School of Medicine
Showing 1-50 of 152 Results
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Russ B. Altman
Kenneth Fong Professor and Professor of Bioengineering, of Genetics, of Medicine (General Medical Discipline), of Biomedical Data Science and, 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
Research Scientist, Med/BMIR
BioAlison Callahan is a research scientist in the Center for Biomedical Informatics and a member of the Shah Lab. Her work involves research and development of informatics methods for the analysis of biomedical and clinical data, to derive insights and inform medical decision making.
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. -
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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Elizabeth (Liz) Chin
Ph.D. Student in Biomedical Informatics, admitted Autumn 2017
Stanford Stdnt Employee-Summer, Medicine - Med/PCORBioI am a PhD candidate in the Department of Biomedical Data Science at Stanford University, advised by Euan Ashley and Trevor Hastie. The overarching goal of my research is to create targeted interventions to aid medically vulnerable and marginalized populations to prevent poor health outcomes and the social determinants of these outcomes. My work centers around integrating data from disparate sources using a variety of quantitative approaches such as machine learning, simulations, and inference.
My research was generously funded by the National Science Foundation Graduate Fellowship and Stanford Graduate Fellowship. Previously, I obtained my BS in Applied Mathematics at UCLA, where I worked with Xinshu (Grace) Xiao. I have also worked under the guidance of Rachel Martin, Carter Butts, and Pardis Sabeti, and as a machine learning scientist at Adobe Systems and Quora.
If you’re interested in my work or share interests, don’t hesitate to reach out. I am also on the 2021-2022 academic job market. You can contact me at etchin at stanford.edu or follow me on Twitter.
You can find my most recent information and CV on my website, etchin.github.io. -
Jeff Choi
Masters Student in Biomedical Informatics, admitted Autumn 2020
Resident in Surgery - General SurgeryBioGeneral Surgery Resident (2017-) in professional development time. MS in Epidemiology & Clinical Research (2019-2020), and Biomedical Informatics (2020-). Ex-president of SWAT (Surgeons Writing About Trauma). My main research focus is using various machine learning algorithms to develop explainable, practical, and useful prediction tools.
My passions:
1) Re-evaluating dogma with data
2) Reducing the data to bedside gap
3) Fostering collaboration among the next generation of surgeon-data scientists -
Deendayal Dinakarpandian
Clinical Associate Professor, Medicine - Biomedical Informatics Research
Current Research and Scholarly InterestsMethod development and insightful informatics based on my training as a physician, biochemist and computer scientist: Methods for representing, capturing and integrating emerging or expert biomedical knowledge to improve computational predictions of biological and clinical relevance. Methods for evaluating predictions based on machine learning. Interventional and causal predictions. Informatics research on problems in oncology, radiology and allergy/immunology.
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Norman Downing
Clinical Assistant Professor, Medicine - Biomedical Informatics Research
BioI am a faculty member in Biomedical Informatics Research at Stanford and board-certified internal medicine and clinical informatics. I split my time between clinical practice, hospital medical informatics and applications of artificial intelligence in healthcare. I work with the Clinical Excellence Research Center – a research group dedicated to reducing the cost of high-quality care – directing the Partnership in AI collaboration with the Stanford Artificial Intelligence Lab. Recognizing that the complexity of medicine has grown beyond the abilities of even the most expert clinician, we focus applications of computer vision to address some of the greatest challenges in healthcare: perfecting intended care for frail patients in settings ranging from the intensive care unit to the home. 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 interests include a design-based approach to understand how technology has impacted the work of clinicians and implications for new care models, workflow, and technology integration.
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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. -
Claudio Fanconi
Graduate Visiting Researcher Student, Biomedical Informatics
BioI am a Visiting Student Researcher (VSR), doing my Master's thesis in the Boussard Lab at the BMIR. Currently, I am pursuing my MSc in electrical engineering and information technology at ETH Zurich, Switzerland, with a focus on machine learning and signal processing. I hold a BSc in electrical engineering from the same university.
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Sajjad Fouladvand, PhD, MSc
Postdoctoral Scholar, Biomedical Informatics
BioSajjad Fouladvand, PhD, MSc is a postdoctoral scholar at Stanford Center for Biomedical Informatics Research. Dr. Fouladvand's research career thus far has been focused on developing and applying artificial intelligence (AI) algorithms to solve real-world healthcare problems. Prior to Stanford, he worked at the Institute for Biomedical Informatics at the University of Kentucky (UK) while completing his PhD in Computer Science. During this time, he also received training at Mayo Clinic’s Department of Artificial Intelligence and Informatics as an intern.
While at UK as a PhD candidate, he developed a deep learning model based on transformer and Long Short-Term Memory (LSTM) models to analyze multi-stream healthcare data for prediction of opioid use disorder (OUD). While at Mayo Clinic as an intern, he created a LSTM based framework to predict progression from cognitively unimpaired to mild cognitive impairment in an aging population. In his new role at Stanford, Dr. Fouladvand is involved in conducting AI and healthcare data science research in close collaboration with clinicians, scientists, and healthcare systems with access to deep clinical data warehouses and broad population health data sources. -
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 -
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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Mary Kane Goldstein
Professor of Health Policy (PCOR) and, by courtesy, of Medicine (BMIR)
Current Research and Scholarly InterestsHealth services research in primary care and geriatrics: developing, implementing, and evaluating methods for clinical quality improvement. Current work includes applying health information technology to quality improvement through clinical decision support (CDS) integrated with electronic health records; encoding clinical knowledge into computable formats in automated knowledge bases; natural language processing of free text in electronic health records; analyzing multiple comorbidities
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John Graybeal
Rsch Technical Mgr 2, Med/BMIR
Current Role at StanfordJohn is a Technical Program Manager at Stanford University's School of Medicine. He leads the Center for Enhanced Data Annotation and Retrieval (CEDAR), and the NCBO BioPortal Repository, .
John's work encompasses whatever is needed: project management, product management, systems architecture, dev ops, and administration, to name a few fun roles.
