School of Medicine


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  • Julia Palacios

    Julia Palacios

    Assistant Professor of Statistics and of Biomedical Data Science

    BioDr. Palacios seek to provide statistically rigorous answers to concrete, data driven questions in evolutionary genetics and public health . My research involves probabilistic modeling of evolutionary forces and the development of computationally tractable methods that are applicable to big data problems. Past and current research relies heavily on the theory of stochastic processes, Bayesian nonparametrics and recent developments in machine learning and statistical theory for big data.

  • Bibek Paudel

    Bibek Paudel

    Postdoctoral Research Fellow, Biomedical Data Sciences

    BioI am a Postdoctoral Research Fellow at the Department of Biomedical Data Science. My research focuses on developing machine learning and statistical models to solve problems that are inter-disciplinary in nature, including those from the biomedical, ecological, and socio-political sciences. I received my Ph.D. in Computer Science from University of Zurich, Switzerland in 2019, where I developed new algorithms to improve recommendation diversity and algorithmic fairness. I used graph theory, deep learning, and latent-factor models to build documents representations, explainable knowledge base embeddings, and personalization systems. At Stanford, I am building new machine learning models for personalized medicine by combining biological domain knowledge and large heterogeneous datasets. My research spans both ends of the biomedical data spectrum: from single-cell observations to population health data. I am particularly interested in examining the disparate health impacts of environmental factors on vulnerable and minority populations and in understanding how these findings can guide policy interventions.

  • Maximilian Pfau

    Maximilian Pfau

    Visiting Postdoctoral Scholar, Biomedical Data Science

    BioPhysician-scientist who studies retinal diseases such as age-related macular degeneration with a focus on multimodal imaging and psychophysics.

  • Sylvia K. Plevritis, PhD

    Sylvia K. Plevritis, PhD

    Professor of Biomedical Data Science and of Radiology (Integrative Biomedical Imaging Informatics at Stanford)

    Current Research and Scholarly InterestsMy research program focuses on computational modeling of cancer biology and cancer outcomes. My laboratory develops stochastic models of the natural history of cancer based on clinical research data. We estimate population-level outcomes under differing screening and treatment interventions. We also analyze genomic and proteomic cancer data in order to identify molecular networks that are perturbed in cancer initiation and progression and relate these perturbations to patient outcomes.