PRISM supports all faculty in recruiting postdocs. The faculty listed on this page have expressed special interest in the PRISM program and most are actively recruiting. As you look for potential postdoc mentors, consider how faculty research interests align with your own.
For an overview of how the Faculty Nomination/Selection process works, please view our Stanford PRISM Faculty Guide.
As a rule of thumb, we recommend starting with the faculty listed on this page and then expanding your search to other faculty across the university. This is not intended to be a comprehensive list of all faculty eligible to appoint postdocs through PRISM.
For School of Medicine faculty, browse SoM Departments or find details about individual faculty members in the School of Medicine via Community Academic Profiles (CAP).
For faculty outside of the School of Medicine, browse departments in the Natural Sciences, Earth Sciences, or Engineering and find details about individual faculty members in these areas via Stanford Profiles.
Please check back often -- Faculty/Lab profiles may be added or edited throughout the application period.
PRISM mentor | Research Interests |
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Katherine Ferrara Radiology
Last Updated: June 06, 2022 |
Katherine Whittaker Ferrara is a Professor of Radiology and the Division Chief for the Molecular Imaging Program at Stanford. She is a member of the National Academy of Engineering and a fellow of the IEEE, American Association for the Advancement of Science, the Biomedical Engineering Society, the World Molecular Imaging Society, the Acoustical Society of America and the American Institute of Medical and Biological Engineering. Dr. Ferrara received her Ph.D. in 1989 from the University of California, Davis. Prior to her PhD, Dr. Ferrara was a project engineer for General Electric Medical Systems, involved in the development of early magnetic resonance imaging and ultrasound systems. Following an appointment as an Associate Professor in the Department of Biomedical Engineering at the University of Virginia, Charlottesville, Dr. Ferrara served as the founding chair of the Department of Biomedical Engineering at UC Davis. Her laboratory is known for work in molecular imaging and drug delivery.
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Jeremy Heit Radiology
Last Updated: July 13, 2022 |
Dr. Jeremy Heit is a neurointerventional surgeon (neurointerventional radiologist) who specializes in treating stroke, brain aneurysms, brain arteriovenous malformations, brain and spinal dural arteriovenous fistulae, carotid artery stenosis, vertebral body compression fractures, and congenital vascular malformations. Dr. Heit treats all of these conditions using minimally-invasive, image-guided procedures and state-of-the-art technology. |
Craig Levin Radiology, Physics, Electrical Engineering, Bioengineering, Radiology-MIPS, Stanford Cancer Center, Cardiovascular Med Institute, Neuroscience Institute
Last Updated: March 16, 2022 |
The research interests of the molecular imaging instrumentation lab are to create novel instrumentation and software algorithms for in vivo imaging of molecular signatures of disease in humans and small laboratory animals. These new cameras efficiently image radiation emissions in the form of positrons, annihilation photons, gamma rays, and/or light emitted from molecular contrast agents that were introduced into the body and distributed in the subject tissues. These contrast agents are designed to target molecular pathways of disease biology and enable imaging of these biological signatures in tissues residing deep within the body using measurements made from outside the body. The goals of the instrumentation projects are to advance the sensitivity and spatial, spectral, and/or temporal resolutions, and to create new camera geometries for special biomedical applications. The computational modeling and algorithm goals are to understand the physical system comprising the subject tissues, radiation transport, and imaging system, and to provide the best available image quality and quantitative accuracy. The work involves designing and building instrumentation, including arrays of position sensitive sensors, readout electronics, and data acquisition electronics, signal processing research, including creation of computer models, and image reconstruction, image processing, and data/image analysis algorithms, and incorporating these innovations into practical imaging devices. The ultimate goal is to introduce these new imaging tools into studies of molecular mechanisms and treatments of disease within living subjects.
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Sandy Napel Radiology
Last Updated: June 06, 2022 |
The practice of Radiology is undergoing a radical transformation from one in which the primary result of an imaging examination is a written report addressing the reasons that the examination was ordered, to one in which the output is a (set of) quantitative measurement(s) with links to knowledge that could affect treatment. For example, while a traditional report might have said “there is a mass in the right upper lobe of the lung,” the report of the future might say “The mass in the right upper lobe of the lung has grown by 25% since the last examination 3 months ago; it now measures 60 cc and has imaging features consistent with adenocarcinoma with an EGFR mutation that has has a favorable response to TK inhibitors. Click these links for similar cases and their clinical history. See references [1-4] for the latest articles of relevance.” Our lab, in collaboration with other IBIIS labs, radiologists, and other clinicians, and other collaborators from the School of Medicine, is involved in many aspects of creating that future, including advanced software for image visualization and quantitative analysis, image segmentation software that isolates regions within images for further analysis, software that extracts imaging features (e.g., shape, size, margin sharpness, pixel texture) within these regions, and algorithms for computing similarity between images and between patients as expressed by their images, demographic and clinical data.
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Sharon Pitteri Radiology
Last Updated: November 11, 2021 |
The Pitteri laboratory uses mass spectrometry to identify, quantify, and characterize proteins in complex biological and clinical samples. We are focused on using proteins and their post-translational modifications to better understand biology and to answer clinical problems in health and disease states. Currently, a main focus of the lab is developing and implementing new methods to study protein glycosylation in cancer. |
Daniel Rubin Biomedical Data Sciences, Radiology, Biomedical Informatics
Last Updated: August 17, 2020 |
The QIAI lab focuses on cutting‐edge research at the intersection of imaging science and biomedical informatics, developing and applying AI methods to large amounts of medical data for biomedical discovery, precision medicine, and precision health (early detection and prediction of future disease). The lab develops novel methods in text and image analysis and AI, including multi-modal and multi-task learning, weak supervision, knowledge representation, natural language processing, and decision theory to tackle the challenges of leveraging medical Big Data. Our exciting work is bridging a spectrum of biomedical domains with multidisciplinary collaborations with top scientists at Stanford as well as with other institutions internationally. The QIAI lab provides a unique multidisciplinary environment for conducing innovative AI-based healthcare research with a strong record of scholarly publication and achievement. Core research topics in the laboratory include: (1) automated image annotation using unsupervised methods of processing associated radiology reports using word embeddings and related methods; (2) developing methods of analyzing longitudinal EMR data to predict clinical outcomes and best treatments, (3) creating multi-modal deep learning models integrating multi-dimensional EMR and other data to discover electronic phenotypes of disease, (4) developing AI models with noisy or sparse labels (weak supervision), and cross-modal, multi-task learning, and observational AI approaches, and (5) developing and implementing algorithms for distributed computation for training deep learning models that leverage multi-institutional data while avoiding the barriers to data sharing.
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Mirabela Rusu Radiology
Last Updated: August 11, 2020 |
Dr. Mirabela Rusu directs the Laboratory for Integrative Personalized Medicine (PIMed), which is part of the School of Medicine, Department of Radiology, Division of Integrative Biomedical Imaging Informatics. PIMed focuses on developing deep learning methods for radiology-pathology integration and to characterize the appearance of diseases on radiology images using the pathology information. Such integrative methods may be applied to create comprehensive multi-scale representations of biomedical processes and pathological conditions, thus enabling their in-depth characterization and the identification of imaging signatures of pathologic conditions. Our team extensively studies the appearance of prostate cancer on MRI, but also works on breast cancers as well as non-oncologic applications. |
Mirabela Rusu Radiology, HumanCentered Artificial Inte
Last Updated: January 12, 2022 |
The PIMed Laboratory has a multi-disciplinary direction and focuses on developing analytic methods for biomedical data integration, with a particular interest in radiology-pathology fusion to facilitate radiology image labeling . The radiology-pathology fusion allows the creation of detailed spatial labels, that later on can be used as input for advanced machine learning, such as deep learning. The recent focus of the lab has been on applying deep learning methods to detect and differentiate aggressive from indolent prostate cancers on MRI using the pathology information (both labels and the image content). Other applications include breast cancer and brain samples.
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Mirabela Rusu Radiology
Last Updated: November 29, 2021 |
The Laboratory for Integrative Personalized Medicine (PIMed) is directed by Dr. Mirabela Rusu, PhD, and is part of the School of Medicine, Department of Radiology, Division of Integrative Biomedical Imaging Informatics at Stanford University. The PIMed Laboratory has a multi-disciplinary direction and focuses on developing analytic methods for biomedical data integration, with a particular interest in radiology-pathology fusion to facilitate radiology image labeling . Such integrative methods may be applied to create comprehensive multi-scale representations of biomedical processes and pathological conditions, thus enabling their in-depth characterization. The radiology-pathology fusion allows the creation of detailed spatial labels, that later on can be used as input for advanced machine learning, such as deep learning. PIMed closely collaborates with the Urologic Cancer Innovation Lab at Stanford for the prostate cancer work.
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Dan Spielman Radiology
Last Updated: July 14, 2022 |
Dr. Spielman’s research is in the field of MRI, spectroscopy (MRS), and PET, with a focus on the development of new methods of imaging in vivo metabolism. Current projects include 13C MRS of hyperpolarized substrates for the assessment of glycolysis and oxidative phosphorylation in cancer, 1H MRS measurements brain oxidative stress and neurotransmission, and combined PET/MRS studies. He has focused on a novel array of both acquisition and analysis techniques for use in preclinical and clinical studies.
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Tanya Stoyanova Radiology
Last Updated: July 13, 2022 |
Stoyanova lab is interested in understanding fundamental molecular mechanisms underlying the development of epithelial cancers and their utility as biomarkers and therapeutic targets. Currently, the major focus of our group is in prostate cancer. We are also interested in breast and neuroendocrine cancers. The ultimate goals of the laboratory are to: 1) improve the stratification of indolent from aggressive prostate cancer and 2) guide the development of novel and effective therapeutic strategies for metastatic cancers. |
Shreyas Vasanawala Radiology
Last Updated: July 13, 2022 |
We are seeking a talented individual for a research associate position in our multidisciplinary team. Our advanced pediatric MRI research program spans across novel developments in hardware, pulse sequences, machine learning algorithms, image reconstruction methods, and image analysis techniques, all with an integrated clinical translational component. Efforts bridge across multiple departments on the Stanford University campus and UC Berkeley, as well as with Silicon Valley companies. The position offers the opportunity to work with multiple faculty, post-doctoral scholars, graduate students, and undergraduates. Responsibilities include developing novel techniques, contributing to grant proposals, writing and submitting manuscripts, and developing intellectual property. |
Adam Wang Radiology, Electrical Engineering
Last Updated: July 14, 2022 |
My research interests revolve around the following areas: - Novel systems and methods for x-ray and CT imaging - Applications of x-ray/CT to image-guided interventions and therapy and diagnostic imaging - Dual energy / spectral imaging, including photon counting detectors - Applications of artificial intelligence / machine learning / deep learning to medical imaging - Monte Carlo and Deterministic methods for x-ray imaging and radiation dose - Model-based image reconstruction
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Greg Zaharchuk Radiology
Last Updated: January 12, 2022 |
My research focuses on advanced MRI and PET/MRI techniques and their application to alleviate neurological disease. I lead an inter-disciplinary team of physicians, graduate and post-doctoral students, and research associates with technical expertise in all the required realms to perform successful advanced imaging studies. As an active clinical neuroradiologist, I have a strong track record of integrating advanced imaging methods to clinical patients and have published extensively on its value in a wide range of diseases. During the past several years, I have become convinced that AI generally and deep learning in particular will transform medicine. Radiology will be fundamentally affected. In the area of deep learning, I have demonstrated its use to improve MR reconstruction, reduce MR contrast dose and radiation dose, segmentation of brain metastases, and to predict the future. |
Michael Zeineh Radiology
Last Updated: July 14, 2022 |
My lab focuses on translating advanced MRI into clinical practice. In Alzheimer’s disease, we are investigating the nature of iron deposition to understand how iron interacts with inflammation, amyloid, and tau in the progression of AD. We bring to this disease the full arsenal of imaging: ultra-high resolution MRI of human AD specimens coupled with novel histological methods including x-ray microscopy and electron microscopy. We bring this armamentarium full circle to living human imaging with 7.0T MR and multi-tracer PET-MR. In mild traumatic brain injury, we are studying the imaging signatures of brain insult that occur in high-contact sports using advanced MRI combined with mouthguard accelerometer measurements of impacts. In chronic fatigue syndrome, we are identifying microstructural changes that accompany fatigue and correlate with systemic circulating cytokines that together may form a biomarker for this disorder. |
Michael Zeineh Radiology, Radiology-RSL, Neuroscience Institute
Last Updated: January 29, 2023 |
Dr. Michael Zeineh received a B.S. in Biology at Caltech in 1995 and obtained his M.D.-Ph.D. from UCLA in 2003. After internship also at UCLA, he went on to radiology residency and neuroradiology fellowship both at Stanford. He has been faculty in Stanford Neuroradiology since 2010. He spearheads many initiatives in advanced clinical imaging at Stanford, including clinical fMRI and DTI. Simultaneously, he runs a lab with the goal of discovering new imaging abnormalities in neurodegenerative disorders, with a focus on detailed microcircuitry in regions such as the hippocampal formation using advanced, multi-modal in vivo and ex vivo methods, with applications to neurodegenerative disorders such as Alzheimer’s disease and mild traumatic brain injury.
Specific projects: Ex vivo MRI of iron in Alzheimer’s disease |
Michael Zeineh Radiology
Last Updated: July 14, 2022 |
My lab focuses on translating advanced MRI into clinical practice. In Alzheimer's disease, we are investigating the nature of iron deposition to understand how iron interacts with inflammation, amyloid, and tau in the progression of AD. We bring to this disease the full arsenal of imaging: ultra-high resolution MRI of human AD specimens coupled with novel histological methods including x-ray microscopy and electron microscopy. We bring this armamentarium full circle to living human imaging with 7.0T MR and multi-tracer PET-MR. In mild traumatic brain injury, we are studying the imaging signatures of brain insult that occur in high-contact sports using advanced MRI combined with mouthguard accelerometer measurements of impacts. In chronic fatigue syndrome, we are identifying microstructural changes that accompany fatigue and correlate with systemic circulating cytokines that together may form a biomarker for this disorder. |
Christopher Barnes Biology, Structural Biology
Last Updated: July 22, 2022 |
We combine biophysical methods with in vivo approaches to understand how viruses such as HIV and SARS-CoV-2 infect host cells and elicit specific humoral immune responses. Our research will translate knowledge of the structural correlates of antibody-mediated neutralization of viruses into the rational development of highly protective antibodies. A related goal is the structure-based design of potent and stable immunogens for vaccination. |
Kacper Rogala Structural Biology, Chemical and Systems Biology
Last Updated: June 23, 2022 |
How are nutrients recognized by their protein sensors? How is their transport across cellular and intracellular membranes regulated? And, how is nutrient sensing integrated with other chemical signals, such as hormones, to determine cellular decisions, especially the decision: to grow or not to grow? We are a team of structural and chemical biologists aiming to answer these fundamental questions at the level of ångstroms, nanometers, and micrometers. Many proteins in these pathways are deregulated in cancer, and our mission is to first reveal the mechanism of action of these proteins, and then use that knowledge to develop targeted chemical probes to modulate their activity in cells and organisms. Our lab is friendly to trainees from all walks of life, and we cherish trust, inclusiveness and intellectual curiosity, where no question is too big to study, as long as we have the right approach and a unique angle. Most importantly, our lab operates with a growth mindset for all of our trainees, and we put a heavy emphasis on training and skills development — across a wide range of experimental and computational techniques. And through collaboration, strong work ethic, seeking feedback, and trying out new strategies, we drive innovation and novel discoveries for our team. If this is something you might be interested in, please contact Kacper directly. We are always on the lookout for driven postdocs! Especially, we want cell biologists and biochemists to join our team and to contribute your unique skillsets to a number of collaborative projects. |
Jill Helms Surg: General Surgery
Last Updated: February 24, 2023 |
I am a Professor in the Department of Surgery at Stanford University. I trained as a dentist and have a certificate in Periodontics and a PhD. My lab works in the field of Regenerative Medicine and Dental Medicine, with a focus on the biological and mechanical regulation of tissue repair and regeneration. Our objective has remained unchanged for the last two decades: to make new discoveries that improve patient outcomes.
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Electron Kebebew Surg: General Surgery
Last Updated: July 13, 2022 |
The Endocrine Oncology Research Laboratory is engaged in cutting-edge endocrine and neuroendocrine clinical, translational and basic research. Our research is focused on:
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Todd Wagner Surg: General Surgery
Last Updated: August 13, 2020 |
Health economics, implementation science, access to care, use and effects of consumer health information. Co-director of the NCI/VA Big Data Fellowship. https://www.herc.research.va.gov/include/page.asp?id=bd-step |
James Brooks Urology
Last Updated: March 17, 2022 |
Our interest is in developing diagnostic and prognostic markers for urological diseases. Our work spans discovery, measurement methodologies, and clinical validation of candidate biomarkers. We have primarily used genomic and proteomic approaches for biomarker discovery. While our primary focus has been in prostate cancer, we have also worked in kidney cancer and other malignancies. We are also working to characterize the functional roles of several of the candidate biomarkers in cancer. In the past several years our work has expanded into benign urologic diseases including benign prostatic hyperplasia, obstructive nephropathy, and androgen insensitivity syndrome. In collaboration with bioengineers and radiologists, we have active research in molecular imaging, and protein and nucleotide detection on biological samples. We also participate in several large clinical trials for development, validation and implementation of clinical biomarkers in prostate cancer.
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James Brooks Urology
Last Updated: July 26, 2021 |
Our interest is in developing diagnostic and prognostic markers for urological diseases. Our work spans discovery, measurement methodologies, and clinical validation of candidate biomarkers. We have primarily used genomic and proteomic approaches for biomarker discovery. While our primary focus has been in prostate cancer, we have also worked in kidney cancer and other malignancies. We are also working to characterize the functional roles of several of the candidate biomarkers in cancer. In the past several years our work has expanded into benign urologic diseases including benign prostatic hyperplasia, obstructive nephropathy, and androgen insensitivity syndrome. In collaboration with bioengineers and radiologists, we have active research in molecular imaging, and protein and nucleotide detection on biological samples. We also participate in several large clinical trials for development, validation and implementation of clinical biomarkers in prostate cancer.
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Kevin Alexander Med: Cardiovascular Medicine, Cardiovascular Med Institute
Last Updated: January 29, 2023 |
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Tim Assimes Med: Cardiovascular Medicine
Last Updated: July 13, 2022 |
Our investigative focus is the design, conduct, analysis, and interpretation of human molecular epidemiology studies of complex cardiovascular disease (CVD) related traits including coronary atherosclerosis and risk factors for coronary atherosclerosis. In addition to performing discovery and validation population genomic studies, we use contemporary genetic studies to gain important insight on the causal and mechanistic nature of associations between purported risk factors and adverse cardiovascular related health outcomes through instrumental variable analyses and genetic risk score association studies of intermediate phenotypes. Successful applicants will be immersed in cutting-edge molecular epidemiology studies of traits related to cardiovascular disease using large scale population biobanks including the Million Veteran Program, the Women’s Health Initiative, and the UK Biobank, with the goal of improving biological understanding, refining risk prediction, and discovering new therapeutic targets. |
Michael Kapiloff Ophthalmology, Med: Cardiovascular Medicine
Last Updated: July 13, 2022 |
Specificity and efficacy in intracellular signal transduction can be conferred by the anchoring and co-localization of key enzymes and their upstream activators and substrate effectors by scaffold proteins. The Kapiloff lab investigates “signalosomes” formed by scaffold proteins, asking fundamental questions such as: 1) how are signalosomes constituted; 2) how are upstream signals integrated by signalosomes to regulate in a concerted manner downstream effectors; 3) what is the physiologic relevance of these signalosomes; and 4) can signalosomes be targeted in a clinically relevant manner so as to constitute new therapeutic strategies. In particular, the Kapiloff lab studies signaling within the myocardium and retina. Using a comprehensive approach that includes biochemistry, cell biology, and in vivo physiology, ongoing projects address the regulation of pathological cardiac remodeling and the effects of disease on retinal neurons.
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Kiran Khush Med: Cardiovascular Medicine
Last Updated: January 18, 2022 |
Our heart transplant research group focuses on clinical and translational research in the field of heart transplantation. Our major projects currently focus on (1) donor heart evaluation and selection for heart transplantation, (2) evidence-based strategies to expand the heart transplant donor pool, (3) incidence, etiology, and mechanisms of primary graft dysfunction, (4) non-invasive biomarkers of acute rejection, (5) drug therapy to prevent and treat cardiac allograft vasculopathy--the leading cause of long-term graft failure after heart transplantation, and (6) developing genomic tools to monitor for early development of post-transplant malignancies. We are funded by the NIH and transplant-related foundations, and our work involves collaborations with other research groups across campus in Oncology, Bioengineering, Infectious Disease, and Biostatistics.
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Josh Knowles Med: Cardiovascular Medicine, Cardiovascular Med Institute, Med: Prevention Research Cntr
Last Updated: January 13, 2022 |
The overall theme of our research has been the genetic basis of cardiovascular disease across the continuum from Discovery to the development of Model Systems to the Translation of these findings to the clinic and most recently to the Public Health aspect of genetics. Currently our Discovery and basic translational efforts center on understanding the genetic basis of insulin resistance using genome wide association studies coupled advanced genetic analyses such as colocalization with exploration using in vitro and in vivo model systems including induced pluripotent stem cells and and gene editing screens.
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Josh Knowles Med: Cardiovascular Medicine
Last Updated: July 13, 2022 |
"The fundamental theme of work in the Knowles lab is the application of genetics to improve human health. We view this as a continuum from Discovery to the development of Model Systems to Clinical Translation to larger Public Health efforts. Currently, discovery and basic translational efforts center on understanding the genetic basis of insulin resistance and related cardiovascular traits using GWAS studies coupled with exploration in model systems both in vitro (including classic cell lines as well as induced pluripotent stem cells) and in vivo (primarily mouse models). Clinical-translational research efforts in the lab are at the intersection of genetics, insulin resistance and hypercholesterolemia. We are asking if we can improve an individual’s risk by giving them information (i.e. genetic risk score) about their inherited risk of heart disease. We are also performing a clinical trial to determine the mechanism of statin-associated diabetes (which predominantly occurs in those with insulin resistance). Finally, Familial Hypercholesterolemia (FH) is a major focus given its morbidity and mortality and public health impact. As the Chief Research Advisor for The FH Foundation (FHF), a patient-led non-profit research and advocacy organization, we are attempting to raise the profile of familial hypercholesterolemia (FH), an inherited disease that causes extremely elevated LDL cholesterol levels and risk of coronary disease. We helped lead the FHF efforts to establish a national patient registry (CASCADE FH), apply for an ICD10 code for FH, advocate for genetic testing to be offered to FH patients and are now using cutting-edge “big-data” approaches to identify previously undiagnosed FH patients in electronic medical records (FIND FH). We collaborate with the CDC, AHA and ACC on these efforts."
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Fatima Rodriguez Med: Cardiovascular Medicine
Last Updated: November 01, 2022 |
The Health Equity Advancement through Research and Technology (HEART) Lab, led by Dr. Fatima Rodriguez, aims to develop innovative approaches to understanding and eliminating cardiovascular disease health disparities across diverse and understudied populations. Prior and current projects seek to identify the source of inequities in cardiovascular disease by race, ethnicity, language, sex, age, and more. We have documented extensive barriers to guideline adherence to cardiovascular prevention recommendations and how these result in adverse clinical outcomes. Several projects also center around Hispanic cardiovascular health and prevention. We have published work highlighting the importance of disaggregation of Hispanic individuals by background, acculturation, and socioeconomic factors. We are also interested in using novel AI/machine learning approaches in the electronic health record to improve cardiovascular risk prediction and treatment for understudied populations, including historically marginalized racial/ethnic patient groups and older adults. Other areas of focus include promoting digital health equity by studying telemedicine access and utilization, especially after the expansion of virtual care following the COVID-19 pandemic. Our research also explores reasons and solutions to increase workforce diversity in cardiovascular medicine and representation of diverse groups in guideline-informing clinical trials. |
Matthew Wheeler Med: Cardiovascular Medicine
Last Updated: November 29, 2021 |
I am a physician scientist with interests in cardiomyopathies, rare and undiagnosed diseases, therapeutics and genomics. I have research training in myocardial and skeletal muscle biology and genetics, genomics, and multi-scale networks. In addition to my research training, I am a physician with interest and experience treating patients with hypertrophic cardiomyopathy, neuromuscular disease associated cardiomyopathies, and inherited dilated cardiomyopathies. I have clinical training in medicine, cardiology, cardiovascular genetics, and advanced heart failure and transplant cardiology. I have extensive translational science efforts, as site PI for ongoing clinical trials for hypertrophic cardiomyopathy and dilated cardiomyopathy and for cardiomyopathy consortia including NONCOMPACT, PPCM and the Precision Medicine Study/DCM Consortium. I am Co-PI of Stanford’s NIH-funded Center for Undiagnosed Diseases, a clinical site of the Undiagnosed Diseases Network. I am also Co-PI of the NIH-funded Bioinformatics Center of the Molecular Transducers of Physical Activity Consortium. I pursue projects and collaborations at the intersection of striated muscle genetics, genomics, therapeutics and clinical investigation.
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Sean Wu Cardiovascular Med Institute, Med: Cardiovascular Medicine
Last Updated: August 12, 2020 |
My laboratory seeks to identify mechanisms responsible for human congenital heart disease, the most common cause of still-births in the U.S. and one of the major contributors to morbidity and mortality in infants and toddlers. We believe that by understanding the mechanisms regulating growth and differentiation of heart precursor stem/progenitor cells during early embryonic development we can then apply these principles to understand the pathogenesis heart malformation during fetal development and to leverage them for treating adult onset heart diseases such as heart failure and arrhythmia. We currently use both genetically-modified mice as our in vivo model to understand the biology of heart development as well as induced pluripotent stem cells (iPSCs) as a in vitro model to study the process of heart cell formation. Our major areas of interests include cardiovascular developmental biology, disease modeling, tissue engineering, and regenerative biology. Within each of these areas we are particularly focused on understand the major genes that regulate the proper formation of heart chambers and the consequesnces of disrupting the normal expression of these genes and how that may lead to the development of congenital heart diseases. While mouse models are useful for studying the process of heart formation, they are not exactly like the human hearts in various ways. Since human heart fetal tissue are diffulty to obtain, we have chosen to use iPSCs derived from patients with particular congenital heart diseases to study steps involved in human heart malformation. Furthermore, to bring our work closer to treating heart disease patients, we have combined our expertise in stem cell biology with 3D biopring to make engineered functional heart tissue for screening drugs and to serve as replacement tissues for damaged heart muscles.
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Phillip Yang Med: Cardiovascular Medicine
Last Updated: July 13, 2022 |
Dr. Yang is a physician-scientist whose research focuses on cardiovascular regeneration and restoration. His laboratory combines stem cell biology with novel imaging technology to advance clinical implementation of induced pluripotent stem cells and their derivatives. Induced pluripotent stem cells and their secretes will trigger a paradigm shift. His research provides a requisite validation with emphasis on clinical translation. Dr. Yang is a Principal Investigator of the National Institute of Health (NIH) funded Cardiovascular Cell Therapy Research Network designed to conduct multi-center clinical trial on novel stem cell therapy. In addition, he leads multiple NIH, foundation, and pharmaceutical research grants along with five clinical trials. He has received several prestigious awards, including the NIH Career Development Award, NIH Career Enhancement Award in Stem Cell Biology, NIH Mid-career Award, and multiple awards from both the American Heart Association and American College of Cardiology. He is a frequent guest speaker and session chair at national and international meetings. |
Han Zhu Med: Cardiovascular Medicine, Cardiovascular Med Institute
Last Updated: February 13, 2023 |
Our lab is dedicated to discovering the underpinnings of immune-related diseases in the heart. Many cancer drugs may cause immune-related toxicity in the heart, including severe myocarditis, making it difficult for patients with cancer to get the life-saving treatments they need. We have previously discovered that several key types of immune cells may be involved in potentiating disease. We are currently performing experiments to pin down the underlying mechanisms of how immune cells may cause various inflammatory heart diseases. We use a combination of precision medicine-oriented techniques including single-cell RNA-seq, TCR-seq, and CyTOF as well as classical molecular biology, cell modeling and animal modeling to answer mechanistic questions about the pathogenesis of cardiac inflammatory diseases, with the goals of discovering therapeutic targets which can be brought to the patient bedside.
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Michelle Lin Surg: Emergency Medicine
Last Updated: October 26, 2022 |
Dr. Lin's active NIH-funded research portfolio includes developing a novel patient-reported outcome measure for emergency asthma care; evaluating post-acute transitions and outcomes for high-risk populations; and enhancing gender equity in the health professions workforce. Her prior funded projects have evaluated the impact of value-based care on emergency care delivery and payment; drivers of ED admission rates; and changes in the intensity of emergency care.
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William Robinson Med: Immunol and Rheumatology, Immunity Transplant Infection
Last Updated: January 12, 2022 |
Our lab studies the molecular mechanisms of and develops therapies to treat autoimmune and rheumatic diseases, with a focus on rheumatoid arthritis, osteoarthritis, multiple sclerosis, and systemic lupus erythematosus. The overriding objectives of our laboratory are: 1) To investigate the mechanisms underlying autoimmune diseases. 2) To develop novel diagnostics and therapeutics for autoimmune and rheumatic diseases. 3) To investigate the role of innate immune inflammation in osteoarthritis. We perform translational research, with the goal of rapidly converting discoveries made at the bench into practical patient care tools and therapies.
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Paul (PJ) Utz Med: Immunol and Rheumatology
Last Updated: July 14, 2022 |
The Utz Lab focus is on the normal immune system and how it differs from the immune system of patients with immunodeficiency disorders, infections, and autoimmune diseases. Autoimmune diseases being studied include systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), systemic sclerosis (scleroderma), myositis, primary biliary cirrhosis (PBC), Sjögren's disease, insulin dependent diabetes (type I diabetes or IDDM), multiple sclerosis (MS), inflammatory bowel disease (IBD), and mixed connective tissue disease (MCTD).
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Noah Diffenbaugh Environ Earth System Science, Woods Institute
Last Updated: January 12, 2022 |
The Climate and Earth System Dynamics Group is led by Prof. Noah S. Diffenbaugh. Our research takes an integrated approach to understanding climate dynamics and climate impacts by probing the interface between physical processes and natural and human vulnerabilities. This interface spans a range of spatial and temporal scales, and a number of climate system processes. Much of the group's work has focused on the role of fine-scale processes in shaping climate change impacts, including studies of extreme weather, water resources, agriculture, human health, and poverty vulnerability. |
Sarah Fletcher Civil and Environ Engineering, Woods Institute
Last Updated: June 27, 2022 |
We work to advance water resources management to promote resilient and equitable responses to an uncertain future. We develop computational modeling approaches that bridge the natural, built, and social environments. Our approach improves understanding of the water and climate risks that threaten people and the environment, while developing systems-based engineering and policy solutions. |
Meagan Mauter Civil and Environ Engineering, Woods Institute, Chemical Engineering
Last Updated: June 23, 2022 |
The mission of the Water & Energy Efficiency for the Environment Lab (WE3Lab) is to reduce the cost and carbon intensity of water desalination and reuse. Ongoing research efforts include: 1) developing automated, precise, robust, intensified, modular, and electrified (A-PRIME) water desalination technologies to support a circular water economy; 2) optimizing the coordinated operation of decarbonized water and energy systems; and 3) supporting the design and enforcement of water-energy-food policies (e.g., Effluent Limitation Guidelines, the Clean Power Plan, CA Sustainable Groundwater Management Act, etc.). |
Erin Mordecai Biology, Woods Institute
Last Updated: January 12, 2022 |
Our research investigates how environmental changes like climate and land use change are affecting infectious diseases in humans and wildlife. We use tools from disease ecology, including mathematical and statistical models, health surveillance data, remotely sensed data, laboratory experiments, and field surveys to better understand the mechanisms by which changes in temperature and habitat affect vectors and disease transmission. |
Thomas Robinson Ped: General Pediatrics, Med: Prevention Research Cntr, Epidemiology and Population Health, Cardiovascular Med Institute, Stanford Cancer Center, Woods Institute, HumanCentered Artificial Inte
Last Updated: January 27, 2023 |
Stanford Solutions Science Lab. The Stanford Solutions Science Lab designs solutions to improve health and well-being of children, families, and the planet. Dr. Robinson originated the solution-oriented research paradigm. He is known for his pioneering obesity prevention and treatment research, including the concept of stealth interventions. His research applies social cognitive models of behavior change to behavioral, social, environmental and policy interventions for children and families in real world settings, making the results relevant for informing clinical and public health practice and policy. His research is largely experimental, conducting rigorous school-, family- and community-based randomized controlled trials. He studies obesity and disordered eating, nutrition, physical activity/inactivity and sedentary behavior, the effects of television and other screen time, adolescent smoking, aggressive behavior, consumerism, and behaviors to promote environmental sustainability. Rich longitudinal datasets of physical, physiological, psychological, behavioral, social, behavioral, and multi-omics measures are available from our many community-based obesity prevention and treatment trials in low-income and racial/ethnic minority populations of children and adolescents and their parents. Stanford Screenomics Lab - Human Screenome Project. People increasingly live their lives through smartphones. Our Stanford Screenomics app captures everything that people see and do on their smartphone screens – a record of digital life – by taking a screenshot every 5 seconds. The resulting sequence of screenshots, make up an individual’s screenome, an unique and dynamic sequence of exposures, thoughts, feelings, and actions. To date, we have collected more than 350 million screenshots from 6-12 months of phone use from national samples of about 500 hundred adults and adolescents and their parents. Opportunities available to study the screenome to understand digital media use and its impacts on health and behavior, develop novel diagnostics and prognostics from the screenome, and deliver precision interventions to improve health and well being. An opportunity to help build this paradigm-disrupting new science. |
Sheri Krams Surg: Transplantation Surgery
Last Updated: July 13, 2022 |
Our research focuses on the control of immune responses to alloantigen and viruses (EBV, SARS-CoV-2) using both experimental models and human immunology. Current studies ongoing in the lab are:
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Sheri Krams Immunity Transplant Infection, Surg: Transplantation Surgery
Last Updated: June 23, 2022 |
Our research focuses on the control of immune responses to alloantigen and viruses (EBV, SARS-CoV-2) using both experimental models and human immunology. Current studies ongoing in the lab are: Insight into Development and Progression of Multi-System Inflammatory Syndrome and COVID in Children. Molecular and Cellular Immunobiology/CyTOF/bioinformatics
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Olivia Martinez Surg: Transplantation Surgery
Last Updated: July 13, 2022 |
My laboratory investigates the immune response to viruses and allogeneic tissues. We are interested in characterizing the human immune response to EBV, CMV, and SARS-CoV-2 to distinguish features that are associated with control of the virus or result in pathologies including COVID-19, MIS-C, and post-transplant viral disease. Projects that are available include 1) analysis of the diversity of TCR usage in the response to EBV, CMV, and SARS-CoV-2 through the use of next generation sequencing and single cell approaches to evaluate T cell phenotype and function; 2) characterization of the natural killer (NK) cell populations that participate in the response to viruses; 3) determining the role of the viral protein LMP1 in activation of the PI3K/Akt/mTOR pathway and the effect of targeting this pathway in EBV-associated B cell lymphoma development. 4) identification of novel host gene targets and pathways of oncogenesis utilized by EBV. Human immunology projects utilize cell lines as well as existing extensive repositories of human blood and tissue samples. Animal models of transplant immunology and tumor immunology are also established in the lab.
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Andrew Gentles Biomedical Data Sciences, Biomedical Informatics, Stanford Cancer Center, Neuroscience Institute
Last Updated: January 12, 2022 |
Our research focus is in computational systems biology, primarily in cancer and more recently in neurodegenerative diseases. We develop and apply methods to understand biological processes underlying disease, using high-throughput genomic and proteomic datasets and integrating them with phenotypes and clinical outcomes. A key interest is dissecting how the cellular composition and organization of tissues affects their behaviour in disease; and how these things might be targeted for therapy or diagnostic purposes. We collaborate with many wet lab and clinical groups at Stanford, including in the areas of cancer, immunology, and neuroscience. |
Olivier Gevaert Biomedical Informatics, Biomedical Data Sciences
Last Updated: January 18, 2022 |
Vast amounts of molecular data characterizing the genome, epi-genome and transcriptome are becoming available for a wide range of complex disease such as cancer and neurodegenerative diseases. In addition, new computational tools for quantitatively analyzing medical and pathological images are creating new types of phenotypic data. Now we have the opportunity to integrate the data at molecular, cellular and tissue scale to create a more comprehensive view of key biological processes underlying complex diseases. Moreover, this integration can have profound contributions toward predicting diagnosis and treatment. The Gevaert lab focuses on achieving progress in multi-scale modeling by tackling challenges in biomedical multi-scale data fusion. Applications are in the area of complex diseases with most projects in the lab focused on oncology, and possible new directions studying neuro-degenerative & cardiovascular diseases. |
Olivier Gevaert Biomedical Informatics, Biomedical Data Sciences
Last Updated: July 13, 2022 |
Multi-omics, multi-modal, multi-scale data fusion in complex diseases using machine learning |
Daniel Rubin Biomedical Data Sciences, Radiology, Biomedical Informatics
Last Updated: August 17, 2020 |
The QIAI lab focuses on cutting‐edge research at the intersection of imaging science and biomedical informatics, developing and applying AI methods to large amounts of medical data for biomedical discovery, precision medicine, and precision health (early detection and prediction of future disease). The lab develops novel methods in text and image analysis and AI, including multi-modal and multi-task learning, weak supervision, knowledge representation, natural language processing, and decision theory to tackle the challenges of leveraging medical Big Data. Our exciting work is bridging a spectrum of biomedical domains with multidisciplinary collaborations with top scientists at Stanford as well as with other institutions internationally. The QIAI lab provides a unique multidisciplinary environment for conducing innovative AI-based healthcare research with a strong record of scholarly publication and achievement. Core research topics in the laboratory include: (1) automated image annotation using unsupervised methods of processing associated radiology reports using word embeddings and related methods; (2) developing methods of analyzing longitudinal EMR data to predict clinical outcomes and best treatments, (3) creating multi-modal deep learning models integrating multi-dimensional EMR and other data to discover electronic phenotypes of disease, (4) developing AI models with noisy or sparse labels (weak supervision), and cross-modal, multi-task learning, and observational AI approaches, and (5) developing and implementing algorithms for distributed computation for training deep learning models that leverage multi-institutional data while avoiding the barriers to data sharing.
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