Independent Labs, Institutes, and Centers (Dean of Research)


Showing 11-20 of 91 Results

  • Justin Gardner

    Justin Gardner

    Associate Professor of Psychology

    Current Research and Scholarly InterestsHow does neural activity in the human cortex create our sense of visual perception? We use a combination of functional magnetic resonance imaging, computational modeling and analysis, and psychophysical measurements to link human perception to cortical brain activity.

  • Joseph Garner

    Joseph Garner

    Professor of Comparative Medicine and, by courtesy, of Psychiatry and Behavioral Sciences

    Current Research and Scholarly InterestsThe medical research community has long recognized that "good well-being is good science". The lab uses an integrated interdisciplinary approach to explore this interface, while providing tangible deliverables for the well-being of human patients and research animals.

  • Matthias Garten

    Matthias Garten

    Assistant Professor of Microbiology and Immunology and of Bioengineering

    Current Research and Scholarly InterestsWith a creative, collaborative, biophysical mindset, we aim to understand the ability non-model organisms to interface with environment to a point at which we can exploit the mechanisms finding cures against diseases and use the mechanisms as tools that we can use to engineer the environment. By developing approaches that allow a quantitative understanding and manipulation of molecular transport our research makes non-model organisms accessible to researchers and engineers.

    Specifically, we are studying how the malaria parasite takes control over red blood cells. By learning the biophysical principles of transport in between the host and the parasite we can design ways to kill the parasite or exploit it to reengineer red blood cells. The transport we study is broadly encompassing everything from ions to lipids and proteins. We use variations of quantitative microscopy and electrophysiology to gain insight into the unique strategies the parasite evolved to survive.

  • Brice Gaudilliere

    Brice Gaudilliere

    Associate Professor of Anesthesiology, Perioperative and Pain Medicine (MSD) and, by courtesy, of Pediatrics (Neonatology)

    Current Research and Scholarly InterestsThe advent of high dimensional flow cytometry has revolutionized our ability to study and visualize the human immune system. Our group combines high parameter mass cytometry (a.k.a Cytometry by Time of Flight Mass Spectrometry, CyTOF), with advanced bio-computational methods to study how the human immune system responds and adapts to acute physiological perturbations. The laboratory currently focuses on two clinical scenarios: surgical trauma and pregnancy.

  • Charles Gawad

    Charles Gawad

    Associate Professor of Pediatrics (Hematology/Oncology)
    On Partial Leave from 02/01/2025 To 10/01/2025

    BioOur lab works at the interface of biotechnology, computational biology, cellular biology, and clinical medicine to develop and apply new tools for characterizing genetic variation across single cells within a tissue with unparalleled sensitivity and accuracy. We are focused on applying these technologies to study cancer clonal evolution while patients are undergoing treatment with the aim of identifying cancer clonotypes that are associated with resistance to specific drugs so as to better understand and predict treatment response. We are also applying these methods to understand how more virulent pathogens emerge from a population of bacteria or viruses with an emphasis on developing a deeper understanding of how antibiotic resistance develops.

  • Pascal Geldsetzer

    Pascal Geldsetzer

    Assistant Professor of Medicine (Primary Care and Population Health) and, by courtesy, of Epidemiology and Population Health

    BioPascal Geldsetzer is an Assistant Professor of Medicine in the Division of Primary Care and Population Health and, by courtesy, in the Department of Epidemiology and Population Health. He is also affiliated with the Department of Biomedical Data Science, Department of Health Policy, King Center for Global Development, and the Stanford Centers for Population Health Sciences, Innovation in Global Health, and Artificial Intelligence in Medicine & Imaging.

    His research focuses on identifying and evaluating the most effective interventions for improving health at older ages. In addition to leading several randomized trials, his methodological emphasis lies on the use of quasi-experimental approaches to ascertain causal effects in large observational datasets, particularly in electronic health record data. He has won an NIH New Innovator Award (in 2022), a Chan Zuckerberg Biohub investigatorship (in 2022), and two NIH R01 grants as Principal Investigator (both in 2023).

  • Michael Genesereth

    Michael Genesereth

    Associate Professor of Computer Science

    BioGenesereth is most known for his work on Computational Logic and applications of that work in Enterprise Management, Computational Law, and General Game Playing. He is one of the founders of Teknowledge, CommerceNet, Mergent Systems, and Symbium. Genesereth is the director of the Logic Group at Stanford and the founder and research director of CodeX - the Stanford Center for Legal Informatics.

  • Michael Gensheimer

    Michael Gensheimer

    Clinical Associate Professor, Radiation Oncology - Radiation Therapy

    Current Research and Scholarly InterestsIn addition to my clinical research in head and neck and lung cancer, I work on the application of computer science and machine learning to cancer research. I develop tools for analyzing large datasets to improve outcomes and safety of cancer treatment. I developed a machine learning prognostic model using data from around 13,000 patients with metastatic cancer which performs better than traditional models and physicians [PubMed ID 33313792]. We recently completed a prospective randomized study in thousands of patients in which the model was used to help improve advance care planning conversations.

    I also work on the methods underpinning observational and predictive modeling research. My open source nnet-survival software that allows use of neural networks for survival modeling has been used by researchers internationally. In collaboration with the Stanford Research Informatics Center, I examined how electronic medical record (EMR) survival outcome data compares to gold-standard data from a cancer registry [PubMed ID 35802836]. The EMR data captured less than 50% of deaths, a finding that affects many studies being published that use EMR outcomes data.