School of Medicine
Showing 1-90 of 90 Results
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Russ B. Altman
Kenneth Fong Professor and Professor of Bioengineering, of Genetics, of Medicine, of Biomedical Data Science, Senior Fellow at the Stanford Institute for HAI and Professor, by courtesy, of Computer Science
Current Research and Scholarly InterestsI refer you to my web page for detailed list of interests, projects and publications. In addition to pressing the link here, you can search "Russ Altman" on http://www.google.com/
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Alison Callahan
Instructor, Medicine - Biomedical Informatics Research
BioAlison Callahan is an Instructor in the Center for Biomedical Informatics and Clinical Data Scientist in the Stanford Health Care Data Science team led by Nigam Shah. Her current research uses informatics to expand and improve the data available about pregnancy and birth, and to develop and maintain and EHR-derived obstetric database. She is also the co-leader of the OHDSI Perinatal & Reproductive Health (PRHeG) working group. Her work in the SHC Data Science team focuses on developing and implementing methods to assess and identify high value applications of machine learning in healthcare settings.
Alison completed her PhD in the Department of Biology at Carleton University in Ottawa, Canada. Her doctoral research focused on developing HyQue, a framework for representing and evaluating scientific hypotheses, and applying this framework to discover genes related to aging. She was also a developer for Bio2RDF, an open-source project to build and provide the largest network of Linked Data for the life sciences. Her postdoctoral work at Stanford applied methodologies developed during her PhD to study spinal cord injury in model organisms and humans in a collaboration with scientists at the University of Miami. -
Jonathan H. Chen, MD, PhD
Assistant Professor of Medicine (Biomedical Informatics)
Current Research and Scholarly InterestsInformatics solutions ares the only credible approach to systematically address challenges of escalating complexity in healthcare. Tapping into real-world clinical data streams like electronic medical records will reveal the community's latent knowledge in a reproducible form. Delivering this back as clinical decision support will uniquely close the loop on a continuously learning health system.
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Henry C. Cousins
MD Student, expected graduation Spring 2024
Ph.D. Student in Biomedical Informatics, admitted Autumn 2021
MSTP StudentBioHenry is an MD-PhD candidate and Knight-Hennessy Scholar in the Medical Scientist Training Program and the Biomedical Informatics Program, where he is advised by Professor Russ Altman. He develops machine-learning methods to study the effects of complex genetic variation on human disease mechanisms, with focus on neurological and ophthalmic disorders. His goal is to translate genomic discoveries into disease-modifying therapies.
He received an AB summa cum laude from Harvard University in 2017, where he studied genetic mechanisms of retinal development with Professor Joshua Sanes. He then graduated with an MPhil with distinction from the University of Cambridge as a Gates Cambridge Scholar. He previously worked at Leaps by Bayer and the Massachusetts Eye and Ear Infirmary and has received a number of awards related to research and teaching. -
N. Lance Downing
Clinical Assistant Professor, Medicine - Biomedical Informatics Research
BioI am board-certified internal medicine and clinical informatics. I am a primary care physician and teaching hospitalist. I have published work in the New England Journal of Medicine, Health Affairs, Annals of Internal Medicine, and the Journal of the American Medical Informatics Association. My primary focus throughout my career has been to deliver personalized and compassionate care that incorporates the latest advancements in medical science. I aim to help all of my patients maximize their healthspan and age with the best quality of life possible.
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Matthew A. Eisenberg
Clinical Assistant Professor (Affiliated), Med/BMIR
BioDr. Matthew A. Eisenberg joined Stanford Health Care in early 2013 and is the Medical Informatics Director for Analytics & Innovation with a focus on interoperability and health information exchange, regulatory reporting, health care analytics, patient reported outcomes and other uses of technology to meet our strategic initiatives.
Dr. Eisenberg is board certified in Pediatrics and Clinical Informatics. He is a Clinical Assistant Professor (Affiliated) in the Stanford Center for Biomedical Informatics Research at the Stanford University School of Medicine and he serves as the Stanford Health Care site director for the Stanford Clinical Informatics Fellowship Program. He previously held the position of Clinical Assistant Professor in Pediatrics at the University of Washington School of Medicine. He is a current member of the eHealth Exchange Coordinating Committee, a Sequoia Project Board member and serves as the current chair of the Epic Care Everywhere Network Governing Council. He is a member of the Carequality Advisory Council (past co-chair) and a member of IHE USA Implementation Committee. He is a Fellow of the American Academy of Pediatrics and a member of the American Medical Informatics Association and their Clinical Informatics Community. -
Jason Fries
Research Engineer, Med/BMIR
Current Role at StanfordI'm currently working as a staff research scientist in the Shah Lab and research scientist at Snorkel AI. My interests fall in the intersection of computer science and medical informatics. My research interests include:
• Machine learning with limited labeled data, e.g., weak supervision, self-supervision, and few-shot learning.
• Multimodal learning, e.g., combining text, imaging, video and electronic health record data for improving clinical outcome prediction
• Human-in-the-loop machine learning systems.
• Knowledge graphs and their use in improving representation learning -
Andrew Gentles
Assistant Professor (Research) of Pathology, of Medicine (BMIR) and, by courtesy, of Biomedical Data Science
Current Research and Scholarly InterestsComputational systems biology
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Olivier Gevaert
Associate Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
Current Research and Scholarly InterestsMy lab focuses on biomedical data fusion: the development of machine learning methods for biomedical decision support using multi-scale biomedical data. We primarily use methods based on regularized linear regression to accomplish this. We primarily focus on applications in oncology and neuroscience.
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Summer Han
Associate Professor (Research) of Neurosurgery, of Medicine (Biomedical Informatics) and, by courtesy, of Epidemiology and Population Health
Current Research and Scholarly InterestsMy current research focuses on understanding the genetic and environmental etiology of complex disease and developing and evaluating efficient screening strategies based on etiological understanding. The areas of my research interests include statistical genetics, molecular epidemiology, cancer screening, health policy modeling, and risk prediction modeling. I have developed various statistical methods to analyze high-dimensional data to identify genetic and environmental risk factors and their interactions for complex disease.
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Josef Hardi
Software Dvlpr 3, Med/BMIR
BioI'm a software engineer with a keen interest in data science. I have over 10 years’ experience in software development and 5 years in the data processing. Currently, I work as a backend developer for the Stanford Center of Biomedical Informatics Research; tackling issues in data and metadata management and interoperability. I also actively engage in the work of converting health and claim records to the OMOP common data model as part of my collaboration with the Stanford Population Health Sciences. I have experience with Java, Python, R, RDF, OWL, OBDA, Schema.org and Elasticsearch.
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Zihuai He
Assistant Professor (Research) of Neurology (Neurology Research Faculty), of Medicine (BMIR) and, by courtesy, of Biomedical Data Science
Current Research and Scholarly InterestsStatistical genetics and other omics to study Alzheimer's disease.
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Tina Hernandez-Boussard
Professor of Medicine (Biomedical Informatics), of Biomedical Data Science, of Surgery and, by courtesy, of Epidemiology and Population Health
Current Research and Scholarly InterestsMy background and expertise is in the field of computational biology, with concentration in health services research. A key focus of my research is to apply novel methods and tools to large clinical datasets for hypothesis generation, comparative effectiveness research, and the evaluation of quality healthcare delivery. My research involves managing and manipulating big data, which range from administrative claims data to electronic health records, and applying novel biostatistical techniques to innovatively assess clinical and policy related research questions at the population level. This research enables us to create formal, statistically rigid, evaluations of healthcare data using unique combinations of large datasets.
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Zepeng Huo
Postdoctoral Scholar, Biomedical Informatics
BioConducting research on Foundation Models for medicine
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Jenelle Asha Jindal
Affiliate, Med/BMIR
BioDr. Jenelle Jindal is a physician who believes in bringing well designed technology into healthcare. She has spent years in the healthcare system practicing medicine, as well as in hospital leadership roles and in government during the pandemic. She is a graduate of Stanford University, Yale School of Medicine, and completed residency and fellowship at the Harvard hospitals of Mass General and Brigham & Womens.
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Detailed Bio
Dr. Jenelle Jindal has experience as an operator within the healthcare system, serving as medical director at El Camino Hospital in Silicon Valley launching telestroke and 24/7/365 thrombectomy care. Subsequently the hospital was recognized by the Joint Commission with a new higher level of Thrombectomy Capable Certification. She also completed a tour of duty helping in the Emergency Operations Center of Santa Clara County during the COVID-19 pandemic assisting with antigen testing deployment and increasing vaccination uptake.
She is also an experienced neurologist, caring for thousands of patients as a practicing physician. Her clinical focus has included treating strokes, brain hemorrhage, epilepsy, and neurodegenerative disease in the emergency room, ICU, and hospital wards. She was founder and CEO running a private medical practice for nearly 7 years and served as a Medical Advisory Board member of the Pacific Stroke Association.
LinkedIn: www.linkedin.com/in/jenellejindal/ -
Teri Klein
Professor (Research) of Biomedical Data Science, of Medicine (BMIR) and, by courtesy, of Genetics
Current Research and Scholarly InterestsCo-founder, Pacific Symposium on Biocomputing
NIEHS, Site Visit Reviewer
NIH, Study Section Reviewer -
Curtis Langlotz
Professor of Radiology (Thoracic Imaging), of Biomedical Informatics Research, of Biomedical Data Science and Senior Fellow at the Stanford Institute for HAI
Current Research and Scholarly InterestsI am interested in the use of deep neural networks and other machine learning technologies to help radiologists detect disease and eliminate diagnostic errors. My laboratory is developing deep neural networks that detect and classify disease on medical images. We also develop natural language processing methods that use the narrative radiology report to create large annotated image training sets for supervised machine learning experiments.
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Tushar Mungle
Postdoctoral Scholar, Biomedical Informatics
Current Research and Scholarly InterestsUse electronic health records (EHRs) to identify and classify common ocular diseases such as glaucoma, diabetic retinopathy, and macular degeneration. We aim to develop an approach to accurately identify these conditions using EHRs. This will be followed by cluster analysis to identify novel subtypes of these conditions that have not been recognized before. Finally, we will develop an approach to extract outcome data from EHRs for patients with these conditions in the primary care setting.
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Mark Musen
Stanford Medicine Professor of Biomedical Informatics Research, Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
Current Research and Scholarly InterestsModern science requires that experimental data—and descriptions of the methods used to generate and analyze the data—are available online. Our laboratory studies methods for creating comprehensive, machine-actionable descriptions both of data and of experiments that can be processed by other scientists and by computers. We are also working to "clean up" legacy data and metadata to improve adherence to standards and to facilitate open science broadly.
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Fateme Nateghi Haredasht
Postdoctoral Scholar, Biomedical Informatics
BioAs a postdoctoral scholar at the Stanford Center for Biomedical Informatics Research, I find myself at the exciting intersection of machine learning and healthcare. My journey began with a PhD in Biomedical Sciences from KU Leuven in Belgium, where I delved into the complexities of machine learning algorithms and their transformative potential in healthcare settings. My research, particularly focused on adapting these algorithms for time-to-event data (a method used for predicting specific events in a patient’s future), has not only been a challenging endeavor but also a deeply fulfilling one.
Now at Stanford, my role involves not just advancing machine learning integration in healthcare, but also collaborating with a diverse team of experts. Together, we're striving to unravel complex healthcare challenges and improve patient outcomes. -
Madelena Ng
Postdoctoral Scholar, Biomedical Informatics
BioDr. Ng is a postdoctoral fellow at the Stanford Center for Biomedical Informatics Research, mentored by Dr. Tina Hernandez Boussard. Her research aims to illuminate the evolving ethical and practical challenges with emerging technologies used for health purposes. Prior to joining Stanford, Dr. Ng facilitated mobile- and internet-based health research initiatives with the Health eHeart Study and the Eureka Digital Research Platform and developed research study prototypes that used blockchain technology for health data exchange. Her current work focuses on discerning key challenges that exist at each stage of the AI life cycle and generating informed guidance to drive the responsible and equitable use of AI for patient care.
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Minh Nguyen
Ph.D. Student in Biomedical Informatics, admitted Autumn 2018
Ph.D. Minor, Management Science and EngineeringBio@DARE fellow (Diversifying Academia, Recruiting Excellence) https://vpge.stanford.edu/people/minh-nguyen
@Data Science Scholar
https://datascience.stanford.edu/people/minh-nguyen -
Justin Norden, MD, MBA, MPhil
Adjunct Professor, Med/BMIR
BioDr. Justin Norden is an Adjunct Professor at Stanford Medicine in the Department of Biomedical Informatics Research. He teaches courses on digital health and AI in Medicine. His research focuses on AI in healthcare, digital health, and care system transformation.
Additionally, Dr. Norden is a Partner at GSR Ventures where he focuses on early-stage investments in digital health and AI/ML in healthcare. Prior to GSR Ventures, Dr. Norden was founder and CEO of Trustworthy AI which was acquired by Waymo (Google Self-Driving). He worked on the healthcare team at Apple, co-founded Indicator (an NLP based platform for biopharma decision making), and helped start the Stanford Center for Digital Health.
Dr. Norden received an MD from Stanford University School of Medicine, where he served as student body president. An MBA from the Stanford Graduate School of Business, where he served as president of the healthcare club. An M.Phil in Computational Biology with distinction from the University of Cambridge, and a BA in Computer Science with distinction from Carleton College.
Finally, he is a professional athlete for the Oakland Spiders (ultimate frisbee) - holding the team all-time records for assists and completions. He is a 3x World Champion, 1x professional champion, former Team USA Captain (U24), and D1 University National Champion. -
Natalie Pageler
Clinical Professor, Peds/Clinical Informatics
Clinical Professor, Medicine - Biomedical Informatics ResearchCurrent Research and Scholarly InterestsIn my administrative role, I oversee the development and maintenance of clinical decision support tools within the electronic medical record. These clinical decision support tools are designed to enhance patient safety, efficiency, and quality of care. My research focuses on rigorously evaluating--1) how these tools affect clinician knowledge, attitudes, and behaviors; and 2) how these tools affect clinical outcomes and efficiency of health care delivery.
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Jonathan P. Palma
Clinical Professor, Medicine - Biomedical Informatics Research
Current Research and Scholarly InterestsInterventional informatics to achieve examples of a learning healthcare system; optimization of commercial EMRs to support complex clinical workflows in newborn intensive care; clinical decision support; real-time clinical dashboards; electronic sign-out tools; IT-supported patient/family communication.
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Malvika Pillai
Postdoctoral Scholar, Biomedical Informatics
BioMalvika Pillai is a postdoctoral research fellow in the VA Big Data Scientist Training Enhancement Program (BD-STEP), jointly in Stanford University in Medicine (Biomedical Informatics) in the Boussard Lab and VA Palo Alto. She received her BS in Quantitative Biology and PhD in Health Informatics from the University of North Carolina at Chapel Hill. Her current work focuses on the development, evaluation and implementation of machine learning algorithms for clinical decision support.
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Daniel Rubin
Professor of Biomedical Data Science, of Radiology (Integrative Biomedical Imaging Informatics at Stanford), of Medicine (Biomedical Informatics Research) and, by courtesy, of Ophthalmology
Current Research and Scholarly InterestsMy research interest is imaging informatics--ways computers can work with images to leverage their rich information content and to help physicians use images to guide personalized care. Work in our lab thus lies at the intersection of biomedical informatics and imaging science.
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Sina Sadeghzadeh
MD Student with Scholarly Concentration in Clinical Research, expected graduation Spring 2026
Masters Student in Medicine, admitted Spring 2024BioSina was born in Tehran, Iran and raised in Zanjan, Iran. He came out to Massachusetts to attend Harvard University where he obtained his undergraduate degree cum laude in Neuroscience with a secondary in Economics. In college, Sina conducted wet-lab research under the supervision of Dr. Hugo Bellen, worked as a legal intern in Levy Firestone Muse LLP, and served as a research assistant for Drs. Francis Shen, Steven Levitsky, and Jennifer Hochschild. Sina moved to California (by bike!) to begin medical school at Stanford where he is currently pursuing clinical and basic science research opportunities in the neuroscience domain. Outside of medical school, Sina is an avid cyclist, enjoys going on walks, doing yoga, and learning to salsa dance.
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Thomas Robert Savage
Clinical Assistant Professor, Medicine
Masters Student in Biomedical Informatics, admitted Autumn 2022BioDr Thomas Savage is a Hospitalist at Stanford University Hospital. He teaches residents and medical students on the general medicine service as well as covers the oncology, cardiology and transplant services as a nocturnist. His research interests include artificial intelligence applications to medicine and wearable medical devices.
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Nigam H. Shah, MBBS, PhD
Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
Current Research and Scholarly InterestsWe analyze multiple types of health data (EHR, Claims, Wearables, Weblogs, and Patient blogs), to answer clinical questions, generate insights, and build predictive models for the learning health system.