Carey Barry is an Associate Clinical Professor and Chair of the Department of Medical Sciences at Northeastern University. With over two decades of clinical experience in surgical specialties like vascular, cardiac, and plastic surgery, she transitioned from a career as a medical technologist into physician assistant education. Her research focuses on surgical training, professional behavior, and predictors of success in PA programs. MS, Physician Assistant, Quinnipiac University, Hamden, CT BSc, Medical Laboratory Science, University of New Hampshire, Durham, NH Barry’s work bridges clinical practice and education, emphasizing interprofessional collaboration and equity in PA admissions. Her recent studies investigate language barriers, veteran transitions, and gender minority representation in PA programs, alongside validating statistical methods for assessing clinical competency. Carey Barry’s publications span surgical wound infections, immunohematology, and educational outcomes. Key trends include disparities in PA program admissions, the role of professionalism in licensing, and data-driven approaches to clinical training evaluation. Distinguished Fellow, American Academy of PAs (AAPA) MCPHS University 2016 Faculty Scholarship Showcase Award – Teaching Category As an educator, she teaches courses in surgical principles and clinical diagnostics. Her certifications include NCCPA Physician Assistant Special Recognition in Surgery and Medical Technologist (ASCP). Barry’s contributions highlight the intersection of clinical excellence and evidence-based medical education.
Payam Barnaghi is a Professor and Chair in Machine Intelligence Applied to Medicine at Imperial College London's Department of Brain Sciences, part of the Faculty of Medicine. He holds multiple leadership roles, including Co-Director of the School of Convergence Science in Human and Artificial Intelligence and Deputy Head of Neurology. His research focuses on AI-driven healthcare solutions, particularly in neurosciences and dementia care. He leads the Translational Machine Intelligence group at the UK Dementia Research Institute (UK DRI) and is a Visiting Professor at University College London's Institute of Child Health. His affiliations include the NVIDIA Deep Learning Institute, the British Heart Foundation Centre for Research Excellence, and the UK DRI Care and Research Technology Centre. He has received awards such as the Wellcome Trust Mental Health Ideathon Award (2023) and the IEEE Outstanding Leadership Award (2017). His work emphasizes remote patient monitoring, digital biomarkers, and explainable AI for early health event detection. Key projects include the TIHM (Technology Integrated Health Management) initiative for dementia care, leveraging wearable sensors and machine learning. He contributes to interdisciplinary efforts in smart care ethics and has published extensively on topics like neural network applications, healthcare data analysis, and clinical decision support systems.
Peter B. Noël is an Assistant Professor of Radiology at the Hospital of the University of Pennsylvania and holds academic affiliations with the Technical University of Munich (TUM). He is a member of the Institute for Diagnostic and Interventional Radiology and chairs the 'image reconstruction & x-ray' research group under Prof. Navab's Medical Informatics Applications department. His work integrates advanced imaging technologies with clinical applications. Education: PhD in Computer Science (2009, SUNY Buffalo), MSc in Computer Science (Toshiba Stroke Research Center), BEng in Biomedical Engineering (University of Applied Sciences Giessen, Germany). Research focuses on CT imaging advancements including diagnostic/interventional x-ray imaging, tomographic reconstruction algorithms, spectral imaging with photon-counting detectors, and GPU-based high-performance computing. He leads efforts to reduce radiation exposure in CT scans and translate cutting-edge imaging techniques into clinical practice. Awards: Behnker-Berger Foundation Research Award for contributions to CT radiation exposure reduction. Current projects include the 'image reconstruction & x-ray' group, DHM (Deutsches Herzzentrum München) collaborations, and leadership in labs like NARVIS (NArvIs) and RobUSt (Robotics and Ultrasound). His work is supported by national and industrial grants.
Debbi Marais is a Professor (Teaching Focussed) at the University of Warwick within the Warwick Medical School and Health Sciences department. She serves as the Director of Postgraduate Education and is a Principal Fellow of the UK Higher Education Academy , demonstrating strategic leadership in enhancing teaching quality, curriculum development, and student mentorship. With over 25 years of experience in higher education, she has held academic positions at Stellenbosch University , University of Aberdeen , and University of Warwick . Her expertise spans teaching, assessment, program coordination, quality assurance, and reflective practice. Marais’ research interests include pedagogical innovation , with a focus on technology-enhanced teaching and employability & professionalism , as well as public health nutrition covering infant and young child feeding , nutrition transition , and global health . She employs mixed methods in her research and has contributed to understanding exclusive breastfeeding barriers , maternal obesity trends in Africa, and Arabic weight-loss app design . Her work often intersects with technology-enhanced health education and interdisciplinary collaboration . Her recent publications highlight qualitative studies on food-based dietary guidelines in Kenya and South Africa, mobile health interventions for weight loss, and educational innovations in medical and nutrition training. These works reflect her commitment to global health equity and digital pedagogy , with recurring themes in African and Southeast Asian health contexts. She emphasizes participatory research methods and policy translation in maternal and child nutrition. Scientific Awards Principal Fellow of the UK Higher Education Academy Marais has supervised postgraduate research students (PhD and Masters) and contributed to curriculum reform through collaborative international projects. She has secured external funding for research and demonstrated interdisciplinary expertise in nutrition , public health , and health education .
Prof. Emiel Krahmer is a Professor at the Department of Communication and Cognition, Tilburg School of Humanities and Digital Sciences (TSHD), Tilburg University. His research focuses on healthcare communication, digital health technologies, and patient-centered approaches. He explores barriers/facilitators in return-to-work strategies for trauma patients, personalized predictions in rehabilitation, and the role of serious games in health behavior change. His work also addresses ethical challenges in self-monitoring platforms for mental health, emphasizing epistemic justice and algorithmic fairness. Collaborations with medical professionals and interdisciplinary teams highlight his contributions to digital health innovation. Key projects include studies on trauma patient perspectives, implementation of patient-reported outcome measures (PROMs), and game-based interventions. His research bridges communication science and clinical practice, aiming to enhance patient engagement and equitable healthcare delivery through technology.
Elena Niculina Dragoi is a Lecturer at the Faculty of Chemical Engineering and Environmental Protection 'Cristofor Simionescu' at Gheorghe Asachi Technical University in Iasi, Romania. Her academic work integrates Artificial Intelligence and Machine Learning tools for solving complex problems in Chemical Engineering and Environmental Protection . With over 30 published papers and six active research projects, her contributions span process optimization, nanomaterials, and sustainable technologies. Teaches Applied Informatics (Years 1 & 4) and Artificial Intelligence at the Faculty of Chemical Engineering Contributes to Programming Engineering at the Faculty of Computer Science, University 'Alexandru Ioan Cuza' Engaged in interdisciplinary courses at the Faculty of Automatic Control and Computer Engineering Research Interests : Elena's work focuses on modelling and optimization (90% emphasis) of chemical processes using AI methodologies, with cross-disciplinary applications in environmental engineering (70%) and chemical engineering (95%). Her recent publications highlight innovations in: 3D-printed nanocomposite adsorbents for pollutant removal Metaheuristic optimization algorithms for industrial processes Hydrogen generation via nanocatalysts Electrochemical biosensors for environmental and health monitoring AI-driven wastewater treatment systems Green chemistry applications in pharmaceutical and dye removal
Dr. Richard Segall is a Professor in the Department of Information Systems and Business Analytics at Arkansas State University , affiliated with the Beck College of Sciences & Mathematics . He is also affiliated faculty in the Master of Engineering Management (MEM) Program , the Environmental Sciences Program , and serves on thesis committees at the University of Arkansas at Little Rock (UALR) . Education: Ph.D. in Operations Research, University of Massachusetts at Amherst (1984) M.S. in Operations Research and Statistics, Rensselaer Polytechnic Institute (1975) M.S. in Mathematics, Rensselaer Polytechnic Institute (1973) B.S. in Mathematics, Rensselaer Polytechnic Institute (1971) Dr. Segall's research spans data mining, text mining, web mining, big data analytics, bioinformatics, supercomputing applications, and mathematical modeling . His work bridges business analytics and computational biology , with a focus on transdisciplinary applications in agriculture, healthcare, and space systems. His recent publications emphasize genomic data analysis , plant disease diagnostics , AI-driven healthcare solutions , and space technology forecasting . The integration of machine learning , data visualization , and open-source tools is a recurring theme across domains. Scientific Awards & Grants: Three research awards from the National Research Council (NRC) Software grants from Oracle Corporation and SAS Institute, Inc. Dr. Segall has served on the editorial boards of the International Journal of Data Science , International Journal of Data Mining, Modelling and Management , and International Journal of Fog Computing . He previously contributed to the Arkansas Center for Plant-Powered Production (P3) and currently participates in the Center for No-Boundary Thinking (CNBT) .
Nathorn Chaiyakunapruk is a Professor in the Department of Pharmacotherapy at the University of Utah College of Pharmacy . He holds an adjunct appointment in Population Health Sciences and serves on multiple institutional committees including the Global Health Steering Committee and Health Economics Core at CTSI . His academic leadership extends to international roles with the World Health Organization and founding initiatives like the ISPOR Asia Consortium . Education : PhD in Pharmaceutical Outcomes Research, University of Washington PharmD, University of Wisconsin-Madison BS in Pharmaceutical Science, Chulalongkorn University Research Interests span health technology assessment , global health economics , and evidence synthesis . His work applies methodologies like network meta-analysis and umbrella reviews to address health equity, infectious disease modeling, and pharmaceutical policy. Recent studies focus on social determinants of health and vaccine economic value . Article Trends highlight collaborations in AI-assisted systematic reviews , vaccine rollout optimization , and health disparities . His publications frequently address cost-effectiveness and global health burden across infectious and non-communicable diseases. Scientific Awards : Senior Class (P4) Distinguished Teacher (2022) NRCT Outstanding Research Award (2019, 2012) Monash University PVC Research Award (2015) Nagai Research Foundation Awards (2006-2010) ISPOR Task Force Leadership (CHEERS 2022) Teaching & Service : Courses include Systematic Review and Meta-analysis and Global Health Policy . He chairs the Asia Pacific Evidence-based Medicine Network and advises WHO on vaccine economics and Thailand’s National Health Security Office on pharmaceutical policy.
Panagiotis Papapetrou is a Professor of Data Science and Deputy Head of Department at the Department of Computer and Systems Science , Stockholm University (since 2017). He also serves as Head of the Data Science Research Group and holds an Adjunct Professor position at Aalto University (Finland). As a Board Member of the Swedish Association for Artificial Intelligence (SAIS) , he contributes to shaping AI research directions in Sweden. Research Pillars: Algorithmic data mining, interpretable machine learning, time series classification, and health informatics Key Projects: AI for societal fairness, digital twins for smart buildings, EXTREMUM for explainable medical AI, and e-learning personalization Teaching Legacy: Developed courses in Data Mining (HT2013-2022), Machine Learning (VT2022-2024), and Health Informatics (VT2018-2021) His work focuses on interpretable AI for healthcare applications, particularly through counterfactual explanations for time series classification and forecasting. This includes developing methods like Glacier for constrained counterfactuals and Ijuice for k-justified explanations. His research also explores multimodal clustering of sepsis patient records and federated learning approaches for ICU mortality prediction. Recent scientific contributions include: CounterFair (2024): Group fairness analysis via counterfactual burden metrics M-ClustEHR (2024): Multimodal clustering for electronic health records COMET (2024): Constraint-based glucose forecasting explanations Temporal pattern mining (2024-2025): Enhanced forecasting models through decomposition Z-Time (2024): Interpretable multivariate time series classification His editorial leadership includes: Action Editor at Machine Learning Journal (since 2024) Action Editor at Data Mining and Knowledge Discovery (since 2018) Guest Editorial Board for ECML/PKDD Journal Track (2014-2019)
Peter X. K. Song is a Professor in the Department of Biostatistics at the University of Michigan School of Public Health. With expertise spanning statistical methodology development and interdisciplinary applications, Dr. Song maintains active collaborations across Nutritional Sciences, Environmental Health Sciences, Chronic Disease research, and Nephrology. His work bridges theoretical statistics with practical healthcare solutions, focusing on innovative approaches to complex data challenges in public health and medicine. Based at the M4140 SPH II building in Ann Arbor, he leads the Song Lab and contributes significantly to the academic community through teaching, research mentorship, and scholarly publications. PhD, University of British Columbia, Vancouver, 1996 BS, Jilin University, Changchun, 1985 Dr. Song's research focuses on the statistical foundation of big data analytics, with particular emphasis on data integration, distributed inference, high-dimensional data analysis, longitudinal data analysis, mediation analysis, and spatiotemporal modeling. His methodological innovations address critical challenges in smart health applications, including organ exchange programs, children's health, chronic disease management, environmental health assessment, and nutritional sciences. His approach combines statistical theory, integer optimization, and algorithm development to create practical tools that help researchers understand complex relationships between environmental exposures and health outcomes. Dr. Song's publication record demonstrates a consistent trajectory of methodological innovation applied to pressing health challenges. His recent work shows increasing focus on sleep classification using AI techniques, personalized treatment effect analysis, distributed statistical methods for high-dimensional data, and epigenetic applications in adolescent health. The interdisciplinary nature of his research is evident in publications spanning biostatistics journals, computer science venues, and domain-specific medical publications. His work increasingly addresses the challenges of integrating diverse data sources while maintaining statistical rigor in the era of big data. IMS Fellow ASA Fellow Elected Member of the International Statistical Institute 2017 ENAR John Van Ryzin Award Dr. Song has mentored an impressive 22 PhD students and 6 postdoctoral trainees throughout his career, with many now holding faculty positions at prestigious institutions or working as data scientists in leading technology companies. His lab, the Song Lab, currently supports two postdoctoral research fellows and eight doctoral students working on cutting-edge statistical methodology development. His collaborative research extends across numerous grants that support interdisciplinary projects in kidney paired donation programs, environmental health studies, nutritional sciences, and chronic disease research, demonstrating his commitment to translating statistical innovation into practical health solutions. The Song Lab serves as a hub for interdisciplinary statistical research at the University of Michigan, bringing together experts from statistics, operations research, and machine learning to address complex challenges in medical and public health sciences. Current lab members include eight doctoral students and three postdoctoral fellows working on projects related to optimal organ matching strategies, causal mediation pathways of omics biomarkers, and statistical methods for big data integration. The lab maintains strong connections with clinical researchers across nephrology, pediatrics, environmental health sciences, and nutritional sciences, ensuring that methodological developments remain grounded in real-world applications.
Dr. Jeremy Greene is the William H. Welch Professor of the History of Medicine and Director of the Department of the History of Medicine and the Center for Medical Humanities and Social Medicine at Johns Hopkins University . He holds joint appointments in the Department of History of Science and Technology and the Department of Anthropology at the Krieger School of Arts and Sciences. Education includes an MD and PhD in the History of Science from Harvard (2005), with a Residency in Internal Medicine at Brigham & Women’s Hospital (2008). His research explores how medical technologies shape understandings of health, disease, and pharmaceuticals, drawing on historical, anthropological, and policy frameworks. His scholarly activities span 20th-century clinical medicine , pharmaceuticals , medical anthropology , and global health . Recent publications analyze the evolution of digital health , generic drugs , and medical device innovation . Scientific Awards include the 2021 Nicholas Davies Award (ACP) Rachel Carson Prize (Sociology of Science) Edward Kremers Award (Pharmaceutical History) Richard Shryock Medal (Medical History) Dr. Greene also practices Internal Medicine at the East Baltimore Medical Center and contributes to initiatives like the Johns Hopkins Drug Access and Affordability Initiative and the Berman Institute of Bioethics .
Dr. Helena Mentis is Professor and Department Head of Information Science at Drexel University's College of Computing & Informatics. She holds a PhD in Information Sciences from Pennsylvania State University, an MS in Communication from Cornell University, and a BS in Psychology from Virginia Tech. Her research focuses on human-centered computing in healthcare, with emphases on telemedicine, online safety for vulnerable populations, and responsible technology design. Research Interests: Dr. Mentis investigates collaborative technologies for healthcare contexts using sociotechnical frameworks. Her work includes: Developing telemedicine systems for surgical training and rehabilitation Designing cybersecurity safeguards for older adults with cognitive impairments Creating ethical frameworks for computing education Awards & Leadership: US Fulbright Scholar (2021) Former Executive VP/President of ACM SIGCHI Grants & Labs: Secured $1.4M+ in NSF/Mozilla funding for projects like Telemedicine at Scale and Negotiating Cyber Systems Access . Directed UMBC's Center for Responsible and Inclusive Technology and Bodies in Motion Lab.
Professor Trina Myers serves as the Head of School for the School of Information Technology at Deakin University's Faculty of Science Engineering and Built Environment. With extensive experience in academia and research leadership, she plays a pivotal role in shaping IT education and research directions at Deakin. She is also an active member of the Australian Council of Deans of ICT (ACDICT), having served as its immediate past President. Her educational background includes: Doctor of Philosophy in Computer Science from James Cook University Master of Business Administration from James Cook University Master of Information Technology from James Cook University Professor Myers' research focuses on semantic technologies, ontology engineering, Internet of Things, knowledge management, natural language processing, and human-computer interaction . Her work emphasizes interdisciplinary collaboration, bridging technology with fields such as healthcare, marine science, environmental conservation, and business. She has pioneered approaches in academagogy (academic gamification) to enhance online learning engagement, particularly for adult learners. Her IoT research has significant applications in healthcare space optimization, environmental monitoring, and resource management. Her recent publications demonstrate a strong trajectory in applying AI and IoT technologies to solve real-world problems, particularly in healthcare, education, and resource optimization. There's a clear pattern of interdisciplinary work connecting computer science with healthcare, education, and environmental science. Her research increasingly focuses on human-centered technology design, especially for vulnerable populations like adolescents with autism spectrum disorder. Her notable achievements include: Fellow of the Australian Computer Society (2023) Australian Awards for University Teaching (AAUT) Teaching Award (2020) Women in IT Professional Leadership Award Finalist (2020) Asia-Pacific International Triple E Entrepreneurial Educator of the Year Award (1st runner-up, 2020) Australian Computer Society, National Digital Disruptor ICT Educator of the Year (2019) Professor Myers actively supervises doctoral students across diverse research areas including gamification in language learning, brain tumor analysis using deep learning, AI in higher education, AI for refugee resilience, data integrity in edge environments, and quantum-driven satellite networking. She has secured significant research funding, including a recent grant for "Indiginizing ICT Curriculum: A Starter Framework for the Community of Practice" through the Australian Council of Deans of ICT. Her teaching philosophy emphasizes active learning methodologies, Process Oriented Guided Inquiry Learning (POGIL), blended learning, and collective intelligence approaches.
Jerad Moxley is an Assistant Professor of Psychology at Weill Cornell Medical College since 2022. His academic work bridges psychology and gerontology, focusing on mental health, cognitive functioning, and technology adoption in aging populations. He contributes to interdisciplinary research in medicine and public health, particularly in dementia care, palliative care, and aging with chronic conditions like HIV. Ph.D., Florida State University (2016) M.A., Murray State University (2008) B.A., Murray State University (2004) Dr. Moxley’s research explores the psychological and social dimensions of aging, including loneliness, pain disparities, and self-perceptions of aging. He investigates how technology can enhance aging in place and improve well-being for older adults with cognitive impairments or HIV. His work often integrates cross-cultural perspectives, as seen in studies on Puerto Rican older adults and racial/ethnic differences in pain and mental health outcomes. The trends in his publications highlight interdisciplinary approaches to aging, combining psychology, public health, and technology. Recent studies address elder neglect interventions, tech adoption barriers, and the role of social support in physical and cognitive health. Earlier work examines stress-cognition interactions, late-onset depression, and cognitive aging through chess skill and decision-making paradigms. Dr. Moxley has secured significant funding from the National Institute on Aging and the Administration for Community Living. Grants include projects on pain in later life, collaborative care models for serious illness, and technology-based interventions for aging adults with HIV. He serves as Co-Investigator and Key Personnel in initiatives like the CREATE Center and ENHANCE Center, focusing on aging and technology enhancement.
Stephen T. Wong holds the John S. Dunn Presidential Distinguished Chair in Biomedical Engineering and serves as Professor of Radiology and Medicine with Tenure and Chief of Medical Physics at Houston Methodist. He maintains professorships across multiple prestigious institutions including Weill Cornell Medicine (Radiology, Neurosciences, Pathology and Laboratory Medicine), Texas A&M University, Baylor College of Medicine, University of Texas MD Anderson Cancer Center, Rice University, University of Texas Health Houston, and University of Houston. Weill Cornell Medicine: Professor of Computer Science and Bioengineering in Radiology (since 2008), Pathology and Laboratory Medicine (since 2010), and Neuroscience (since 2012) Houston Methodist: John S. Dunn Presidential Distinguished Chair in Biomedical Engineering Academic leadership: Director of multiple research centers including Ting Tsung and Wei Fong Chao Center for BRAIN and AI in Innovative Medicine lab Dr. Wong's research employs a systems-based approach integrating engineering with biology and medicine to elucidate disease mechanisms. His laboratory focuses on discovering novel drugs and biomarkers while developing advanced diagnostic and therapeutic devices, with particular emphasis on cancer, neurological disorders, and metabolic diseases. Current projects target micro- and macroenvironments of cancer and Alzheimer's disease, apply spatial and systems biology methods for drug discovery, create label-free point-of-care molecular diagnostics, and develop AI applications for stroke triage and treatment. His publication portfolio demonstrates consistent growth over three decades, with over 500 peer-reviewed papers and five books. Recent work shows strong emphasis on artificial intelligence applications in medical imaging, cancer therapeutics, and neurological diagnostics, with multiple 2025 publications featuring multimodal AI approaches for hepatocellular carcinoma, lung cancer interventions, tumor evolution, brain imaging, and thyroid nodule characterization. Fellowships: IEEE, AIMBE, IAMBE, ACMI, AMIA, Optica, and AAIA Honors: AIIA Fellow (2024), American College of Medical Informatics Fellow (2023), AAIA-Fellow (2021), AIMBE Fellow (2021) Professional: Registered Professional Engineer (PE), Executive education from Stanford, MIT, and Columbia Business Schools Dr. Wong has trained over 170 PhD, MD/PhD, and postdoctoral scholars, with four now holding endowed chairs. His research has received continuous NIH funding for three decades, supporting 35 active and completed projects including DeepStroke+ for AI stroke detection, Alzheimer's disease research, and cancer diagnostics. He has founded multiple research centers including the Division of Shared Resources at Houston Methodist Neal Cancer Center, Translational Biophotonics Lab, and Center for Modeling Cancer Development.
