School of Medicine

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  • Scott Fleming

    Scott Fleming

    Ph.D. Student in Biomedical Informatics, admitted Autumn 2018

    BioScott Fleming is a Ph.D. Student in Stanford's Biomedical Informatics Training Program, Department of Biomedical Data Science. He completed his B.S. in Mathematical and Computational Science at Stanford University. During that time, he worked with Dr. Leanne Williams to build pipelines for analyzing heterogeneous, high-dimensional datasets in order to discover patterns of brain activity that contribute to anxiety and depression. His most recent work has focused on developing machine learning methods to make accurate and effective crowd-powered diagnoses for children with autism and other developmental disorders.

  • Sajjad Fouladvand, PhD, MSc

    Sajjad Fouladvand, PhD, MSc

    Postdoctoral Scholar, Biomedical Informatics

    BioSajjad Fouladvand, PhD, MSc is a postdoctoral scholar at Stanford Center for Biomedical Informatics Research. Dr. Fouladvand's research career thus far has been focused on developing and applying artificial intelligence (AI) algorithms to solve real-world healthcare problems. Prior to Stanford, he worked at the Institute for Biomedical Informatics at the University of Kentucky (UK) while completing his PhD in Computer Science. During this time, he also received training at Mayo Clinic’s Department of Artificial Intelligence and Informatics as an intern.

    While at UK as a PhD candidate, he developed a deep learning model based on transformer and Long Short-Term Memory (LSTM) models to analyze multi-stream healthcare data for prediction of opioid use disorder (OUD). While at Mayo Clinic as an intern, he created a LSTM based framework to predict progression from cognitively unimpaired to mild cognitive impairment in an aging population. In his new role at Stanford, Dr. Fouladvand is involved in conducting AI and healthcare data science research in close collaboration with clinicians, scientists, and healthcare systems with access to deep clinical data warehouses and broad population health data sources.

  • Jason Fries

    Jason Fries

    Research Engineer, Med/BMIR

    Current Role at StanfordI'm currently working as a staff research scientist in the Shah Lab and research scientist at Snorkel AI. My interests fall in the intersection of computer science and medical informatics. My research interests include:

    • Machine learning with limited labeled data, e.g., weak supervision, self-supervision, and few-shot learning.
    • Multimodal learning, e.g., combining text, imaging, video and electronic health record data for improving clinical outcome prediction
    • Human-in-the-loop machine learning systems.
    • Knowledge graphs and their use in improving representation learning