Stanford University
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Deborah L. Narh
Postdoctoral Scholar, Biology
BioDeborah earned her MSc in Biotechnology from Wageningen University and her PhD in Biotechnology from the University of Pretoria, where her research centered on mechanisms employed by Armillaria species for iron homeostasis using a multi-omics approach. She was a 2014 Laureate of the African Women in Agricultural Research and Development (AWARD) Fellowships, a 2016 Agropolis Fondation Fellow at the Laboratoire des Symbioses Tropicales & Mediterraneennes, and a 2018 Fellow of the Norman E. Borlaug International agricultural Science and Technology Fellowship Program at Michigan State University. Currently, her work in the Peay Lab focuses on the impacts of abiotic factors on pine and pine-associated microbiomes using various indicators. She also aims to understand how individual species of ectomycorrhizal fungi respond to environmental stress including temperature and drought at the molecular level, using a multi-omics approach. In addition to her research, Deborah is deeply involved in mentoring young scientists and is committed to using collaborative, interdisciplinary approaches to addressing scientific challenges.
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Rohollah Nasiri
Postdoctoral Scholar, Radiation Physics
Current Research and Scholarly InterestsMy current research focuses on developing tumor-on-a-chip models for preclinical radiation therapy research.
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Fateme (Fatima) Nateghi
Postdoctoral Scholar, Biomedical Informatics
BioAs a postdoc researcher at the Division of Computational Medicine, 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. -
Shaghayegh Navabpour
Postdoctoral Scholar, Psychiatry
Current Research and Scholarly InterestsMy research investigates how genetic, transcriptomic, and epigenomic mechanisms shape brain function and contribute to psychiatric disorders, with a special focus on PTSD. By combining large-scale human genomic data with molecular neuroscience approaches, I aim to identify cell-type-specific pathways and therapeutic targets that advance our understanding and treatment of mental health conditions.
