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PRISM Mentors

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PRISM supports all faculty in recruiting postdocs. The faculty listed on this page have expressed special interest in the PRISM program and may be actively recruiting. This is one of many ways to identify potential postdoc mentors; also review the guidance and links in the PRISM Application Guide for other ways to explore Stanford faculty. As you look for potential postdoc mentors, consider how faculty research interests align with your own.

Faculty: to create a profile, click "Log In" at the top right corner, then the "PRISM Faculty Opt In" button below. To edit an existing profile, click "Log In" at the top right corner, then the "Edit" button under your name/department/URL.

 

PRISM Faculty Opt-In   Displaying 351 - 400 of 568
PRISM mentor Research Interests

Mirabela Rusu

Radiology, HumanCentered Artificial Inte
Dr.
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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. 

  • Stanford Cancer Imaging Training (SCIT) Program

Mirabela Rusu

Radiology
Assistant Professor
View in Stanford Profiles

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. 

Department URL:
http://radiology.stanford.edu/

  • Stanford Cancer Imaging Training (SCIT) Program

Dan Spielman

Radiology
Professor
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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.


Associated T32s: Stanford Center for Imaging Training (SCIT), Stanford Molecular Imaging Scholars (SMIS), Stanford Training in Biomedical Imaging Instrumentation (TBI2)

Tanya Stoyanova

Radiology
Assistant Professor
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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.

Sindy Tang

Mechanical Engineering, Bioengineering, Radiology
Associate Professor
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Mechanical Engineering, Bioengineering, Radiology


Last Updated: August 24, 2023

Postdoctoral Research Fellow – Cell biology & microfluidics, UCSF & Stanford

A joint postdoc position between the labs of Wallace Marshall (UCSF) and Sindy Tang (Stanford) is immediately available in the area of single-cell wound healing. The broad question we aim to answer is how the single-celled ciliate Stentor can heal drastic wounds. We are looking for a candidate with a background in cell biology or related fields. This position will allow ample opportunities to learn new techniques including microfluidics for single-cell manipulation and mathematical modeling.

Application
For questions or applications (see below), please feel free to reach out to Prof. Wallace Marshall (wallace.ucsf@gmail.com) or Prof. Sindy Tang (sindy@stanford.edu). To apply, please include a CV (with a publication list) and some detail about your background and interest in the project.

Project description:
Biomechanical mechanisms conferring wound resilience in single-celled organisms
Stentor coeruleus is a large, single-celled ciliate that has remarkable wound healing and regenerative capacity (see Slabodnick et al., Current Bio, 2014 https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.10...). It is found in environments that can be subject to high mechanical stresses due to natural flows or predation. The overall goal of this project is to investigate how this organism employs both mechanical and biochemical mechanisms upstream of wounding for wound prevention, as well as downstream of wounding for robust healing from wounds (https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-021-00970-0).

We have sequenced the Stentor genome, and developed tools for molecular manipulation of Stentor gene expression to pave the way to a molecular understanding of Stentor wound response.   This project involves conceptualization of a novel chemical screen to test the role of the cytoskeleton in conferring wound resistance to the cell, and the role of large-scale mechanical force generation in complementing biochemical healing modes to close wounds of increasing severity.

Some questions we ask are: how does Stentor cell mechanics give rise to wound resistance? How do cells respond to shear or other types of stresses? What molecular pathways are important in Stentor wound healing, and are they the same as in other eukaryotes?
The project combines cell biology, microfluidics for precise wounding (see Blauch et al., PNAS 2017 https://www.pnas.org/doi/abs/10.1073/pnas.1705059114), and mechanobiology modeling.

Required Qualifications:
Desired skills for this project include:
• Cell biology
• Chemical screen
• RNAi and genetic transformation
• Past experience with Stentor, other ciliates, or manipulation (e.g., microinjection) of large cells or embryos such as Drosophila
• Mathematical modelling of cellular processes
Candidates proficient in certain skills outlined above will have opportunities to receive training in complementary skill sets.

Required Application Materials:
Your CV with a publication list, and some detail about your background and interest in the project.

Sindy Tang

Mechanical Engineering, Bioengineering, Radiology
Associate Professor
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Mechanical Engineering, Bioengineering, Radiology


Last Updated: January 27, 2024

From finger prick tests for blood glucose monitoring to industrial-scale drug screening in pharmaceutical companies, the ability to extract information from scarce volumes of samples quickly and cheaply is key to effective disease management and drug discovery. To this end, microfluidics offers major advantages over conventional liquid handling due to drastic reduction in reagent volume and the precise control of single cells, microtissues, and their microenvironments. The micro-nano-bio lab under the direction of Dr. Sindy Tang aims to develop innovative micro and nanoscale devices that harness mass transport phenomena to enable precise manipulation, measurement, and recapitulation of biological systems, in order to understand the "rules of life" and accelerate precision medicine and material design for a future with better health and environmental sustainability. Our approach involves building new tools to probe biological systems (from single cells to microtissues), and engineering smart materials, synthetic cells & tissues with properties that mimic some of the amazing properties biological systems have. Current research projects include:

 

  • Understanding and accelerating the diagnosis of allergic diseases
  • Biomechanics of single cell wound resilience
  • Tools for advancing cancer research
  • Bottom-up construction of biological systems

Shreyas Vasanawala

Radiology
Professor
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Radiology


Last Updated: February 23, 2024

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
Professor
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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

  • Stanford Cancer Imaging Training (SCIT) Program

Greg Zaharchuk

Radiology
Professor of Radiology
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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, Radiology-RSL, Neuroscience Institute
Associate Professor of Radiology
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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
MR-histopathology correlation (both traditional histology and clearing methods)
MR-PET of AD
7T MR in AD
Analysis of iron-changes in exosomes from AD
Multi-modal MRI (DTI, ASL, QSM, rsfMRI) in mild traumatic brain injury
7T MR in Epilepsy
Ultra-high resolution 7T MRI
X-ray imaging of iron
X-ray imaging of myelin and myelin orientation
Scattered light imaging
Hippocampal microanatomy

Michael Zeineh

Radiology
Associate Professor
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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
Assistant Professor
View in Stanford Profiles

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
Assistant Professor
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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
Assistant Professor
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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
Professor
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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.


While conducting clinically relevant research has been my main objective, it has always gone hand-in-hand with another goal: I believe that education is one of the most important tools to improving human health, and I am committed to diversifying our profession for the good of our communities and society. I use every avenue available to transform the way people think about science and medicine and emphasize its contribution to their daily lives. I also invest my time in supporting initiatives that promote inclusion, equity, and diversity. I am the Vice Chair of Diversity and Inclusion in our Department of Surgery at Stanford, and in this role I oversee diversity/equity/inclusion initiatives that impact students ranging from high school and college, through to trainees and junior faculty. In my lab I have assembled a team of individuals from different racial, ethnic, gender, age, and socioeconomic backgrounds, and I believe our science is stronger because of this diversity.

  • Other

Electron Kebebew

Surg: General Surgery
Professor
View in Stanford Profiles

Surg: General Surgery


Last Updated: February 23, 2024

The Endocrine Oncology Research Laboratory is engaged in cutting-edge endocrine and neuroendocrine clinical, translational and basic research. Our research is focused on:

  • Identifying the molecular basis of endocrine cancers that could impact patient care.
  • Creating new and improved methods, strategies, technologies, and algorithms for the diagnosis of endocrine neoplasms.
  • Defining genetic testing criteria, and optimal screening and surveillance strategies for inherited endocrine and neuroendocrine syndromes.
  • Discovering new molecular, genetic, proteomic, and metabolomic markers for developing better diagnosis and novel targets for treatment of metastatic and advance endocrine and neuroendocrine cancers or biomarkers which could predict prognosis/response to surgical therapy.
  • Advanced imaging and genetics that will allow for precision endocrine surgery.

Todd Wagner

Surg: General Surgery
Associate Professor (Research)
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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
Professor
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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.

  • Adult and Pediatric Nephrology and Urology Research Training Program
  • Stanford Molecular Imaging Scholars (SMIS)

James Brooks

Urology
Professor
View in Stanford Profiles

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.

  • Adult and Pediatric Nephrology and Urology Research Training Program

Kevin Alexander

Med: Cardiovascular Medicine, Cardiovascular Institute
Assistant Professor
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Med: Cardiovascular Medicine, Cardiovascular Institute


Last Updated: January 29, 2023

Tim Assimes

Med: Cardiovascular Medicine
Associate Professor
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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‚Äôs Health Initiative, and the UK Biobank, with the goal of improving biological understanding, refining risk prediction, and discovering new therapeutic targets.

Shoa Clarke

Med: Cardiovascular Medicine, Med: Prevention Research Cntr
Assistant Professor
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Med: Cardiovascular Medicine, Med: Prevention Research Cntr


Last Updated: August 28, 2023

The Clarke Lab uses genomics, epidemiology, and data science to understand cardiovascular disease risk. Key areas of focus include:

1. Equitable development and applications of polygenic risk scores

2. Novel phenotyping using electronic health records, wearables, and/or medical imaging

3.  Artificial intelligence applications to medical imaging

4. Studying nataionl biobanks (Million Veteran Program, UK Biobank, All of Us)

 

  • Cardiovascular Disease Prevention Training Program

Michael Kapiloff

Ophthalmology, Med: Cardiovascular Medicine
Associate Professor
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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.

  • Training in Myocardial Biology at Stanford (TIMBS)

Kiran Khush

Med: Cardiovascular Medicine
Professor
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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. 

  • Mechanisms in Innovation in Vascular Disease
  • Multi-Disciplinary Training Program in Cardiovascular Imaging at Stanford
  • Training in Myocardial Biology at Stanford (TIMBS)

Brian Kim

Med: Cardiovascular Medicine, Cardiovascular Institute
Assistant Professor
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Med: Cardiovascular Medicine, Cardiovascular Institute


Last Updated: November 15, 2023

The lifetime risk of developing cardiovascular disease (CVD) is determined by the genetic makeup and exposure to modifiable risk factors. The Cardiovascular Link to Environmental ActioN (CLEAN) Lab is interested in understanding how various environmental pollutants (eg. tobacco, e-cigarettes, air pollution and wildfire) interact with genes to affect the transcriptome, epigenome, and eventually disease phenotype of CVD. The current focus is to investigate how different toxic exposures can adversely remodel the vascular wall leading to increased cardiac events. We intersect human genomic discoveries with animal models of disease, in-vitro and in-vivo systems of exposure, single-cell sequencing technologies to solve these questions. Additionally, we collaborate with various members of the Stanford community to develop biomarkers that will aid with detection and prognosis of CVD. We are passionate about the need to reduce the environmental effects on health through advocacy and outreach. We strongly believe that the mechanistic understanding of the adverse health effects of harmful exposures will help to devise a targeted approach towards reduction of environmental toxins as well as to identify areas in need of improving environmental equity.

  • Mechanisms in Innovation in Vascular Disease
  • Training in Myocardial Biology at Stanford (TIMBS)

Josh Knowles

Med: Cardiovascular Medicine, Cardiovascular Institute, Med: Prevention Research Cntr
Assistant Professor
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Med: Cardiovascular Medicine, Cardiovascular 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. 

  • Cardiovascular Disease Prevention Training Program
  • Diabetes, Endocrinology and Metabolism
  • Mechanisms in Innovation in Vascular Disease
  • Multi-Disciplinary Training Program in Cardiovascular Imaging at Stanford
  • Other

Josh Knowles

Med: Cardiovascular Medicine
Assistant Professor
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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."

  • Cardiovascular Disease Prevention Training Program
  • Diabetes, Endocrinology and Metabolism
  • Mechanisms in Innovation in Vascular Disease

Fatima Rodriguez

Med: Cardiovascular Medicine
Assistant Professor
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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
Assistant Professor
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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.

Department URL:
https://med.stanford.edu/cvmedicine.html

  • Training in Myocardial Biology at Stanford (TIMBS)

Sean Wu

Cardiovascular Institute, Med: Cardiovascular Medicine
Associate Professor
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Cardiovascular 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.

 

  • Mechanisms in Innovation in Vascular Disease
  • Other

Phillip Yang

Med: Cardiovascular Medicine
Associate Professor
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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 Institute
Clinical Instructor (2023: Assistant Professor), Director, Stanford Translational Cardio-Oncology
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Med: Cardiovascular Medicine, Cardiovascular 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. 

 

 

  • Cardiovascular Disease Prevention Training Program

Michelle Lin

Surg: Emergency Medicine
Associate Professor
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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.

  • Other

Samuel Yang

Surg: Emergency Medicine
Associate Professor
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Surg: Emergency Medicine


Last Updated: February 07, 2024

The investigative interests of my lab falls within the general themes of

1) Developing precision diagnostics for infectious diseases that integrates pathogen, host, and drug response information. This includes

  • Developing high-content, near-patient, diagnostic system for rapid broad pathogen detection and characterization.
  • Integrating multi-omics molecular and phenotypic data layers with novel computational approaches into advanced diagnostics and predictive analytics for acute infections.
  • Developing personalized, rapid antimicrobial susceptibility analysis system based on early response kinetics in physiological conditions to inform antimicrobial choice, dosage, and duration.
  • Exploring the clinical utility of serum bactericidal assay as a humoral immune functional assessment in the prediction of bloodstream infections. 

2) Understanding the functional roles of extracellular DNA in neutrophil extracellular traps and biofilm

  • As a DNAzyme that drives bactericidal effects and immunopathologies. 

 

William Robinson

Med: Immunol and Rheumatology, Immunity Transplant Infection
Professor
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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.

 

  • Molecular and Cellular Immunobiology
  • Stanford Training Program in Aging Research
  • Training Program in Adult and Pediatric Rheumatology

Paul (PJ) Utz

Med: Immunol and Rheumatology
Professor
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Med: Immunol and Rheumatology


Last Updated: February 23, 2024

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).

  • Molecular and Cellular Immunobiology
  • Training Program in Adult and Pediatric Rheumatology

Noah Diffenbaugh

Earth Energy Env Sciences, Woods Institute
Professor, Senior Fellow
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Earth Energy Env Sciences, 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
Assistant Professor

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
Associate Professor
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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
Associate Professor
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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 Institute, Stanford Cancer Center, Woods Institute, HumanCentered Artificial Inte
Professor
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Ped: General Pediatrics, Med: Prevention Research Cntr, Epidemiology and Population Health, Cardiovascular 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
Senior Associate Dean of Graduate Education and Postdoctoral Affairs, Professor of Surgery (Abdominal Transplantation)
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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:

  • Insight into Development and Progression of Multi-System Inflammatory Syndrome and Long Haul COVID in Children.
  • Exosomes and microRNAs in the regulation of  Immune Responses
  • NK Cell Responses to EBV
  • Development of strategies to control alloimmune responses
  • Molecular and Cellular Immunobiology

Sheri Krams

Immunity Transplant Infection, Surg: Transplantation Surgery
Professor, Senior Associate Dean for Graduate Education and Postdoctoral Affairs
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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.
Exosomes and microRNAs in the regulation of  Immune Responses
NK Cell Diversity and Responses to viral and allo antigens
Novel T regulatory populations

Molecular and Cellular Immunobiology/CyTOF/bioinformatics

  • Molecular and Cellular Immunobiology

Olivia Martinez

Surg: Transplantation Surgery
Professor
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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.

  • Molecular and Cellular Immunobiology

Andrew Gentles

Biomedical Data Sciences, Med: Biomedical Informatics Research (BMIR), Stanford Cancer Center, Neuroscience Institute
Assistant professor
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Biomedical Data Sciences, Med: Biomedical Informatics Research (BMIR), 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

Med: Biomedical Informatics Research (BMIR), Biomedical Data Sciences
Assistant Professor
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Med: Biomedical Informatics Research (BMIR), 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

Med: Biomedical Informatics Research (BMIR), Biomedical Data Sciences
Assistant Professor
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Med: Biomedical Informatics Research (BMIR), Biomedical Data Sciences


Last Updated: July 13, 2022

Multi-omics, multi-modal, multi-scale data fusion in complex diseases using machine learning

Olivier Gevaert

Biomedical Data Sciences, Med: Biomedical Informatics Research (BMIR)
Associate Professor

Biomedical Data Sciences, Med: Biomedical Informatics Research (BMIR)


Last Updated: January 23, 2024

Multi-omics, multi-modal, multi-scale data fusion for precision medicine

Vast amounts of biomedical data are now routinely available for patients ranging from sequencing of tissues to liquid biopsies. In addition, new computational tools for quantitatively analyzing radiographic images are now available. Multi-scale data is now available for complex diseases at molecular, cellular and tissue scale to establish a more comprehensive view of key biological processes. Intra and inter individual heterogeneities are often quoted as the main challenge for studying complex diseases. These heterogeneities exist at all scales, from microscopic to macroscopic. We develop multi-scale modeling approach to counter heterogeneity and uncover potentially untapped synergies between different data modalities by integrating information across spatial scales. Multi-scale modeling involves linking information from molecules, cells, tissues, and organs all the way to the organism and the population. We propose to use high dimensional molecular data with tissue scale image data to develop a statistical multi-scale modeling approach in the context of multi-modal & multi-scale modeling. Such modeling can contribute toward predicting diagnosis and treatment by revealing synergies and previously unappreciated relationships. Multi-scale modeling also can contribute to a more fundamental understanding of disease development and can reveal novel insights in how data at different scales are linked to each other.

Daniel Rubin

Biomedical Data Sciences, Radiology, Med: Biomedical Informatics Research (BMIR)
Professor of Biomedical Data Science, Radiology, and Medicine
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Biomedical Data Sciences, Radiology, Med: Biomedical Informatics Research (BMIR)


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.

  • Stanford Cancer Imaging Training (SCIT) Program

Nigam Shah

Med: Biomedical Informatics Research (BMIR), Biomedical Data Sciences
Associate Professor
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Med: Biomedical Informatics Research (BMIR), Biomedical Data Sciences


Last Updated: July 13, 2022

We 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. Our group runs the country's only bedside consult service to enable better medical decisions using aggregate EHR and Claims data at the point of care. Our team leads the Stanford Medicine Program for Artificial Intelligence in Healthcare, which makes predictions that allow taking mitigating actions, and studies the ethical implications of using machine learning in clinical care. We have built models for predicting future increases in cost, identifying slow healing wounds, missed diagnoses of depression and for improving palliative care.

  • Mechanisms in Innovation in Vascular Disease
  • Training Program in Adult and Pediatric Rheumatology

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