Sharon C. Kiang, MD, is an Associate Professor and Vice Chair of Research in the Department of Surgery, Vascular Division at Loma Linda University's School of Medicine. She specializes in vascular surgery with a focus on endovascular interventions, peripheral vascular disease, and the application of artificial intelligence (AI) in clinical decision-making. Her research spans traumatic vascular injuries, aortic aneurysms, and outcomes analysis in chronic limb-threatening ischemia (CLI). Dr. Kiang holds an MD from Vanderbilt University and a BS from the University of Maryland. Her clinical and research activities are supported by grants from LLU departments, including studies on AI's role in vascular care, radiation safety in fluoroscopy-guided procedures, and long-term outcomes of vascular injuries. Her research outputs emphasize translational science, with publications in Annals of Vascular Surgery , Circulation , and Journal of Vascular and Interventional Radiology . Key areas include validating ICD-10 codes for CLI, analyzing AI biases in vascular imaging, and investigating technical failures in endovascular procedures. She has led or collaborated on over 75 peer-reviewed articles since 2008. Dr. Kiang’s academic contributions extend to mentoring students through her roles in residency and fellowship training programs. Her work integrates clinical practice with advancing technologies to improve patient care outcomes.
Professor Saskia E. Drösler holds a faculty position at Niederrhein University of Applied Sciences in the Department of Health Care Management within the School of Health Sciences . Her academic expertise spans health services research, medical informatics, patient safety, and quality assurance with a focus on administrative data analysis for healthcare policy. Her research, visible through publications from 2019 to 2011, explores: ICD-11/10 coding frameworks for safety events Small-area health disparities in diabetes care International healthcare quality comparisons Administrative data limitations and improvements Standardization of diagnosis-timing in hospital records Key collaborations include institutions such as University of Calgary, UC Davis , and participation in WHO ICD-11 advisory groups . She has served in multiple university governance roles at Hochschule Niederrhein from 2004 to 2023.
Erica Koegler serves as an Assistant Professor in the School of Social Work at the University of Missouri-St. Louis, where she teaches Master's level research methods courses and advises MSW students. Her academic journey includes a PhD in Public Health from Johns Hopkins Bloomberg School of Public Health (2016), a Master of Social Work from the University of Chicago (2010), and a BA in Psychology from Eastern Illinois University (2004). Her educational foundation is reflected in her research profile: PhD, Public Health, Johns Hopkins Bloomberg School of Public Health (2011-2016) MA, Social Work, University of Chicago (2008-2010) BA, Psychology, Eastern Illinois University (2000-2004) Dr. Koegler's research centers on human trafficking in the American Midwest and global health issues affecting conflict-affected populations, with expertise in mixed methods and community-based participatory research. Fluent in Swahili, she has conducted fieldwork in the Democratic Republic of Congo and South Africa, examining intersections of mental health, sexual risk, and substance use among vulnerable populations including refugees and transgender individuals. Her 24+ publications reveal consistent methodological rigor and thematic focus on trafficking victimization patterns, mental health correlates, and service gaps. Recent work employs latent class analysis for victimization typologies and examines ICD coding practices in emergency departments, demonstrating both epidemiological sophistication and practical clinical applications. Her research consistently bridges global health perspectives with domestic Midwest contexts. Dr. Koegler currently leads two human trafficking research initiatives in the Midwest while mentoring graduate students. Her collaborative work with service providers informs trauma-informed treatment approaches for survivors, particularly regarding substance use interventions. She actively engages with community stakeholders through participatory research frameworks to address systemic gaps in trafficking identification and response systems.
Asai Asaithambi is a Professor and Graduate Program Director in the School of Computing at the University of North Florida (UNF), where he also served as School Director from 2011-2015. With 37+ years of academic experience, he previously held leadership roles including Professor/Chair at the University of South Dakota (2004-2011), Associate Professor/Chair at Saint Louis University (1997-2004), and Assistant/Associate Professor positions at Lincoln University and Mississippi State University. His academic credentials include: PhD in Computer Science, University of Wisconsin-Madison (1985) MS in Computer Science, Indian Institute of Technology-Madras (1980) Bachelor of Technology in Electrical Engineering, Indian Institute of Technology-Madras (1977) Professor Asaithambi's research spans artificial intelligence, computational science, and high-performance computing, with significant contributions to quantum computing algorithms, biomedical image analysis, and numerical methods for differential equations. His work demonstrates consistent focus on applying computational techniques to real-world problems in healthcare, cybersecurity, and engineering, while maintaining strong commitment to broadening participation of underrepresented groups in computing. Analysis of his 15 most recent publications (2019-2025) reveals dominant themes in medical imaging AI (lung X-ray and brain MRI analysis), bioinformatics algorithms for genome rearrangement, quantum computing security implications, and multi-robot coordination systems. His methodology consistently combines theoretical algorithm development with practical implementation, often leveraging advanced optimization techniques and parallel computing approaches. Key research projects include: Getting American Indians to Information Technology (GAIN-IT) as Co-PI (2008-2013) A Computational Intelligence to Gene Structure Prediction as PI (2007-2008) South Dakota Biomedical Research Infrastructure Network as Co-PI (2001-2012) Throughout his career, Professor Asaithambi has directed numerous doctoral dissertations and Master's theses while teaching diverse courses from introductory programming to quantum computing. His teaching philosophy emphasizes critical thinking development for both traditional and non-traditional student populations, with particular attention to mathematical preparation challenges in computational courses.
Hyacinth I. Hyacinth is a Professor at the University of Cincinnati, affiliated with the Department of Neurology. His research focuses on the biological basis of disparities in stroke, cognitive impairment, and dementia, particularly examining the role of sickle cell mutations and genetic variants in cerebral macro/microvascular pathologies among individuals of African ancestry. Education: PhD (Walden University), Postdoctoral training (Medical University of South Carolina, Emory University, Morehouse School of Medicine), MPH (University of Liverpool), MD (University of Jos) His work integrates genetic epidemiology, neurovascular biology, and hematology to define mechanisms linking genetic variation to differential disease risk. Recent studies include neuroinflammation in sickle cell mice, perivascular space quantification in SCD patients, and genomic risk scores for stroke prediction. Scientific contributions include peer-reviewed publications in JAMA Neurology , Nature , Stroke , and Experimental Biology and Medicine . He holds a FAHA fellowship from the American Heart Association.
Matthew J O'Brien, MD, is an Associate Professor in the Department of Medicine at the Feinberg School of Medicine, Northwestern University, with joint appointments in Preventive Medicine. His research focuses on eliminating health disparities in U.S. Latino populations through community-engaged interventions using culturally-competent community health workers. His educational background includes: MD from Brown University (2004) Internal Medicine Residency at Hospital of the University of Pennsylvania (2007) Robert Wood Johnson Clinical Scholars Program Fellowship at University of Pennsylvania (2010) Dr. O'Brien specializes in health disparities research, particularly developing community health worker (promotora) programs for diabetes, cardiovascular disease, and cancer prevention in Latino communities. His work combines qualitative and epidemiologic methods to identify intervention targets and advocates for integrating community-based resources with traditional healthcare systems. Key research areas include social determinants of health, health policy, and primary care innovation. Recent publications (2024-2025) demonstrate consistent focus on diabetes prevention in Hispanic populations, technology access disparities, and social determinants of health. His work emphasizes community partnership models and addresses systemic barriers to healthcare equity. Scientific recognition includes: Community Engagement Award from Feinberg School of Medicine (2022) Dr. O'Brien maintains strong community partnerships through affiliations with the Center for Diabetes and Metabolism, Institute for Public Health and Medicine (IPHAM), Northwestern University Clinical and Translational Sciences Institute (NUCATS), and Ryan Family Center for Global Primary Care. His research model prioritizes community-driven priorities and equitable collaboration with community leaders.
Brian L. Strom is a Professor of Epidemiology at the University of Pennsylvania’s Perelman School of Medicine, affiliated with the Department of Biostatistics, Epidemiology, and Informatics (DBEI). His academic career spans over four decades, with a focus on pharmacoepidemiology, drug safety, and public health outcomes. Strom earned his M.D. from Johns Hopkins University (1975), M.P.H. from UC Berkeley (1980), and B.S. from Yale University (1971). His research emphasizes drug utilization, safety, and efficacy, particularly in chronic disease populations such as diabetes, rheumatoid arthritis, and pediatric conditions. Key areas include vaccine effectiveness, antibiotic exposure impacts, and pandemic health effects. Collaborators include prominent figures like James D. Lewis (Professor of Medicine and Epidemiology) and Meenakshi Bewtra (Associate Professor of Medicine and Epidemiology). Strom’s work bridges clinical and population health, addressing real-world drug outcomes and healthcare policy. Recent studies explore opioid-benzodiazepine mortality risks in veterans and antibiotic effects on pediatric chronic diseases. He has contributed to methodological advancements in algorithm validation for disease identification and public health surveillance. Educational Background: B.S., Yale University, 1971 M.D., Johns Hopkins University, 1975 M.P.H., University of California, Berkeley, 1980 Research Collaborations: James D. Lewis (Medicine & Epidemiology) Meenakshi Bewtra (Medicine & Epidemiology) Gregory Tasian (Urology & Epidemiology) Methodological Expertise: Pharmacoepidemiological study designs Health outcomes research Algorithm development for disease detection His publications span high-impact journals like Chest , Contraception , and Diabetes Care , reflecting interdisciplinary contributions to drug safety and public health. Strom’s work has informed FDA guidelines and healthcare policy, emphasizing evidence-based practices in clinical and population settings.
Hercules Dalianis is a Professor at the Department of Computer and Systems Sciences, Stockholm University. His research focuses on Natural Language Processing, particularly in clinical text mining for Swedish language data. He leads the Natural Language Processing Research Group and serves as director of the Health Bank - Swedish Health Record Research Bank infrastructure. MSc in Electrical Engineering (1984), KTH PhD in Technology (1996), KTH Professor of Computer and Systems Science (2011), Stockholm University His research addresses privacy-preserving NLP for clinical text analysis, including automated de-identification , domain adaptation of BERT models , and clinical entity recognition . Current projects like DataLEASH and Privacy-Preserving Techniques explore machine learning solutions that balance data utility with patient confidentiality. Key publication trends show emphasis on Swedish clinical text processing , ICD-10 coding automation , and privacy-aware language modeling . Collaborations span Karolinska University Hospital, Nordic healthcare institutions, and international AI research communities. He teaches courses in Internet Search Techniques and Business Intelligence (ISBI) , Natural Language Processing (NLP) , and Principles and Foundations of Artificial Intelligence (PFAI) . His work has produced the open-access textbook Clinical Text Mining: Secondary Use of Electronic Patient Records , establishing foundational frameworks for clinical NLP in low-resource languages.
Dr. Kensaku Kawamoto is a Professor and Vice Chair of Clinical Informatics at the University of Utah Department of Biomedical Informatics, and Associate Chief Medical Information Officer at University of Utah Health. He leads the ReImagine EHR initiative, developing award-winning EHR add-ons like neonatal bilirubin management and lung cancer screening tools. He chairs the Clinical Decision Support committee and co-leads the HL7 Clinical Decision Support Work Group. His research focuses on clinical decision support systems, personalized medicine, and health IT standards. Education: B.A. in Biochemical Sciences, Harvard University M.D., Ph.D. in Biomedical Engineering (focusing on informatics), Duke University M.H.S. in Clinical Research, Duke University School of Medicine Key Roles: HL7 Interoperability Standards Priorities Task Force Co-Chair Past Board Member of HL7 Fellow of American College of Medical Informatics & AMIA His research interests emphasize clinical decision support , standards development , and healthcare equity . Recent work addresses disparities in genetic testing access via chatbot platforms (BRIDGE trial) and lung cancer screening optimization. He has secured $55M+ in grants from NCI, NIDDK, AHRQ, and industry. Notable achievements include 100+ peer-reviewed articles, OpenCDS initiative leadership, and recognition as a Top 25 Healthcare Innovator (2019). Current projects include the MAINTAIN PRIME weight management trial and lung cancer screening tools integrated into EHR workflows. Dr. Kawamoto's labs focus on interoperable clinical decision support, with collaborations spanning Huntsman Cancer Institute and national standards bodies. He advocates for precision medicine enabled by scalable informatics solutions.
Matthew Iveson is a Senior Research Fellow at the Centre for Clinical Brain Sciences (University of Edinburgh) with a focus on mental health data science, cognitive ageing, and administrative data linkage. He holds a PhD in Psychology (2015) from the University of Edinburgh and Suor Orsola Benincasa University, an MSc by Research (2010), and an MA (Hons.) in Psychology (2009). Research Interests : Mental health prediction using EHRs, antidepressant response phenotyping, treatment resistance, dementia risk modeling, and socioeconomic determinants of mental health. Grants : 2024–2025: RDS Accelerator Award (PI) on 'Antidepressant exposure and resistance' 2023–2028: Wellcome Mental Health Award (Work Package 2 lead) for 'Understanding antidepressant mechanisms' 2018–2020: MRC Mental Health Pathfinder Award (Work Package 1) on intergenerational mental health patterns Scientific Awards : JSPS Post-doctoral Fellowship (2015–2016) in Kyoto, Japan. Knowledge Exchange : Advocates for NHS data utilization, develops best practices for mental health data science, and collaborates with policymakers to enhance administrative data resources.
Bruno Martins is an Associate Professor at Instituto Superior Técnico (IST) of the University of Lisbon, affiliated with the Human Language Technologies Lab at INESC-ID and the Lisbon ELLIS Unit (LUMLIS). His research focuses on information retrieval, text mining, geographical information sciences, and machine learning. He leads projects on geospatial aspects of information access and integrates NLP, ML, and GIS methodologies. Research Interests: Geographic Information Retrieval (GIR) Text Mining & Natural Language Processing (NLP) Machine Learning Applications in Geospatial Analysis Information Extraction from Historical Documents Recent Research Trends: Recent work emphasizes deep learning for geospatial tasks (e.g., population distribution modeling), multimodal systems (medical VQA, remote sensing captioning), and computational social science (political discourse analysis). His publications address challenges in geocoding, spatial disaggregation, and multilingual NLP. Advising & Projects: Supervised over 50+ students across PhD, MSc, and postdoc levels. Key projects include the EU-funded DETECT (epidemiological surveillance), MATISSE (shellfish safety forecasting), and DigCH (historical Mexican documents analysis). Active in initiatives like GeoAI and Geospatial Humanities workshops. Labs & Teams: Directs research at INESC-ID’s Human Language Technologies Lab and participates in the Lisbon ELLIS Unit. Collaborates with international teams on vision-language models, geospatial AI, and computational humanities.
Professional Overview Jan Kristian Damås is a Professor at the Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU). His research focuses on sepsis pathophysiology, infectious diseases, and translational epidemiology, with particular emphasis on leveraging genomics and machine learning for clinical prediction. Research Interests His work spans multiple domains including: Infectious Disease Mechanisms : Investigating immune responses to pathogens like scrub typhus and pneumocystis pneumonia Sepsis Outcomes : Developing predictive models for mortality and long-term morbidity using electronic health records Genetic Epidemiology : Identifying risk loci for infections through Mendelian randomization and GWAS Clinical Informatics : Optimizing diagnostic coding practices and healthcare data systems Key Contributions Recent work includes: Systematic review of machine learning approaches for bloodstream infection prediction Nationwide registry studies on sepsis trends and outcomes Discovery of canonical notch pathway dysregulation in scrub typhus patients Awards & Collaborations Collaborates extensively with clinical teams at St. Olavs Hospital and international groups. Active in translational research bridging basic immunology and clinical practice.
Generosa of Birth is a Professor in the Department of Human Resources and Organizational Behavior at ISCTE - University Institute of Lisbon. She leads the Executive Master's in Strategic People Management and Leadership , Executive Master's in Health Services Management , and Postgraduate Program in Management for Health Professionals through ISCTE Executive Education. Research Focus: Her work bridges Health Services Management and Strategic People Management , emphasizing leadership impacts, organizational transformation, and non-monetary workforce incentives. She has consulted extensively on organizational change across public, private, and social sectors. Academic Contributions: Recent publications explore pandemic-driven organizational shifts (2021-2024), AI applications in clinical coding (2024), and contextual ambidexterity in public institutions (2021). Her studies span healthcare sustainability ( Bloco Operatório Verde , 2021), lean healthcare (2018), and performance management systems (2018). Expertise: She combines theoretical rigor in organizational behavior with practical healthcare management applications, balancing broad disciplines like Public Health and Leadership with niche subfields such as ICD-10 coding AI and integrated ENT service centers.
Dr. Mohammad Nazmul Haque is an Associate Lecturer at the School of Information and Physical Sciences, University of Newcastle, Australia, where he also holds a Casual Academic position. His academic career spans both Australian and Bangladeshi institutions, with significant contributions to data analytics, evolutionary computing, and machine learning research. Dr. Haque earned his Doctor of Philosophy in Computer Science from the University of Newcastle in February 2017. Prior to this, he completed his B.Sc and M.Sc in Computer Science & Engineering from Daffodil International University (DIU), Dhaka, Bangladesh in 2006 and 2011, respectively. His academic journey includes lecturing positions at Daffodil International University (2009-2012) and Daffodil Institute of IT (2007-2009) before commencing his PhD studies. His research focuses on innovative applications of continued fractions for regression methods using memetic algorithms, with applications spanning astronomy, scientific functions, and predictions. He has extensive interdisciplinary experience in data analytics from diverse data sources including gene expression, business and consumer behavior, and images. His work bridges theoretical computer science with practical applications in health informatics, network analysis, and complex systems. Dr. Haque's publication record demonstrates a consistent focus on continued fractions, memetic algorithms, and ensemble methods across diverse domains. His recent work shows increasing application of these techniques to physical sciences, materials science, and even digital humanities, reflecting his interdisciplinary approach. The publications reveal strong collaboration with Professor Pablo Moscato and others across multiple disciplines. ACM-Solver Coding Championship (2005) University of Newcastle International Postgraduate Research Scholarship (2012) University of Newcastle Research Scholarship Central (2012) Chartered Professional Engineer (CPEng) from Engineers Australia (2025) Senior Member of IEEE (2021) ACS Certified Professional (2024) Dr. Haque has successfully supervised seven Honours/Masters students with projects ranging from computer vision applications to data mining and software engineering. He has secured research funding totaling $16,445, including a $14,945 grant from Hunter Water Corporation for data science methods to cluster consumer water consumption. His professional memberships include IEEE Senior Member, ACM Member, and Australian Computer Society certifications, reflecting his standing in the computing community. As part of the University of Newcastle's research ecosystem, Dr. Haque contributes to collaborative projects with international reach, evidenced by his publications with co-authors from Australia, United States, Canada, Malaysia, Bangladesh, UK, and South Korea. His work with the Data Science and Statistics group continues to explore innovative mathematical representations for complex data analysis problems.
Juliana Schmidt is a Researcher at the Faculty of Health Sciences , Working Group 5 Health Economics and Health Management at Bielefeld University. She holds an M.Sc. in Public Health and a B.Sc. in Health Communication, both from Bielefeld University. Her research focuses on health-related quality of life , health economic evaluation , and respiratory syncytial virus (RSV) diagnostics. 2015: General higher education entrance qualification 2015-2016: Federal Voluntary Service (Bundesfreiwilligendienst) in a Munich hospital 2016-2019: B.Sc. in Health Communication at Bielefeld University 2019-2021: M.Sc. in Public Health at Bielefeld University Her recent publications analyze measurement properties of HRQoL instruments , statistical adjustments for RSV misclassification , and telemedicine adoption trends . She contributes to projects like DigiSep (funded by the German Federal Government) and Impact of medical diagnosis on German EQ-5D values . Her work combines empirical research with policy-relevant data analysis . Current research themes include: Comparative analysis of EQ-5D-5L and Stroke Impact Scale 2.0 Validity studies of ICD-10 codes for RSV Telemedicine utilization patterns in outpatient care Risk factor analysis for herpes zoster infections She actively participates in third-party funded projects and contributes to peer-reviewed journals and conference proceedings .
