School of Medicine
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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.
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