PRISM Mentors

How do we learn to communicate using language? I study children's language learning and how it interacts with their developing understanding of the social world. I am interested in bringing larger datasets to bear on these questions and use a wide variety of methods including eye-tracking, tablet experiments, and computational models. Recent work in my lab has focused on data-oriented approaches to development, including the creation of large datasets like Wordbank and MetaLab. I also have a strong interest in replication, reproducibility, and open science; some of our research addresses these topics.

http://web.stanford.edu/~mcfrank

My research utilizes multimodal imaging (fMRI, dMRI, qMRI), computational modeling, and behavioral measurements to investigate human visual cortex. We seek to understand how the underlying neural mechanisms and their anatomical implementation enable rapid and efficient visual perception and recognition. Critically, we examine how the human brain and visual perception change across development to understand how the interplay between anatomical constraints and experience shapes visual cortex and ultimately behavior.

We strive to create a lab that reflects the diversity of our global community and is actively involved in solving scientific and societal problems that affect all of us. I am also involved in the Wu Tsai Neurosciences Institute and the Ophthalmology T32 training grant.

Our lab uses the tools of cognitive neuroscience to understand the brain systems involved in decision making, executive function, and behavioral change.  We also develop tools to improve the reproducibility and transparency of neuroimaging research, including data sharing and data analysis.

My lab's research uses neuroimaging to understand the brain systems underlying decision making and executive function.  We are also engaged in the development of neuroinformatics tools to help improve the reproducibility and transparency of neuroscience, including the Openneuro.org and Neurovault.org data sharing projects and the Cognitive Atlas ontology.

The Stanford Media & Psychology Lab is a multidisciplinary group focused on design and data analysis techniques for study of media and human behavior, integrating established and new disciplines to accelerate research innovations that foster innovations in psychological theory and social policy. Current research directions include emotional regulation, media and technology use, lifespan development, and new methods for analysis of intensive longitudinal analysis–including analysis of ecological momentary assessment and smartphone sensor data. Our lab is committed to global diversity and fostering minority representation in social science, and we collaborate widely with schools and departments across Stanford and other universities.

The gene encoding the p53 transcription factor is the most commonly mutated gene in human cancer, yet we lack a complete understanding of how its loss promotes cancer and how to target this pathway therapeutically. My lab studies p53 in the context of two very deadly and common cancer, pancreatic cancer and lung cancer, to understand how p53 loss promotes tumor initiation and progression. We are investigating not only how p53 mutation changes tumor cells themselves but also how these changes in tumor cells alter the cells of the tumor microenvironment to promote cancer development. We strive to understand p53 function using varied approaches, including mass spectrometry, CRISPR screening, ATAC-sequencing, spatial transcriptomics and in vivo mouse analyses. Using these combined approaches, we are gaining key new insights into the fundamental functions of p53 in vivo, which will ultimately inform us on how to target this critical pathway therapeutically.

The Frock laboratory is interested in elucidating mechanisms of DNA double-stranded break (DSB) repair and chromosome translocations.  We employ a high-throughput sequencing technology that identifies and maps cellular DSBs.  We are interested in further developing this technology to more fully quantify the DSB repair fates from targeted DSBs.  Our research disciplines are broad and cover aspects of molecular and cancer biology, bioinformatics. immunology, genome editing, and radiation biology.

The Kalbasi laboratory tackles questions at the intersection of immunology and cancer biology, with an emphasis on therapeutic development. Here are some selected areas of interest:

Cytokine-based rewiring of T cells: Advances in gene therapy and synthetic biology have ushered in a new era in T cell therapy. Engineered T cells can now be dynamically modulated to perform context-specific functions. To leverage these technologies, the lab is studying how external cytokine signals, especially common gamma chain family, shape T cell function (Kalbasi, et al. Nature 2022).

Unveiling sarcoma targets through cell-of-origin queries: Most patients with sarcoma have yet to benefit from immunotherapy, which may in part be related to the absence of natural endogenous T cell responses to sarcoma. Engineered T cell approaches offer a solution to this problem, but therapeutic T cell targets are critical. The lab is examining sarcoma cell-of-origin as an approach to unveil rational, lineage-based therapeutic targets for T cell therapy.

Myeloid reprogramming: Myeloid cells are prevalent in the sarcoma microenvironment and further recruited by radiation and other cytotoxic therapies. The  laboratory is studying how activation of pattern recognition receptor signaling may serve to bias the fate of radiation-associated myeloid cells toward one that promotes anti-tumor functions of T cells.

Tumor-intrinsic resistance to radiotherapy: Cancer cells evolve under immunologic pressure and not surprisingly, find myriad ways to evade immune attack. Uncovering and bypassing these evasive tactics can restore the efficacy of immunotherapy (Kalbasi, et al. Sci Transl Med 2020). The lab is studying whether the same principles may apply to radiation resistance, which may be both immune-dependent or immune-independent.

Research Tools: The Kalbasi lab aims to leverage the growing toolkits developed by synthetic biologists to study perturbations of the immune system and cancer and identify new therapeutic approaches. This means we are heavily invested in syngeneic mouse model systems to faithfully capture tumor - immune interactions, including adoptive transfer models. The lab leverages molecular biology, viral and CRISPR based genetic engineering, basic and advanced immunologic assays, and next-generation sequencing, including single cell approaches. Our group includes both wet and dry lab scientists. We are excited and unafraid to try new techniques and/or engage more experienced collaborators. Finally, the lab has a strong translational focus with a disease interest in sarcoma and melanoma and therapeutic interests that include T cell therapy, immuno-oncology and radiation therapy. The lab is actively involved in biospecimen analysis related to clinical trials:

https://clinicaltrials.gov/ct2/show/NCT04119024?cond=il13ra2&draw=2&rank=1
https://clinicaltrials.gov/ct2/show/NCT04420975?cond=bo-112+sarcoma&draw=2&rank=1
https://clinicaltrials.gov/ct2/show/NCT02701153?cond=5-day+sarcoma+radiation&draw=2&rank=1

Use artificial intelligence in image and biology guided radiotherapy and medical image analysis (PET/CT).

Theranostic nanoparticles for radiosensitization and medical imaging.

Novel treatment technique for ocular disease radiotherapy.

Radio-neuromodulation using focused kV x-rays.

Ultrasound parametric imaging.

We perform translational cancer research by analyzing human tissue and blood samples with next-generation sequencing to understand the genetic underpinnings and expression signatures that determine treatment response and resistance. We use genetically engineered mouse models to validate our findings, perform mechanistic experiments, and test new therapies. Our ultimate goal is to translate our findings to the clinic to improve outcomes for patients with cancer.

An emerging hallmark of cancer is the modulation of metabolic pathways by malignant cells to promote cancer development. Dr. Jiangbin Ye’s professional interest is to investigate the causes and consequences of the abnormal metabolic phenotypes of tumor cells, with the prospect that therapeutic approaches might be developed to target these metabolic pathways to improve cancer treatment. The lab’s current goal is to explore the complex role of metabolic reprogramming in epigenetic regulations, and how cell fate and differentiation process are controlled by these epigenetic regulations. Ye’s lab is located in the Stanford University School of Medicine, with state-of-art research facilities. The multidiscipline research environment provides unique and outstanding training and collaborating opportunities. The candidate will have direct access to modern metabolomics research tools, including YSI biochemical analyzer, Seahorse XF Analyzer, hypoxia chamber and Agilent Q-TOF LC-MS. The lab is specialized in both untargeted and targeted metabolomics analysis, particularly isotope tracing technique for metabolic flux analysis. Dr. Ye is committed to mentoring and training for the candidate, providing all the support the candidate needs to reach the career goal.

Cancer Imaging, Nanoparticles, MRI, PET/MR, Cancer Immunotherapy Imaging, Tumor Associated Macrophages, Stem Cell Tracking

The Demirci Bio-Acoustic MEMS in Medicine Lab (BAMM) specializes in creating technologies to manipulate cells in nanoliter volumes to enable solutions for real world problems in medicine including applications in infectious disease diagnostics and monitoring for global health, cancer early detection, cell encapsulation in nanoliter droplets for cryobiology, and bottom-up tissue engineering.
areas of research are :

Micro nano scale technologies in medicine

Extracellular vesciles

Early Cancer Detection

Biomedical engineering

microrobotics

Utkan Demirci is a professor at Stanford University School of Medicine and serves as the interim division chief and co-director of the Canary Center for Cancer Early Detection in the Department of Radiology. His group focuses on developing innovative microfluidic biomedical technology platforms with broad applications to multiple diseases. Some of his inventions have already been translated into Food and Drug Administration-approved products serving patients. He has mentored and trained many successful scientists, entrepreneurs, and academicians. Currently the group has a strong core focused on bio fabrication, Extracellular vesicles enrichment and isolation, small scale robotics for biomedicine and development of point of care metamaterial based optical sensors.

Our lab's research lies at the interface of biology, engineering, nanotechnology, and medicine. We develop and apply translational micro/nanotechnologies to study cellular heterogeneity and complex biological systems for single cell analysis and precision medicine.  At this unique nexus, we apply key biological principles to design engineering platforms. Our research philosophy is to apply these platforms to fundamentally understand and address the mechanisms of disease (i.e., cancer, infections). 
We, for the first time, have demonstrated magnetic levitation of living cells and its application to detect minute differences in densities at the single-cell level.  We apply this unique tool to perform ultra-sensitive density measurements, magnetic blueprinting, imaging, sorting and profiling of millions of cells and rare biological materials in seconds in real-time at a single-cell resolution.  For instance, magnetic levitation technology can sort rare circulating tumor markers and cells from patient whole blood  without relying on any markers, tags or antibodies, which cut cross multiple disciplines of magnetics, microfluidics and molecular biology.
Our lab's mission is to bridge the gap between biology, engineering and nanotechnology; to develop simple, inexpensive, easy-to-use, yet, broadly applicable platforms that will change the way in which medicine is practiced as well as how patients are monitored, diagnosed and treated for precision medicine. We apply key biological principles to engineering designs.  Interfacing our unique bioengineering platforms with next-generation sequencing technologies, we aim to understand and answer fundamental questions mainly in cancer biology, antibiotic resistance, and regenerative medicine.
Our focus is to develop new tools and technologies to investigate and fundamentally understand disease and wellness. Our research efforts are summarized as follows:

• Creating new tools and technologies to detect and isolate circulating biological signatures, materials and markers from biological fluids (i.e., circulating tumor cells, circulating tumor emboli, exosomes in blood, urine, and saliva).
• Enabling investigations of these rare biological materials to “decode” the molecular, genetic and proteomics characteristics to better understand the biology of disease, with a special focus on cancer biology and metastasis.
• Detecting antibiotic susceptibility using magnetic levitation. 
• Evolving these technologies into the next generation of applications in antibiotic resistance to eradicate biofilms and resistant microorganisms.
• Exploring self-assembly of single cells under microgravity conditions for bioprinting, tissue engineering and regenerative medicine. 

We are seeking open and honest, creative, dedicated, and team-oriented individuals to join our research team. Our lab prioritizes inclusion and diversity to achieve excellence in research and to foster an intellectual climate that is welcoming and nurturing. Two positions are available for energetic, self-driven and passionate postdoctoral fellow candidates.  Applicants are expected to be technically competent in a discipline relevant to our mission and vision.  

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.

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.

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.

Department URL:
https://canarycenter.stanford.edu/

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. 

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/

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.

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.

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.

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.