgh, with prior roles at the NIH Clinical Center and the Information School. Their research integrates AI, health informatics, and critical disability studies to address: Equitable AI and responsible machine learning practices Disability-centered analysis of AI systems Health NLP for clinical and policy applications Recent publications focus on medical concept normalization, disability representation in ontologies, and ethical frameworks for AI in research funding. Newman-Griffis co-leads the UK Young Academy and actively mentors students through: Supervision of PhD candidates Jun Wang and Yi Jiang Teaching coordination for BSc/MSc Data Science programs Development of pedagogical tools like INF111 Practical Programming Scientific accolades include the AMIA Doctoral Dissertation Award . Their grants portfolio includes: £77,000 GRAIL project (Research on Research Institute) £286,887 FRAIM project (AHRC/BRAID) £60,607 British Academy Fellowship