About the Editors
Editor-in-Chief
Joseph C. Kvedar, MD
Harvard Medical School
Mass General Brigham
Boston, USA
At Mass General Brigham (Partners HealthCare), Dr. Joe Kvedar has focused on driving innovation, creating the market, and gaining acceptance for telehealth for nearly three decades. He is now applying his expertise, insights, and influence to advance the adoption of telehealth and virtual care technologies at the national level. Dr. Kvedar is Professor of Dermatology at Harvard Medical School and President of the American Telemedicine Association (ATA). He is co-chair the American Medical Association's (AMA) Digital Medicine Payment Advisory Group (DMPAG), which works to ensure widespread coverage of telehealth and remote patient monitoring, and successfully established several new provider codes for telehealth reimbursement through the CPT process. Dr. Kvedar is also a member of the AAMC’s (Association of American Medical Colleges) telehealth committee, creating tools that will enable medical schools and residency programs to integrate telehealth into the training of future practitioners. He is the author of two books on digital health: The Internet of Healthy Things and The New Mobile Age: How Technology Will Extend the Healthspan and Optimize the Lifespan.
Deputy Editors
Daniel C. Baumgart, MD, PhD
University Professor, College of Health Sciences and College of Natural and Applied Sciences
University of Alberta
Edmonton, Alberta, Canada
Professor Daniel C. Baumgart, MD PhD MBA went to medical school in Berlin (Germany), Basel (Switzerland) and Würzburg (Bavaria). He received his training at Charité Medical School (Humboldt-University of Berlin), at the University of Pennsylvania, Philadelphia, PA, Georgetown University, Washington, DC, and the National Institutes of Health (NIH) Bethesda, MD, USA. An internationally recognized inflammatory bowel disease (IBD) expert and trailblazer of digital innovation, he has a strong interest in digital health, artificial intelligence (AI) and decision support to enable precision health. He is the principal investigator and program director of the "From Data to Decision (FD2D) - Digital Transformation and Artificial Intelligence from Data Value Chain to Human Value" Collaborative Research and Training Experience (CREATE) program launched in 2022 that unites a multidisciplinary group of researchers and innovators at 22 leading academic institutions and technology companies in North America, Europe and Asia, that develop and study digital transformation and artificial intelligence applications across various academic disciplines and industrial sectors as well as their impact on society, funded by the Natural Sciences and Engineering Research Council of Canada (NSERC), Mathematics of Information Technology and Complex Systems (Mitacs) and the University of Alberta, Edmonton, Canada.
Daniel Capurro, MD, PhD
School of Computing and Information Systems, Centre for the Digital Transformation of Health, University of Melbourne
Melbourne, Australia
Daniel Capurro is a General Internist and biomedical informatics researcher, currently Deputy Director of the Centre for the Digital Transformation of Health at the University of Melbourne. His research focuses on applying data science to solving complex clinical problems such as overdiagnosis and clinical variability. His methods include process mining and applied machine learning. Daniel completed his MD and Internal Medicine residency training at Pontificia Universidad Catolica de Chile and obtained a Phd in Biomedical and Health Informatics from the University of Washington, USA.
Adam Dunn, PhD
Professor of Biomedical Informatics, Faculty of Medicine and Health
The University of Sydney
Sydney, NSW, Australia
Adam Dunn is a Professor of Biomedical Informatics in the Faculty of Medicine and Health at The University of Sydney. He has more than 15 years of experience working across most research areas in biomedical informatics, but specialises in applications of machine learning and natural language processing. He has also published in public health in areas related to misinformation and vaccination, and in meta-research in areas related to conflicts of interest and biases in clinical trials and systematic reviews.
Alan Godfrey, PhD
Northumbria University
Newcastle upon Tyne, UK
Alan is an Associate Professor and head of the Digital Health and Wellbeing research group in the Department of Computer and Information Sciences, Northumbria University (UK). His major research is in algorithms for data science and analytics in healthcare. This includes areas of artificial intelligence, machine learning, data mining and multidimensional signal processing. His has specific interests in inertial sensor-based wearable technology to examine human movement, such as gait analysis. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and member of the Institute of Engineering and Technology (MIET).
Yang Xie, MD, PhD
University of Texas Southwestern Medical Center
Dallas, TX, USA
Yang Xie is Professor and Associate Dean of Data Science at UT Southwestern Medical Center, where she holds the Raymond D. and Patsy R. Nasher Distinguished Chair in Cancer Research and leads the Data Science and AI for Precision Health Initiative. She serves as founding Interim Chair of the Department of Health Data Science and Biostatistics at the O'Donnell School of Public Health. Her research focuses on developing innovative AI algorithms and data science methods for health applications and digital medicine. Dr. Xie specializes in integrating multi-modality data to create predictive models that enhance clinical decision-making and personalized healthcare delivery. With interdisciplinary training in statistics, medicine, and epidemiology, she has published over 200 papers advancing the field of health data science.
Associate Editors
Grayson W Armstrong, MD, PhD
Instructor, Department of Ophthalmology
Massachusetts Eye & Ear / Harvard Medical School
Boston, MA, USA
Grayson W. Armstrong, MD, MPH is an ophthalmologist and researcher at Massachusetts Eye & Ear of Harvard Medical School, where he serves as the Director of Ophthalmic Emergency Services and Associate Director of Ophthalmic Medical Student Education. Dr Armstrong's research interests include ophthalmic telemedicine, artificial intelligence, and the creation and validation of novel medical devices. He is also interested in programmatic implementation of public health screening measures, ophthalmic trauma, and medical education. Dr Armstrong is active in health policy, advocacy, and organized medicine.
Rupesh Agrawal, MD
Professor and Senior Consultant
National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore and Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
Dr. Rupesh Agrawal, an Associate Professor and Senior Consultant Ophthalmologist, heads research at the National Healthcare Group Eye Institute and co-heads the Ocular Infections and Antimicrobials department at the Singapore Eye Research Institute. His career spans over a decade in Singapore, with over 350 peer-reviewed publications and numerous pioneering research initiatives. He established the global Program for Ocular Inflammation and Infection Translational Research (PROTON), which unites expertise from various domains to tackle intraocular inflammatory diseases. Dr. Agrawal's mentorship extends to large number of medical students and residents, earning him several awards for his dedication. Beyond his professional achievements, he is also recognized for his humanitarian contributions across Asia, receiving the Healthcare Humanity Award and the President Voluntarism Philanthropy Award.
Harrison Bai, MD
Department of Radiology and Radiological Science, Johns Hopkins University
Baltimore, MD, USA
Dr. Harrison Bai is an Associate Professor of Radiology at Johns Hopkins University with dual board certification in diagnostic and interventional radiology. His research focuses on applying artificial intelligence and deep learning to medical imaging, particularly for disease diagnosis, prognosis, and treatment response assessment. With over 150 peer-reviewed publications and a strong background in bioinformatics and computer science, Dr. Bai has led the development of novel algorithms to enhance clinical decision-making while preserving data privacy. His work emphasizes translational impact, spanning a wide range of imaging modalities and clinical applications.
Mattia Cattaneo, PhD
University of Bergamo
Italy
Mattia Cattaneo is an Associate Professor of Management of Healthcare Organizations at the University of Bergamo. His research focuses on data-driven decision-making in healthcare, combining operations research, artificial intelligence, and management science to improve efficiency, access, and resource allocation in clinical systems. His work addresses challenges in emergency care, digital health, and the design of integrated service networks. He coordinates multi-institutional projects addressing national healthcare priorities and contributes to ANTHEM- Advanced Technologies for Human-Centered Medicine, Italy's flagship program for digital innovation and translational research in healthcare. Internationally, he is Senior Research Fellow at IN+ (Instituto Superior Técnico, Lisbon), Special Research Associate at CHERA (University of Hong Kong), and Scientific Advisor to the European Foundation for Biomedical Research (FERB). He also serves as Advisor to the COST Association and Evaluator for the U.S. National Science Foundation (NSF).
David Chartash, PhD
Yale University School of Medicine
New Haven, CT, USA
Dr. Chartash's research aims to examine information needed by physicians for diagnosis given the digitization of medical information; how physicians read and write.
Specifically, this research is bounded within the clinical encounter, examining both the collection of data from parents/patients and its recording by physicians in the electronic medical record.
Tinglong Dai, PhD
Johns Hopkins University
Baltimore, MD, USA
Tinglong Dai is the Bernard T. Ferrari Professor at the Johns Hopkins Carey Business School and a founding member of the leadership team of the Hopkins Business of Health Initiative. His research interests span human-AI interaction, healthcare analytics, and global supply chains. As co-chair of the Johns Hopkins Workgroup on AI and Healthcare, his current work focuses on developing a science of scaling medical AI, with an emphasis on integrating AI into clinical workflows to enhance productivity, access, and equity in healthcare delivery. He is particularly interested in how transformative technologies reshape behavioral, incentive, and policy issues in healthcare operations and improve decision-making in high-stakes environments. His research has been published in leading journals such as npj Digital Medicine, NEJM AI, Management Science, Manufacturing & Service Operations Management, and Harvard Business Review.
Chathuri Daluwatte,PhD
Head of AI Diagnostics,Alexion AstraZeneca Rare Disease
Boston, MA, USA
Chathuri Daluwatte, PhD is the Head of AI Diagnostics at Alexion AstraZeneca Rare Disease.
Her work spans across drug development, health AI, software as a medical device, regulatory science and policy across multiple therapeutic areas for drugs, vaccines, and devices in cardiovascular, infectious diseases, neuroscience, immunology and inflammation, rare diseases and gene therapy.
She has a bachelor’s degree spanning fields of electronics, telecommunication, and computer science, a master’s degree in statistics, and a Ph.D. in biomedical engineering. She has worked at bioMérieux and in the U.S. Food and Drug Administration (FDA), both at the Center for Devices and Radiological Health (CDRH), and the Center for Drug Evaluation and Research (CDER) and at Sanofi, driving transformational impacts across the life science value chain using AI, globally.
Francesca Faraci, PhD
SUPSI Univesrity - MeDiTech/BSP Group Leader
Lugano
Founder and leader of the Biomedical Signal Processing group, her focus is on leveraging AI tools, advanced statistics, data mining, machine learning, deep learning, and bio-behavioral feedback, for enhancing medical devices and software platforms. Her researchs cover mainly three areas: BRAIN-Neuroscience (EEG. sleep studies), HEART-Cardiology (ECG analysis), and BODY-LIFESTYLE (wearable technology advanced data analysis).
Oscar Freyer, MD
TUD Dresden University of Technology
Dresden, Germany
Oscar Freyer is a medical doctor and researcher focused on the safety, security, and regulation of medical devices, as well as the resilience of digital health systems. As a Research Associate at TU Dresden’s EKFZ for Digital Health, he studies AI safety, cybersecurity, and the regulation of connected medical technologies and healthcare infrastructure. He leads interdisciplinary work on system resilience and evidence-based policy.
Benjamin Gmeiner, PhD
Novartis
Nürnberg, Germany
Dr. Benjamin Gmeiner is Director of Medical Data Strategy & Science at Novartis, where he leads innovation in applying AI to clinical research. With a background in quantum physics and neuroscience from the Max Planck Institute and Harvard University, he brings together deep technical expertise and strategic leadership at the intersection of AI and medicine. His work focuses on leveraging real-world data and machine learning to accelerate evidence generation and improve patient outcomes. Benjamin’s research interests include precision medicine, population health, digital twins, and health data ecosystems. He is also an appointed lecturer at FAU Erlangen-Nürnberg in the Department of Artificial Intelligence in Biomedical Engineering.
Bo Gong, MD, PhD
Department of Medical Imaging, University of Toronto
Toronto, Ontario, Canada
Dr. Gong is a neuroradiology fellow at the University of Toronto, and also completing a MSc degree in Computer Science at the University of Toronto. He is interested in developing innovative AI solutions to address the clinical needs in the imaging of neurological conditions, with a particular focus on multi-modality integration of clinical and imaging data.
Vijay Govindarajan, BSc, MCompSci, MSc
Expedia Group Inc
United States
Vijay specializes in building privacy-preserving, clinically reliable AI systems that support real-world digital medicine workflows. His research focuses on federated learning, secure computation, and robust deep learning architectures that safeguard patient privacy while delivering high-performance medical diagnostics. Vijay has developed advanced models for Alzheimer’s detection, multi-disease retinal analysis, gastric cancer histopathology, osteosarcoma risk stratification, and cloud-based clinical intelligence. His work spans the entire pipeline—from model design to system-level considerations—ensuring readiness for clinical deployment.
Kimberly Harding, PhD
Monarch Innovation Partners, Inc.
Rockville, MD, USA
Kimberly Harding is Founder and President of Monarch Innovation Partners, Inc., a technology consulting firm that supports U.S. and international healthcare and life science commercial, non-profit, and academic research organizations by providing:
• Enterprise Architecture Consulting
• Health Technology and Regulatory Science Frameworks
• Research and Development of Emerging Technology Platforms
Ms. Harding also leads and supports multi-national research consortiums and working groups that develop standards which focus on artificial intelligence, terminology, healthcare policies, and enterprise architecture models at the national and international level for both medical and dental domains.
Mary-Anne (Annie) Hartley, MD, PhD
LiGHT(Laboratory for Intelligent Global Health and Humanitarian Technologies), EPFL (School of Computer Science), Harvard-Chan School of Public Health (Ariadne Labs), CMU Africa
Switzerland
Prof Mary-Anne “Annie” Hartley leads the Laboratory for Intelligent Global Health and Humanitarian Response Technologies (LiGHT), where her research focuses on implementable and scalable AI for clinical practice—particularly in low-resource settings, humanitarian contexts, and large-scale deployment. Her interests include evaluation frameworks and clinical trials for AI tools, optimization techniques, collaborative and privacy-preserving continuous learning to protect data sovereignty, generative AI for medicine, and responsible AI. She collaborates with humanitarian and global health organizations to develop and validate technologies that can be safely deployed in crisis-affected and underserved environments.
Hao Hu, PhD
Professor, Institute of Chinese Medical Sciences & Faculty of Health Sciences
University of Macau
Macao SAR, China
Hao Hu is a professor at the Institute of Chinese Medical Sciences and the Faculty of Health Sciences at the University of Macau. His research focuses on applying health data science for digital medicine, biomedical discovery, and disease control. He is interested in developing digital medical devices and digital health.
Zhengxing Huang, PhD
Professor, Institute of Artificial Intelligence
Zhejiang University
Hangzhou, Zhejiang, China
Zhengxing Huang currently holds the position of professor at the Institute of Artificial Intelligence, Zhejiang University. His primary research focus lies in the interdisciplinary fields of clinical medicine, information science, and data science, with a specific emphasis on transforming paradigms in medical clinical decision-making.
Shenda Hong, PhD
Peking University
Beijing, China
Shenda Hong is an Assistant Professor (tenure-track) at National Institute of Health Data Science, and Institute for Artificial Intelligence, Peking University, China. His research interests focus on deep learning for temporal medical data, including electronic health records and biosignals (e.g., ECG, PPG, EEG, PSG, PCG, FHR). He is also dedicated to AI for digital health, enhancing smart devices with AI, and developing applications for clinical practice. He serves as a reviewer for top-tier AI conferences, including ICLR, NeurIPS, ICML, KDD, AAAI, and IJCAI.
Hyoyoung Jeong, PhD
UC Davis College of Engineering
United States
Dr. Hyoyoung Jeong is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of California, Davis. He earned his Ph.D. in Electrical and Computer Engineering from the University of Texas at Austin and completed his postdoctoral training at Northwestern University, where he developed soft, biointegrated electronic systems for digital health applications. His research focuses on skin-interfaced, implantable, and mobile platforms for continuous physiological monitoring, brain?body interaction analysis, and closed-loop modulation. His work also includes real-time biosignal analytics using machine learning, multimodal sensor networks, and translational collaborations with clinicians and neuroscientists.
Kai Jin, MD, PhD
The Second Affiliated Hospital, School of Medicine, Zhejiang University
Hangzhou, Zhejiang, China
Dr.Jin is an ophthalmologist and professor (tenure-track) at the Eye Center of the Second Affiliated Hospital, Zhejiang University School of Medicine. His research interests focus on the ophthalmology, imaging, artificial intelligence, and personalized medicine. He serves as a peer reviewer for esteemed journals such as BMJ, and Lancet Digital Health. In the past year, Dr. Jin received the WILEY Top Cited Article Award for 2022, and was recognized as one of the World’s Top 2% Scientists in 2024 (Elsevier).
Joseph Kambeitz, MD
Department of Psychiatry and Psychotherapy, University of Cologne and University Hospital Cologne
Cologne, Germany
Dr. Joseph Kambeitz is a clinical psychiatrist, psychologist, and researcher, currently serving as the Deputy Director of the Department of Psychiatry and Psychotherapy at the University of Cologne in Germany. He leads an interdisciplinary research group focussing on improving diagnosis and treatment in the area of clinical neurosciences. At the core of his work the employs neuroimaging, digital tools and data analytic approaches (including A.I.) to advance precision medicine for disorders of mind and brain.
Fikret Isik Karahanoglu, PhD
Pfizer Inc
Cambridge, MA, USA
Isik is a Director in Pfizer Research and Development with the AI/ML, Quantitative and Digital Sciences group. Prior to that, she was an Instructor in Radiology at Harvard Medical School. Her research interests include digital health monitoring tools, wearables, development of novel digital endpoints, clinical trial design, methods and modeling, signal processing, machine learning, statistics, neuroimaging, and MRI.
Kassandra Karpathakis, MPH
Gates Foundation
Washington DC, USA
Kassandra works at the intersection of public health, public policy, and digital technology, focusing on the responsible and effective use of technologies like AI. She has collaboratively shaped discourse and policies on safe, effective, and ethical AI in health for the UK’s National Health Service, the World Health Organization, the Global Digital Health Partnership, and others. Kassandra is a Senior Program Officer in AI Policy at the Gates Foundation.
Deepak Kumar, PT, PhD
Assistant Professor, Department of Physical Therapy, Boston University
Department of Physical Therapy, Boston University; Section of Rheumatology, Boston University Chobanian & Avedisian School of Medicine
Boston, MA, USA
Dr. Kumar is a clinician-scientist at Boston University. His research is to develop mechanism-informed and technology-enabled movement interventions for people with chronic knee pain that are effective, equitable, and scalable. His work intersects rehabilitation, biomechanics, digital health, artificial intelligence, and pain neuroscience. Dr. Kumar has over 50 publications and his research has been funded by federal, foundation, and industry sponsors.
Hyeonhoon Lee, MD(DKM), PhD
Seoul National University Hospital
Seoul, Republic of Korea
Hyeonhoon Lee is a physician-scientist and a research assistant professor at the Healthcare AI Research Institute of Seoul National University Hospital (SNUH), focusing on the development of practical AI systems for clinical applications. He also serves as the professor in charge of the Center for Data Innovation at the National Strategic Technology Research Institute (NSTRI), where he contributes to the creation of a global healthcare data ecosystem by leveraging clinical data from Korean hospitals and establishing interoperable pipelines that facilitate integration and collaboration across domestic and international healthcare platforms. His research focuses on real-time patient monitoring, clinical decision support, and personalized treatment planning, utilizing multimodal medical data such as biosignals, clinical texts, medical imaging, and electronic health records (EHR). To enable these applications, he explores advanced machine learning techniques such as reinforcement learning, large language models, and multi-agent systems. He was recognized with the Minister's Commendation from the Ministry of Health and Welfare of the Republic of Korea in 2024 as an emerging researcher for his contributions to healthcare technology advancement.
Chin Lin, PhD
National Defense Medical Center
Taipei, Taiwan, ROC
Dr. Lin's primary research focuses on the development of artificial intelligence models and their integration into clinical practice to validate improvements in healthcare quality. Dr. Lin's most renowned work is the AI-enabled ECG interpretation platform, capable of detecting over 50 diseases from a single ECG. This platform has initiated more than 10 clinical trials and has recently demonstrated the benefits of AI-ECG in reducing short-term mortality.
Gilbert Lim, PhD
SingHealth
Singapore
Dr. Gilbert Lim is a Senior AI Scientist with SingHealth. His research interests include the practical application of computer vision and artificial intelligence towards diagnostic and predictive modelling of medical conditions, in particular on less-explored modalities and tasks. He has also co-founded a start-up focused on health screening at scale, with products deployed in several countries.
Hooi Min Lim, PhD
University Malaya
Kuala Lumpur, Malaysia
Hooi Min Lim is a primary care physician and senior lecturer at the University of Malaya. Her research centers on the co-design and implementation of digital health interventions in clinical practice, bridging the gap between digital innovation and real-world application through the lens of implementation science. She is particularly interested about enhancing digital health literacy and addressing health misinformation.
Xi Long, PhD
Associate Professor, Department of Electrical Engineering
Eindhoven University of Technology
Eindhoven, The Netherlands
Xi Long is an Associate Professor in the Biomedical Diagnostics Lab, Department of Electrical Engineering at the Eindhoven University of Technology. Prior to that, he was a senior scientist and an AI lead at Philips Research where he has more than ten years of experience in healthcare research and innovation. His research interests include signal processing, machine learning, and unobtrusive sensing for health monitoring and digital medicine in many domains such as vital sign measurement, sleep, maternal and neonatal health, epilepsy, cardiology, intensive care medicine, and remote patient monitoring.
Yuan Luo, PhD
Feinberg School of Medicine, Northwestern University
Chicago, IL, USA
Dr. Luo is Professor in the Department of Preventive Medicine, and Chief AI Officer at the Northwestern University Clinical and Translational Sciences Institute (NUCATS) and at the Institute of AI in Medicine (IAIM). Dr. Luo’s research interests include machine learning, natural language processing, time series analysis, multi-omic analysis and medical imaging, with a focus on integrating these directions in the framework of multi-modal machine learning for health care.
Jacqueline Lutz, PhD
LUJA consulitng LLC and Boston University
Boston, MA
Prof. Jacqueline Lutz is a clinical neuroscientist and digital health researcher.
She currently advises leaders in the digital health industry on clinical development, regulatory strategy, digital product innovation, and scientific communication through her consultancy, LUJA Consulting LLC. Jacqueline also serves as an Assistant Professor at Boston University, where she teaches resident programs in Neuropsychiatry and Digital Mental Health at the Boston University School of Medicine's Department of Psychiatry.
Previously, Jacqueline held leading medical science positions at Akili Interactive, Click Therapeutics, and Biogen Digital Health. She earned her PhD from the University of Zurich and completed postdoctoral research at Massachusetts General Hospital and Harvard Medical School, where she studied mindfulness interventions for individuals living with psychiatric conditions and chronic pain, using tools ranging from fMRI to electronic momentary assessments.
Thomas McCoy, MD
Massachusetts General Hospital
MA, USA
Thomas McCoy is a physician-scientist focused on secondary use of data generated through routine care for clinical prediction and risk stratification. His research program is rooted in the acute care setting and efforts to use natural language processing applied to clinician-authored documentation as a means of quantifying poorly coded phenotypes. He leads the data platform at the Mass General Hospital (MGH) Center for Innovation and Digital Healthcare (CIDH).
Ryan McGinnis, PhD
Director, Center for Remote Patient and Participant Monitoring; Associate Professor, Department of Biomedical Engineering
Wake Forest University School of Medicine
Winston-Salem, USA
Dr. McGinnis is a digital health researcher and entrepreneur, and currently serves as the founding director of the Center for Remote Patient and Participant Monitoring, co-director of the M-Sense Research Group and an associate professor of biomedical engineering at Wake Forest University School of Medicine, the Academic Core of Advocate Health. His research program pairs innovations in wearable and mobile technologies with his expertise in user-centered design, biomechanics, biomedical signal processing, data science and machine learning to develop, validate and commercialize new digital health technologies. Current projects are focused on developing and validating digital biomarkers, phenotypes, and therapeutics in the areas of neurology, physical therapy, mental health and orthopedics.
Queensland University of Technology
Australia
Prof. Steven McPhail is a health systems innovator, health services researcher, health economist and clinician. He obtained his PhD from The University of Queensland. Prof. McPhail is Centre Director for the Australian Centre for Health Services Innovation (AusHSI) and the Centre for Healthcare Transformation at the Queensland University of Technology, where he is also the Prof. of Health Services Research. Prof McPhail works at the intersection of digital health and AI, implementation science, health economics and health policy.
Sanjay Mohanty, MD, MS
Assistant Professor, Department of Surgery
Indiana University School of Medicine
Indianapolis, IN, USA
Sanjay Mohanty is a colorectal surgeon and researcher. His work seeks to understand and innovate perioperative care delivery, especially in older adults, leveraging technology, clinical decision support tools, and implementation science. His work has been funded by AHRQ, the American College of Surgeons, the Hartford Foundation, and the NIH.
Reagan Mozer, PhD
Bentley University
Waltham, MA, USA
Dr. Reagan Mozer is an Assistant Professor in the Department of Mathematical Sciences at Bentley University. She earned her Ph.D. in Statistics from Harvard University, where she focused on developing methods for causal inference in complex experimental and observational settings. Her research explores the integration of causal inference techniques with natural language processing and machine learning, with applications in education, healthcare, and the social sciences. She also has extensive experience in experimental design and mixed methods research, with particular interests in health services research, digital health interventions, and educational program evaluation.
Muthuraman Muthuraman, PhD
Associate Professor, Chair of the Informatics for Medical Technology
University Augsburg, Institute of Computer Science
Augsburg, Germany
Muthuraman Muthuraman was born in Chennai, India, in 1980. Ph.D. degree in biomedical engineering from the technical faculty and Department of Neurology of Christian Albrecht’s University, Kiel, Germany, in 2010. In 2010, he joined the Department of Neurology, University of Kiel, as a Post-doc, and in 2013 became a senior post-doc. Currently from 2024 he is heading the group Informatics for Medical Technology (IMT) in Augsburg as an associate professor and second affiliation to Julius Maximilian university of Würzburg in the department of Neurology and head of the group Neural Engineering with Signal Analytics and Artificial Intelligence (NESA-AI). His current research interests include mathematical methods for time series analysis and source analysis on oscillatory signals, sleep, function of oscillatory activity in central motor systems, biomedical statistics, connectivity analyses, multimodal signal processing and analyses of EEG, MEG, fMRI and EMG, structural and network analyses on anatomical MRI and DTI, functional network analyses on PET imaging, machine learning and deep learning.
Girish Nadkarni, MD
System Chief, Division of Data Driven and Digital Medicine and Director, The Charles Bronfman Institute of Personalized Medicine
Icahn School of Medicine at Mount Sinai
New York, NY, USA
Dr. Nadkarni is the System Chief, Division of Data Driven and Digital Medicine and Director, The Charles Bronfman Institute of Personalized Medicine at the Icahn School of Medicine at Mount SInai. As both a physician and an informaticist he is an expert in health AI, biomedical informatics and digital health. He works with a large team of computer and data scientists, clinicians and informaticists to improve patient outcomes and create learning health systems.
Anthony Nguyen, PhD
Research Team Leader
The Australian e-Health Research Centre, CSIRO
Brisbane, QLD, Australia
Anthony Nguyen is a Research Team Leader and Principal Research Scientist from the Australian e-Health Research Centre (AEHRC), CSIRO’s e-Health research program within the Health and Biosecurity business unit. He leads the Health Data and Text Analytics team within the Health Informatics group to build a clinically focused natural language processing (NLP) research program and deliver innovative software solutions for automating the analysis of unstructured, narrative medical records. His team develops and applies advanced artificial intelligence (AI) techniques to analyse clinical data and text for the purpose of creating value via interoperability, decision support & reporting across all healthcare sectors. Techniques include the combination of text mining, statistical machine learning and information retrieval with clinical terminology (SNOMED CT) semantics to enhance clinical natural language understanding. In partnership with healthcare providers, he creates value from health data to deliver improved patient outcomes, health system performance and productivity.
Dinh Nguyen, MD, MSHI
Kaiser Permanente - Southern California Permanente Medical Group
Pasadena, CA, USA
Dinh Nguyen is the Regional Physician Director of Business Services at Southern California Permanente Medical Group, where he leads a team of data scientists, data analysts, and informaticists to implement artificial intelligence solutions for digital healthcare transformation. With extensive expertise in clinical informatics, he has pioneered projects, such as custom natural language processing models for Electronic Health Record systems and digital platforms, to enhance care delivery and care navigation. His leadership is demonstrated through his role on the SCPMG Artificial Intelligence Advisory Council and his unwavering commitment to advancing healthcare through innovative technology.
Jasmine Ong, PharmD
Division of Pharmacy, Singapore General Hospital
Singapore
Dr Jasmine is a BPS broad certified critical care pharmacist in Singapore General Hospital, Singapore. She is a recipient of the US-ASEAN Fulbright Scholarship and completed her training at University of California, San Francisco. Her interests lies in the clinical applications, evaluation and governances of artificial intelligence tools in medicine.
Alessia Paglialonga, PhD
Senior Research Scientist, National Research Council of Italy (CNR)
Institute of Electronics, Information Engineering and Telecommunications (IEIIT)
Milan, Italy
Alessia Paglialonga is Senior Research Scientist at National Research Council of Italy (CNR), Institute of Electronics, Information Engineering and Telecommunications (IEIIT, Information and Systems Engineering group) in Milan (Italy), adjunct Professor of biomedical informatics at Politecnico di Milano, and Visiting Researcher at Toronto Metropolitan University (Canada), Health Prediction Lab. Her research interests include health data analytics, machine learning, explainable and trustworthy AI, with focus on AI-enabled techniques for health prediction, sensory systems modeling and assessment, and digital solutions for personalized disease prevention.
Hua Pan, PhD
Associate Professor, Department of Medicine, Department of Pathology and Immunology, Department of Biomedical Engineering
Washington University in St. Louis
MO, USA
Hua Pan is a biomedical researcher in the field of translational medicine. She received her Ph.D. in Biomedical Engineering and an MBA in General Management/Entrepreneurship from Washington University in St. Louis. She is committed to translating her laboratory discoveries and technological advancements from the academia into practical applications in patient care through entrepreneurial initiatives. With support from the Small Business Technology Transfer (STTR) program administrated by the National Center for Advancing Translational Sciences (NCATS) at the National Institutes of Health (NIH), she has advanced new therapeutic technology to the commercial sector for further development. Her research focuses on identifying high-risk patient populations using molecular and imaging biomarkers, aiming to develop personalized therapeutics to address unmet medical needs via platform-based delivery systems. Additionally, she aims to integrate human and artificial intelligence to enhance diagnostics and treatment strategies, ultimately providing more accurate and personalized care.
Rüdiger Pryss, PhD
Professor, Institute of Clinical Epidemiology and Biometry
University of Würzburg
Würzburg, Germany
Rüdiger Pryss is Professor of Medical Informatics at the Department of Clinical Epidemiology and Biometry at the University of Würzburg. He is a computer scientist and has been active in research at the interfaces between medicine, psychology and computer science for over 10 years. Main research interests are digital medicine, mobile computing, medical data engineering, AI in medicine and medical informatics expert systems. In these areas, he has already developed over 20 digital applications that are used in different types of studies on various entities in medicine and psychology.
Raj Ratwani, PhD
Vice President of Scientific Affairs
MedStar Health Research Institujte
Washington, DC USA
Dr. Ratwani's research is focused on the usability, safety, and usefulness of digital health technologies. He has conducted rigorous analyses of electronic health records, telehealth platforms, and AI systems. With a background in cognitive science and human factors he looks to foster human-centered solutions.
Julie Redfern, PhD
Westmead Applied Research Centre
Faculty of Medicine and Health, University of Sydney
Sydney, Australia
Julie Redfern is a Professor of Public Health and a clinical physiotherapist. She has led clinical trials and epidemiology studies focussed on secondary prevention along with co-design, testing and implementation of digital health interventions. She is the current Academic Leader (Researcher Development) in the Faculty of Medicine and Health, University of Sydney, co-Chair of the Exercise, Prevention and Rehabilitation Council of the Cardiac Society of Australia and New Zealand and a World Heart Federation Emerging Leader.
John A. Rogers, PhD
McCormick School of Engineering and Neurological Society
Northwestern University
IL, USA
Dr. Rogers's research seeks to understand and exploit interesting characteristics of 'soft' materials, such as polymers, liquid crystals and biological tissues as well as hybrid combinations of them with unusual classes of micro/nanomaterials, in the form of ribbons, wires, membranes, tubes or related. Current research focuses on soft materials for conformal electronics, nanophotonic structures, microfluidic devices and microelectromechanical systems, all lately with an emphasis on bio-inspired and bio-integrated technologies.
Peter Shull, PhD
Department of Mechanical Engineering
Shanghai Jiao Tong University
Shanghai, China
Peter Shull is a Professor at Shanghai Jiao Tong University in the mechanical engineering department, where he leads the Wearable Systems Lab. His focus is on developing wearable systems to explore principles of human movement and movement modification by combining biomechanics and haptics principles to create unique sensors, real-time models, sensor fusion and artificial intelligence algorithms, and novel feedback paradigms. He has performed pioneering research involving wearable systems, human computer interaction, hand gesture recognition, and real-time movement sensing and feedback to improve human health and performance across an array of medical and sports applications.
Eike Staub, PhD
Merck KGaA, Darmstadt, Germany
Darmstadt, Germany
Dr. Staub is the Head of Oncology Data Science at Merck Healthcare KGaA in Darmstadt, Germany. After studying biotechnology and bioinformatics in Braunschweig, Glasgow, and Berlin, followed by doctoral research at the oncogenomics biotech company metaGen in Berlin. After further work in computational biology at the Max Planck Institute for Molecular Genetics, and at ALTANA Pharma, Dr. Staub moved to Merck KGaA in 2007, where he has since held various roles in advanced data analytics for both, drug research and development. Today, he leads a team of data scientists applying predictive analytics, machine learning, and computational modeling to discover new drug targets, develop biomarker strategies, and match patients to the most effective cancer therapies. He is a member of the European Association for Cancer Research (EACR) and the German Society for Medical Informatics, Biometry and Epidemiology (GMDS/GBM).
Mitchell Stotland, MD
Sidra Medicine, and Weill Cornell Medical College - Qatar
Doha, Qatar
Mitchell Stotland received his medical training at McGill University and the University of California, Los Angeles (UCLA). He served as a faculty member at the Geisel School of Medicine at Dartmouth from 1997 to 2014. Since 2014, he has been the Founding Division Chief of Plastic and Craniofacial Surgery at Sidra Medicine in Doha, Qatar. His clinical expertise includes the treatment of cleft lip and palate, complex craniofacial anomalies, total ear reconstruction, and facial trauma. His research focuses on the assessment and quantification of facial deformities through the development of novel machine learning models.
John B. Torous, MD
Beth Israel Deaconess Medical Center
Harvard Medical School
MA, USA
Dr. Torous is a board certified psychiatrist with a background in electrical engineering and computer sciences and enjoys exploring digital mental health. Dr. Torous is active in investigating the potential of mobile mental health technologies for psychiatry, developing smartphone tools for clinical research, leading clinical studies of smartphone apps for diverse mental illnesses and publishing on the research, ethical and patient perspectives of digital psychiatry.
Katarzyna Wac, PhD
Professor of Computer Science
University of Geneva, Quality of Life Technologies Lab
Geneva, Switzerland
Prof. Wac established the QoL Lab in 2010. The Lab aims to responsibly leverage daily life data sources to improve the quality of life of all individuals. The QoL lab's research interests include the fundamental and algorithmic problems, as well as the human-centric challenges related to the assessment and improvement of human behavior, well-being, health, disease self-management, and quality of life as it unfolds naturally over time and in context. Her most recent research projects focus on the design of digital biomarkers for sexual health and is conducted in collaboration with Stanford University.
Dennis Wang, PhD
Imperial College London and A*STAR Singapore
London, UK and Singapore
Dennis holds the Academy of Medical Sciences Professorship (Chair in Data Science) at Imperial College London. He is also a Senior Principal Scientist at A*STAR in Singapore. Dennis’ team focuses on identifying biomarkers of health outcomes across the human lifespan and using computational methods to predict, diagnose and treat multiple long term conditions. He is interested in machine learning approaches that leverage diversity from cohorts around the world. Having worked in both academia and industry, he enjoys mentoring early career data scientists, and helps steer mentorship programmes in the UK and Singapore.
Wei-Qi Wei, MD, PhD
Professor of Biomedical Informatics, Computer Science
Scientific Director for Phenotyping Care
Vanderbilt University Medical Center
My research program focuses on creating and leveraging informatics tools, including machine learning, natural language processing, and ontology techniques to harvest knowledge from big clinical/genetic data to advance precision medicine. My research has generated novel tools/approaches (e.g., PheCode, PheMAP, ConceptWAS and DDIWAS) for research and discovered new genetic relationships between common diseases (e.g., cardiovascular diseases) and common drugs (e.g., statin), and drug repurposing (e.g., for Alzheimer’s disease) I am the PI of multiple R01s and P50s (including NHGRI’s eMERGE Network). I also participated and remained an important role in several significant collaborative research networks, including eMERGE, GIST, PG-POP, PCORI, MPRINT, and All of US. I chair the eMERGE phenotyping workgroup and serve as the director of Precision Phenotyping Core at VUMC.
Chunhua Weng, PhD
Columbia University
New York, USA
Chunhua Weng's long-term research interest is to accelerate clinical and translational science. she combine text knowledge engineering and health data analytics to improve the efficiency and generalizability of clinical research. Her goal is to advance the field of clinical research informatics on several fronts, including text knowledge engineering, aggregate analysis of clinical studies, quality-aware computational reuse of electronic patient data and public data and clinical research workflow optimization in patient care settings towards the achievement of a learning health system.
Zoie S. Y. Wilkins-Wong, PhD
St. Luke's International University
Tokyo, Japan
Zoie S.Y. Wilkins-Wong is an Associate Professor at St. Luke’s International University (Tokyo, Japan). Specialized in digital health innovation, Dr. Wong’s research expertise is in Artificial Intelligence for Patient Safety Improvement, Health Data Analytics, and Infectious Disease Modelling and Visualization. She has been actively involved in collaborative research at the interface between informaticians, computer scientists, statisticians, epidemiologists, practitioners and policy makers investigating a range of challenging problems in health innovation. Dr. Wong currently serves on the Roster of Experts for the World Health Organization (WHO) Digital Health Technical Advisory Group (DHTAG) and as a global member of International Medical Informatics Association (IMIA) Technology Assessment and Quality Development in Health Informatics Working Group (TAQD WG).
Albert Yang, MD, PhD
National Yang Ming Chiao Tung University
Taipei City, Taiwan
Albert Yang is Chair of the School of Medicine at National Yang Ming Chiao Tung University, Taiwan, and a practicing psychiatrist. His research focuses on digital medicine and smart healthcare technologies, with significant contributions to developing AI-assisted platforms for diagnosing and evaluating mental disorders, as well as brain stimulation. He integrates neuroimaging, machine learning, and physiological signal analysis to understanding brain complexity, connectivity, and biomarkers in psychiatric and neurodegenerative conditions.
Guang Yang, PhD
Associate Professor, Department of Bioengineering and I-X
Imperial College London
London, UK
Dr. Guang Yang is an Associate Professor (Senior Lecturer) in the Bioengineering Department and Imperial-X at Imperial College London. He holds a UKRI Future Leaders Fellowship and serves as an Honorary Senior Lecturer in the School of Biomedical Engineering & Imaging Sciences at King's College London. His research group is dedicated to developing novel and translational techniques for imaging and biomedical data analysis. The group's focus encompasses research and development in data-driven fast imaging, data harmonization, data synthesis, federated learning, explainable AI, and AI in drug discovery. Currently, his work spans a wide range of clinical applications in cardiovascular disease, lung disease, and oncology. For more information about Yang’s Lab, visit: https://www.yanglab.fyi/
Jie Yang, PhD
Harvard Medical School, Mass General Brigham
Boston, MA, USA
Dr. Yang is an Assistant Professor at Brigham and Women’s Hospital and Harvard Medical School, specializing in medical informatics, AI in healthcare, and clinical natural language processing (NLP). He is a Fellow of the American Medical Informatics Association (FAMIA), an affiliate faculty member at the Broad Institute of MIT and Harvard, the Kempner Institute of Harvard University, and the Harvard Data Science Initiative, as well as a member of the Technical Advisory Group for the World Health Organization (WHO) Global Clinical Platform. His expertise includes the development of innovative NLP and AI algorithms, particularly large language models (LLMs), and their application to analyzing large medical datasets, especially electronic health records.
Lequan Yu, PhD
The University of Hong Kong
Hong Kong S.A.R., China
Lequan Yu's research interests lie at the intersection of artificial intelligence and biomedical data analysis, with a particular emphasis on medical imaging. His current work centers on multimodal learning, computational pathology, precision oncology, and the application of large language models in healthcare.
Yixuan Yuan, PhD
The Chinese University of Hong Kong
Hong Kong S.A.R., China
Dr. Yixuan Yuan is an Assistant Professor in the Department of Electronic Engineering at the Chinese University of Hong Kong. Her research focuses on developing AI models for healthcare to enhance precision medicine, with a particular interest in multi-modality medical data analysis, emphasizing model explainability, robustness, and security.
Jihui Zhang, PhD
The Affiliated Brain Hospita, Guangzhou Medical University
Guangzhou, Guangdong, China
Prof. Jihui Zhang is a psychiatrist and sleep researcher, currently deputy director for the Affiliated Brain Hospital, Guangzhou Medical University. His research has focused on the clinical assessment and intervention for sleep disorders and related mental disorders, especially using digital and wearable technology. He received his medical degree from the Sun Yat-sen University and PhD degree from the Chinese University of Hong Kong. He obtained postdoctoral training at the National Institutes of Health (NIH) and served as research assistant professor and assistant professor at the department of psychiatry, Chinese University of Hong Kong between 2012-2020.
Qingpeng Zhang, PhD
Associate Professor, Department of Pharmacology and Pharmacy and Institute of Data Science
The University of Hong Kong
Hong Kong S.A.R., China
Dr. Qingpeng Zhang is an Associate Professor in the Musketeers Foundation Institute of Data Science and the Department of Pharmacology and Pharmacy at HKU. His current research focuses on developing knowledge-enhanced predictive decision analytics methods to characterize the high-dimensional biological, clinical and behavioral data for drug discovery, precision medicine, and public health.
Rui Zhang, PhD
University of Minnesota
United States
Dr. Zhang is Professor and Founding Chief of Division of Computational Health Sciences at the University of Minnesota. He was named as McKnight Presidential Fellow and hold several leadership roles, including Chair of AI and Data science for Healthcare workgroup within the UMN's Data Science and AI Hub, Associate Director of Health AI & Data Science for the Center for Learning Health System Sciences, the Director of Natural Language Processing/Information Extraction (NLP/IE) research program, and previously served as Director of NLP at UMN's Clinical and Translational Science Institute. His research focuses on natural language processing, large language models, agentic AI, AI robustness, knowledge graphs, multimodal learning, and learning health systems, with applications across multiple health domains, including cancer, aging, nutrition, mental health, pharmacy, and complementary and integrative health. Dr. Zhang is a Fellow of International Academy of Health Sciences Informatics (FIAHSI), Fellow of American College of Medical Informatics (FACMI) and Fellow of American Medical Informatics Association (FAMIA). He is the current Chair of AMIA Natural Language Processing (NLP) Working Group.
Zhongheng Zhang, PhD
Associate Professor, Department of Emergency Medicine
Sir Run Run Shaw Hospital, Zhejiang University School of Medicine
Zhejiang, China
Zhongheng's research programme aims to enable precision treatment for critically ill adults, with the hypothesis that gene expression profiles generate clinical phenotypes and such networks could be determined by integration of clinical and multi-omics data, such as those from RNA-seq and electronic healthcare records. Machine learning algorithms such reinforcement learning, supervised and unsupervised learning can help to discover new knowledge and give more insights into precise medicine.
S Kevin Zhou, PhD
University of Science and Technology of China
Suzhou, China
S Kevin Zhou is a Professor in the University of Science and Technology of China, where he serves as an Executive Dean for School of Biomedical Engineering and directs the Center for Medical Imaging, Robotics, Analytic Computing & Learning (MIRACLE). He is dedicated to research on medical image computing and its applications in real healthcare practices. He has been elected as a fellow of AIMBE, IAMBE, IEEE, MICCAI, and NAI.
Founding Editors and Scientific Advisors
Steven R. Steinhubl, MD
Scripps Research Translational Institute
CA, USA
Steve Steinhubl's research activities have covered a broad range of topics in cardiology, with a primary early focus on trials of novel antithrombotic therapies for the treatment and prevention of cardiovascular disease, and more recently on the application of an integrated systems-based approach to the optimal identification, communication and treatment of an individual's risk for various manifestations of cardiovascular disease. He has been principal investigator or helped lead over a dozen large-scale, international randomized trials.
Eric Topol, MD
Scripps Research Translational Institute
CA, USA
Eric Topol is a practicing cardiologist at Scripps in La Jolla, California, and is widely credited for Cleveland Clinic's status as the leading center for heart care. Dr. Topol leads the flagship NIH supported Scripps Research Translational Institute and is a co-Founder of the West Wireless Health Institute. His research focus is on individualized medicine, using the genome and digital technologies to understand each person at the biologic, physiologic granular level to determine appropriate therapies and prevention. He has pioneered the development of many medications that are routinely used in medical practice including t-PA, Plavix, Angiomax and ReoPro and was the first physician to raise safety concerns on Vioxx.
News and Views Editors
Stephen Gilbert, PhD
Professor of Medical Device Regulatory Science
Else Kröner Fresenius Center for Digital Health, Dresden University of Technology
Dresden, Germany
Professor Gilbert worked in MedTech and Digital Heath roles in industry for 5 years, before returning to academia in 2022 in Dresden, Germany, where he teaches and conducts research. His research goals focus on the advancement of regulatory science in digital medicine and AI-enabled medical devices. Stephen believes that innovative digital approaches in healthcare must be accompanied by innovative oversight approaches to ensure speed to market, to maximise the access of patients to life saving treatments while at the same time ensuring safety on market.
Dylan Powell, PhD
Assistant Professor (Lecturer) Public Health & Innovation
Faculty of Health Sciences & Sport, University of Stirling
Stirling, Scotland
Dylan Powell is an Assistant Professor (Lecturer) in Public Health & Innovation at the University of Stirling within the faculty of Health Sciences & Sport. Dylan’s professional background as a clinician (Physiotherapist) and researcher has spanned the NHS, academia, professional sport, and within industry. His PhD in Computer Science explored the use of wearables and digital biomarkers in neurological conditions including Sports-Related Concussion. Dylan was previously a researcher and knowledge sharing lead for the UK Deloitte Clinical Network.
Advisory Editor
Lorenzo Righetto, PhD
Lorenzo studied Environmental Engineering at Politecnico di Milano, but was then involved in research in infectious diseases modelling during his PhD at EPFL, in Andrea Rinaldo’s group. He was also a postdoc at Politecnico di Milano (with Marino Gatto and Renato Casagrandi) and Human Technopole (with Fabio Pammolli), where he also worked more broadly in areas related to data science and healthcare, with a focus on pharmaceutical R&D. He joined Nature Communications as their digital medicine editor in January 2020 and has taken the same role at Nature Medicine, starting in December 2022
Communications Editor
Benjamin Mazer, MD, MBA
Johns Hopkins University
Baltimore, MD, USA
Dr. Benjamin Mazer is an assistant professor and practicing surgical/gastrointestinal pathologist at Johns Hopkins. His professional interests include cancer screening and overdiagnosis, evidence-based medicine, and health policy. He is also a freelance journalist writing about medical topics and controversies for the public.
Editorial Board Members
Karthik Adapa, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Rima Arnaout, University of California, San Francisco, CA, USA
Rong-Min Baek, Seoul National University, Seoul, South Korea
Pardis Biglarbeigi, University of Dundee, Dundee, Scotland, UK
Raymond Bond, Ulster University, Ulster, United Kingdom
Varun Buch, Microsoft, CA, USA
Yvonne Chan, Unaffiliated, NY, USA
Chun-Wang Chau, The University of Hong Kong, Hong Kong
George DeCherney, University of North Carolina, Chapel Hill, NC, USA
Maarten De Vos, KU Leuven, Leuven, Belgium
Patrick Desgranges, Scripps Health, CA, USA
Dewar Darren Finlay, Ulster University, Belfast, Northern Ireland, UK
Sara Gerke, Dipl.-Jur. Univ., M.A., Penn State Dickinson Law, Carlisle, PA, USA
Pietro Hiram Guzzi, Magna Graecia University, Catanzaro, Italy
Dean Ho,The Institute for Digital Medicine (WisDM); The N.1 Institute for Health (N.1); and Department of Biomedical Engineering, National University of Singapore, Singapore
Sabeena Jalal, University of British Columbia, Vancouver, Canada
Maciej Kos, Center for Cognitive and Brain Health, Northeastern University, Boston, MA, USA
Jethro Kwong, Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada
Kwang-il Kim, Seoul National University, Seoul, South Korea
Santosh Kumar, The University of Memphis, TN, USA
Andrea Laboni, University of Toronto, Canada
Kris Laukens, University of Antwerp, Antwerp, Belgium
Xiaomeng Li, The Hong Kong University of Science and Technology, Hong Kong SAR
Ari Lightman, Carnegie Mellon University, PA, USA
Hongfang Liu, Mayo Clinic, MN, USA
Nan Liu, Duke-NUS Medical School, National University of Singapore, Singapore
Jayson S Marwaha, Harvard Medical School, Boston, MA, USA
Lara Mangravite, Sage Bionetworks, WA, USA
Valentina Mantua, US Food and Drug Administration, Silver Springs, MD, USA
Yosra Mekki, University of Oxford, Oxford, United Kingdom
Donna Spruijt-Metz, University of Southern California, CA, USA
Veena Misra, North Carolina State University, NC, USA
Andrew R. J. Mitchell, Oxford University Hospital and Jersey General Hospital, Jersey, UK
Mirja Mittermaier, Charité - Universitätsmedizin Berlin, Berlin, Germany
Esmaeil Nadimi, University of Southern Denmark, Odense, DK
Camille Nebeker, University of California, CA, USA
Jeffery Olgin, University of California San Francisco School of Medicine, CA, USA
Andrey Ostrovsky, Children's National Medical Center, Washington D.C., USA
Lav Parshottambhai Patel, Office of the Chief Research Information at University of Kansas Medical Center, KS, USA
Niels Peek, University of Manchester, Manchester, United Kingdom
Sanjay Purkayastha, Imperial College, London, London, UK
Giorgio Quer, Scripps Research Translational Institute, CA, USA
Emma Rich, University of Bath, Bath, UK
Hojjat Salmasian, Childrens Hospital of Philadelphia, PA, USA
Emre Sezgin, Ohio State University, OH, USA
Md Mobashir Hasan Shandhi, Duke University, Durham, NC, USA
Stanley Y. Shaw, Harvard Medical School, MA, USA
Vivek Shetty, University of California Los Angeles, CA, USA
Dimitris Spathis, Google Research, UK & University of Cambridge, UK
Brennan Spiegel, Cedars-Sinai Medical Center, CA, USA
Zachary H Strasser, Harvard Medical School, MA, USA
Kaushik P Venkatesh, Harvard Medical School, MA, USA
Shyam Visweswaran, University of Pittsburgh School of Medicine, PA, USA
Joseph Wang, University of California San Diego, CA, USA
Ryan Van Wert, Stanford University, CA, USA
Robyn Whittaker, University of Auckland, Auckland, New Zealand
Kavishwar Wagholikar, Massachusetts General Hospital, Harvard Medical School, Boston, USA
Brenda K. Wiederhold, Virtual Reality Medical Center, CA, USA
Jonghye Woo, Massachusetts General Brigham and Harvard Medical School, Boston, MA, USA
Jiancheng Yang, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
Zhichao Zhang, Apple Inc., California, USA
Karen Zhou, Northeastern University, MA, USA
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