PRISM Mentors

The Kool lab uses the tools of chemistry and biology to study the structures, interactions and biological activities of nucleic acids and the enzymes that process them. Molecular design and synthesis play a major role in this work, followed by analysis of structure and function, both in vitro and in living systems. These studies are aimed at gaining a better basic understanding of biology, and applying this knowledge to practical applications in biomedicine.

Recent research interests include the development of chemical tools for mapping RNA structure and interactions in cells, methods for stabilization and conjugation of RNAs, and the development of probes of DNA repair pathways and their connections to cancer.

The Pop Lab is a research group led by Prof. Eric Pop in Electrical Engineering (EE) and Materials Science & Engineering (MSE) at Stanford University. We are located in the Paul Allen Center for Integrated Systems (CIS), working in the Stanford Nanofabrication Facility (SNF) and the Stanford Nano Shared Facilities (SNSF). We are affiliated with the Stanford SystemX Alliance and the Non-Volatile Memory Technology Research Initiative (NMTRI).

Our research is at the intersection of nanoelectronics and nanoscale energy conversion, exploring topics such as:

• Energy-efficient transistors, data storage (memory), and thermoelectrics
• 2D materials (graphene, h-BN, MoS2, WSe2,...) and phase-change materials (GST, VO2)
• Fundamental physical limits of current and heat flow, e.g. ballistic electrons and phonons
• Applications of nanoscale energy transport, conversion and harvesting

Our work includes nanofabrication, characterization, and multiscale simulations. On-campus collaborations include Materials Science, Physics, Chemical and Mechanical Engineering, and off-campus they range from UIUC, UC Davis, Georgia Tech, UT Dallas, Univ. of Tokyo and Singapore (NUS), to TU Wien, Univ. Bologna and Poli Milano.

To learn more about us, please visit http://poplab.stanford.edu

The Pop Lab is a research group led by Prof. Eric Pop in Electrical Engineering (EE) and Materials Science & Engineering (MSE) at Stanford University. We are located in the Paul Allen Center for Integrated Systems (CIS), working in the Stanford Nanofabrication Facility (SNF) and the Stanford Nano Shared Facilities (SNSF). We are affiliated with the Stanford SystemX Alliance and the Non-Volatile Memory Technology Research Initiative (NMTRI).

Our research is at the intersection of nanoelectronics and nanoscale energy conversion, exploring topics such as:

• Energy-efficient transistors, data storage (memory), and thermoelectrics
• 2D materials (graphene, h-BN, MoS2, WSe2,...) and phase-change materials (GST, VO2)
• Fundamental physical limits of current and heat flow, e.g. ballistic electrons and phonons
• Applications of nanoscale energy transport, conversion and harvesting

Our work includes nanofabrication, characterization, and multiscale simulations. On-campus collaborations include Materials Science, Physics, Chemical and Mechanical Engineering, and off-campus they range from UIUC, UC Davis, Georgia Tech, UT Dallas, Univ. of Tokyo and Singapore (NUS), to TU Wien, Univ. Bologna and Poli Milano.

To learn more about us, please visit http://poplab.stanford.edu

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. 

My overarching goal is to understand how cell growth triggers cell division. Linking growth to division is important because it allows cells to maintain a specific size range to best perform their physiological functions. For example, red blood cells must be small enough to flow through small capillaries, whereas macrophages must be large enough to engulf pathogens. In addition to being important for normal cell and tissue physiology, the link between growth and division is misregulated in cancer. Today, thanks to decades of research into the question of how cells control division, we have an extensive, likely nearly complete parts-list of key regulatory proteins. Deletion, inhibition, or over-expression of these proteins often results in changes to cell size. However, the underlying molecular mechanisms for how growth triggers division are not understood.  How do the regulatory proteins work together to produce a biochemical activity reflecting cell size or growth? Since we now have most of the parts, the next step to solving this fundamental question is to better understand how they work together.

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. 

We are interested in fundamental aspects of cell-cell recognition, migration and development with the mammalian immune and vascular systems as  models. We use molecular, genetic and single cell transcriptomic and mass cytometric approaches to study  the development and trafficking of  lymphocytes, NK cells and dendritic cells and their role in immune function in health and diseases.    The vascular endothelium controls immune cell recruitment from the blood,  and thus determines the nature and magnitude of immune and inflammatory responses.     In a major new effort, we are applying single cell approaches (scRNAseq and mass cytometry), and novel computational approaches to probe endothelial cell specialization and responses in models of immune and tumor angiogenesis and inflammation.     Although our focus is on fundamental problems in biology, the work is intrinsically translational and the laboratory is interested in applying its  discoveries to models of infection and immune pathology: examples include genetic studies of GPCR's and assessment of novel therapeutics in models of inflammatory bowel disease, psoriasis, cancer, aging and infection.   We are actively recruiting fellows with experience in biocomputation and coding who can take advantage of the datasets we are generating;   or experience in vascular biology, immunology,  imaging and cytometry.

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.

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.

The Horns Lab creates and uses new technologies to understand and manipulate cells. We aim to discover the fundamental principles governing how cells and tissues operate, and to harness these insights to improve human health. Our work unites molecular engineering, synthetic biology, and genomics to answer questions and solve problems in immunology, neuroscience, cancer, and aging.

The Sherlock lab uses experimental approaches to understand the evolutionary process, specifically interested in i) what's the rate of beneficial mutation, ii) what is the distribution of fitness effects of beneficial mutations, iii) what are the identities of beneficial mutations (and are they gain or loss of function, are they recessive, dominant or overdominant, are the genic or regulatory?) and iv) how do each of these change as a function of genotype, ploidy and environment. We are also interested in how mutations that are beneficial in one environment fare in others, to explore the trade-offs that inevitably occur when fitness increases in a specific environment, and we are interested in exploring at what level experimental evolution can be deterministic, and at what level it is stochastic. We typically use short-term continuous (chemostat) and serial batch culture experiments in conjunction with lineage tracking and high throughput sequencing to understand the adaptive changes that occur in yeast in response to selective pressures as they evolve in vitro.

The FUNR Lab, lead by Flora Rutaganira uses choanoflagellates—the closest living single-celled relatives to animals—to study the origin of animal cell communication. We apply chemical, genetic, and cell biological tools to probe choanoflagellate cell-cell communication. We hope that our research has implications for understanding not only animal cell signaling, but also the origin of multicellularity in animals.

The FUNR Lab, lead by Flora Rutaganira uses choanoflagellates—the closest living single-celled relatives to animals—to study the origin of animal cell communication. We apply chemical, genetic, and cell biological tools to probe choanoflagellate cell-cell communication. We hope that our research has implications for understanding not only animal cell signaling, but also the origin of multicellularity in animals.

The Peltz laboratory develops and uses state of the art genetic, genomic and stem cell technologies in its research programs. These methodologies are used to discover the mechanisms mediating disease susceptibility and drug response, and to develop new therapies. As one example, we developed a novel computational genetic analysis method, which has identified genetic factors affecting disease susceptibility and biomedical responses in mouse models. One of the genetic findings is the basis for an ongoing clinical trial that tests a new therapy for preventing opiate withdrawal from occuring in babies born to mothers that take opiates. Over 25 genetic factors affecting susceptibility to drug addiction, chronic pain, infectious diseases, and others have been identified. An ongoing effort is now analyzing 10000 biomedical responses in panels of inbred mouse strains. Single-cell RNA sequencing and metabolic analysis are used to identify developmental and disease-causing pathways. Stem cell-based methods for liver engineering are also used. As examples of this, the Peltz lab has produced mice with humanized livers that are used to improve drug safety; developed methods to engineer human liver from adipocyte stem cells; and to produce human liver organoids from stem cells, which are used for studying the pathogenesis of human genetic liver diseases.

The Batsuli Lab focuses on elucidating mechanisms of the immune response to blood coagulation proteins deficient in patients with inherited bleeding disorders, specifically hemophilia. Hemophilia is a rare bleeding disorder caused by low or absent clotting proteins factor VIII or factor IX that affects an person's risk of bleeding. Our lab seeks to better understand the interaction of factor proteins with antigen presenting cells and the mechanisms of antibody development against factor replacement therapies in order to develop therapeutic strategies that evade these immune responses and promote tolerance. The Batsuli Lab supports a collaborative and supportive research environment that engages in team science.

We are seeking an individual for a postdoctoral fellowship in perinatal / neonatal health who has training and experience in epidemiology or a related field (e.g. PhD or MD with relevant research training). The primary mentor is Dr. Henry C. Lee, Associate Professor of Pediatrics (Neonatology), and Chief Medical Officer of the California Perinatal Quality Care Collaborative (CPQCC) . The CPQCC and its sister organization, the California Maternal Quality Care Collaborative (CMQCC) have their data centers and leadership based at the division of neonatology at Stanford, and have active research programs in perinatal health. The ability to link maternal, neonatal, and long-term follow-up data allow for opportunities to conduct large population-based epidemiologic studies, health services research, and work in reducing disparities. The emphasis of this fellowship will be on the population of extremely preterm birth, including prediction / modeling of outcomes for periviable infants, and development of tools for counseling families affected by extremely preterm birth. The postdoctoral fellow will collaborate with epidemiologists, biostatisticians, and clinician-scientists, with opportunities for mentorship and collaborative research on related topics.

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.  

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

Our lab’s research portfolio crosses multiple disciplines including computational neuropsychiatry, multimodal neuroimaging, cognitive neuroscience and neurocognitive rehabilitation. Our computational neuropsychiatry research mainly involves investigating alterations in the organization of connectome in various neurodevelopmental and neurocognitive disorders using state of the art neuroimaging techniques (fMRI, sMRI, DWI, functional NIRS) combined with novel computational methods (graph theoretical and multivariate pattern analyses). The ultimate research goal is to translate the findings from computational neuropsychiatry research toward developing personalized interventions. We have been developing personalized interventions that integrate computerized cognitive rehabilitation, real-time functional brain imaging and neurofeedback, as well as virtual reality (VR) tailored toward targeted rehabilitation of the affected brain networks in patients with neurocognitive disorders.

Ongoing studies in Dr. Hosseini’s lab include: .

• Multimodal data integration using multilayer networks for early detection of Alzheimer's disease   
• Real-time fNIRS neuromonitoring and neurofeedback for targeted enhancement of working memory in children with ADHD.
• Multimodal neuroimaging study to examine the effect of long-term, cognitive intervention on brain networks in older adults at risk of developing Alzheimer’s disease.
• Developing a low-cost, wireless, wearable, optical imaging system for personal and population-based functional neuroimaging and neuro-intervention.
• Noninvasive optical imaging for monitoring of functional stroke recovery and to direct and optimize stroke therapies.

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. 

The Itakura Lab has an immediate opening for a creative and motivated postdoctoral scholar to conduct applied research in the areas of machine learning and pattern/feature detection with a focus on either computer vision/image or genomic/molecular data processing and analysis. The lab focuses on implementing machine learning frameworks and radiogenomic approaches on heterogeneous, multi-scale cancer data (e.g., clinical, imaging, histopathologic, genomic, transcriptomic, epigenomic, proteomic) to accelerate discoveries in cancer diagnostics and therapeutics. Projects include prediction modeling of survival and treatment responses, biomarker (feature) discovery, cancer subtype discovery, and identification of new therapeutic targets. Guided by critical and relevant problems in oncology, these projects have the potential to lead to clinically actionable or translatable findings.

The successful candidate will join the Department of Medicine, Division of Oncology and work. The job description:

• Build and implement algorithms in machine learning applied to either imaging data (computer vision) or genomic/molecular data (computational biology)
• Develop software tools for integrative analysis of heterogeneous, multi-omic cancer data using machine learning
• Publish and present research findings in journals and conferences

Required Qualifications:

• PhD (or MD/PhD) in Computer Science, Engineering, Informatics, Statistics, Applied Physics, or a related field with strong skills in data mining, machine learning, or statistics
• Experience in modeling, integrative analyses, parallel computing, and/or software development desirable
• Biomedical knowledge or research experience is not a requisite
• Demonstrated ability to work independently, problem-solve, author manuscripts, strive for innovation, and be highly self-motivated
• Strong interpersonal and communication skills, and ability to work as part of a multi-disciplinary team

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

Our focus is on the basic molecular mechanisms of stem cells and muscle and their application to aging, regenerative medicine, and disease. The Blau lab brings together biologists, bioinformatics experts, and bioengineers who are interested in everything from the basic mechanisms of disease, to technology development, to clinical translation. We capitalize on an interdisciplinary approach to science because 'Where we look and how we look determines what we see’. The laboratory collaborates extensively with other researchers. Our overall objective is to understand and apply biology to improve quality of life.

A major aim of our lab is to define metrics of immune competence in various settings, including cancer immunotherapy, organ transplantation, allergy, and chronic viral infection. We use CyTOF mass cytometry, often in combination with other technologies, to broadly survey immune features at the cellular level, then examine links between features or groups of features and clinical outcome. A long-term goal is to create an assay of global immune competence that could predict risk for various immune-related outcomes in both healthy individuals and in disease.

Our lab is interested in the host pathways that determine the susceptibility of humans to viral disease. Viruses constantly evolve to exploit host machineries for their benefit whilst disarming host restriction mechanisms. Discovery of host proteins critical for viral infection illuminates basic aspects of cellular biology, reveals intricate virus host relationships, and leads to potential targets for antiviral therapeutics.

We know far more than what we can directly experience. We learn about the world by drawing rich, abstract inductive inferences that go beyond what we can observe, and much of these observations come from behaviors of others around us. By engaging in social learning in diverse contexts, humans learn from others, share their knowledge with others, and even accumulate a body of cultural knowledge over generations. 

The Social Learning Lab (SLL) aims to understand the cognitive mechanisms that underlie the communicative interactions we experience in our lives. In particular, the ways in which young children learn from others provide a unique window to the interface between our ability to draw powerful inferences and to our understanding of others’ thoughts and actions (Theory of Mind). To better understand this process, we design and conduct behavioral experiments with young children and adults, often combined with computational models that help predict and explain behavioral results.

The Karakikes Lab investigates the molecular mechanisms of rare cardiac diseases, such as dilated cardiomyopathy (DCM). We employ an interdisciplinary approach, integrating functional genomics approaches in human pluripotent stem cell (hPSC) derived cardiovascular cells with single-cell transcriptomics and epigenetics to study cardiomyopathies in a genetically controlled and systematic manner.

Our research aims to improve population health by creating high quality evidence about what health interventions work in whom and where, when, and how to implement them. Most of our research is focused on infectious diseases, including malaria, diarrhea, soil-transmitted helminths, and influenza. Our focus is on improving the health of vulnerable populations from low-resource settings, both domestically and internationally. We use a variety of epidemiologic, computational, and statistical methods, including causal inference and machine learning methods. Department URL: https://med.stanford.edu/epidemiology-dept.html

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.

Mission: Our mission is to both use neuroscience as a tool for improving education, and use education as a tool for furthering our understanding of the brain. On the one hand, advances in non-invasive, quantitative brain imaging technologies are opening a new window into the mechanisms that underlie learning. For children with learning disabilities such as dyslexia, we hope to develop personalized intervention programs that are tailored to a child’s unique pattern of brain maturation. On the other hand, interventions provide a powerful tool for understanding how environmental factors shape brain development. Combining neuroimaging with educational interventions we hope to further our understanding of plasticity in the human brain.

The Lab: The Brain Development & Education Lab is located in the Graduate School of Education at Stanford University and represents a collaboration between the Division of Developmental and Behavioral Pediatrics within the School of Medicine, the Graduate School of Education and the Wu Tsai Neuroscience Institute (we recently moved from The University of Washington’s Institute for Learning & Brain Sciences). The focus of the lab is understanding the interplay between brain maturation and cognitive development.  The lab is interdisciplinary, drawing on the fields of neuroscience, psychology, education, pediatrics and engineering to answer basic scientific and applied questions.  Current projects focus on understanding how the brain’s reading circuitry develops in response to education and how targeted behavioral interventions prompt changes in the brain’s of children with dyslexia. A major component of this work is the development of software to measure properties of human brain tissue, localize differences and quantify changes over development.