School of Medicine
Showing 1-5 of 5 Results
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Fateme (Fatima) Nateghi
Postdoctoral Scholar, Biomedical Informatics
BioAs a postdoc researcher at the Stanford Center for Biomedical Informatics Research (BMIR), I find myself at the exciting intersection of machine learning and healthcare. My journey began with a PhD in Biomedical Sciences from KU Leuven in Belgium, where I explored the complexities of machine learning algorithms and their transformative potential in clinical settings. My research focused on adapting these algorithms for time-to-event data, a method used to predict when specific events may occur in a patient’s future.
At Stanford, my work centers on building trustworthy AI systems to enhance healthcare delivery. I develop and evaluate machine learning models that integrate structured electronic health records (EHRs) and unstructured clinical notes to support real-world clinical decision-making. My recent projects include predicting treatment retention in opioid use disorder, improving antibiotic stewardship for urinary tract infections, and enabling digital consultations through large language models (LLMs). I'm particularly interested in embedding-based retrieval and retrieval-augmented generation (RAG) methods that help bridge cutting-edge AI research with clinical practice.
My role involves not just advancing the integration of machine learning in healthcare but also collaborating with a diverse team of clinicians, data scientists, and engineers. Together, we're striving to unravel complex healthcare challenges and ultimately improve patient outcomes. -
Jeff Nirschl
Affiliate, Biomedical Data Science
BioJeff Nirschl, M.D., Ph.D. is an Instructor in Pathology at Stanford University, Stanford, CA with clinical expertise in Neuropathology. He completed his Ph.D. in Neuroscience at the University of Pennsylvania under the supervision of Dr. Erika Holzbaur. During his thesis research, he investigated axonal transport and genetic forms of parkinsonism. He also developed computational image analysis workflows for fluorescence microscopy and digital pathology. His research interests include molecular motors and the neuronal cytoskeleton, the regulation of axonal transport in neurodegeneration, digital pathology, and quantitative image analysis using machine learning.
https://orcid.org/0000-0001-6857-341X -
Akira Nishii
Masters Student in Biomedical Data Science, admitted Autumn 2024
Current Research and Scholarly InterestsI'm interested in the challenges that arise in healthcare and biomedicine when applying machine learning to data-scarce and safety-critical settings. This broad interest motivates me to work on topics surrounding self-supervised learning and synthetic data.
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Humaira Noor
Postdoctoral Scholar, Biomedical Informatics
BioDr. Humaira Noor is a postdoctoral researcher in the Gevaert Lab with a PhD in glioma genomics from University of New South Wales, Australia. Her expertise spans biomarker discovery, with particular emphasis on prognostic and molecular determinants of glioma treatment-response, radiogenomic model development for early high-risk patient stratification, and the integration of multi-omics and biomedical imaging to advance precision oncology
