School of Medicine
Showing 101-177 of 177 Results
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Liam Edward Mulhall
Software Developer, Biomedical Data Science
Current Role at StanfordLiam develops and maintains the HLA Curation Interface, a tool that supports the assessment of HLA alleles and haplotypes for use in precision medicine and research. He also works on internal tools used by the Stanford ClinGen team.
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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. -
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
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Marcus Oehlrich, PhD
Masters Student in Biomedical Data Science, admitted Autumn 2025
BioI am a Professor of Finance, Accounting, and Taxation at accadis University of Applied Sciences in Bad Homburg, Germany, and I advise on startups, business valuation, and corporate finance. My consulting projects range from small startups in biotechnology and M&A transactions in the pharmaceutical and biotech sectors to the preparation of the business plan for the IPO of an international music and movie production group.
During my business studies, I became interested in law and medicine (especially cancer research), which is why I continued my education in these fields (including a Master of Science in Pharmaceutical Medicine, a Certificate in Pharmaceutical Law, and an MPH at Harvard T.H. Chan School of Public Health). Subsequently, I have started the M.S. in Biomedical Data Science at the Department of Biomedical Data Science at Stanford University School of Medicine.
I also had the privilege of serving as the CEO of the Institute for German, European, and International Medical Law, Health Law, and Bioethics of the Universities of Heidelberg and Mannheim (IMGB) from 2005 to 2011. At accadis University of Applied Sciences, I am Head of the Health Care Management Research Group and responsible for the Master of Arts in International Health Care Management. From 2010 to 2020, I served as the Honorary Consul of the Republic of San Marino in Frankfurt, Germany.
Most of my publications (12 books and more than 70 articles) are related to business topics. However, I also authored three books on cancer "Internetkompass Krebs [Internet compass cancer]" (Springer 2001), "Recombinant humanized monoclonal antibody Trastuzumab for the treatment of metastatic breast cancer with tumors overexpressing the HER2/neu proto-oncogene: A systematic review" (dissertation.de 2003) and "Krebs vorbeugen und bekämpfen [Preventing and combating cancer: All about prevention, early detection, therapy]" (Reader's Digest 2012). The latter was translated into Polish, Czech, Croatian, Slovenian, and Hungarian. -
Soumyadeep Roy
Postdoctoral Scholar, Biomedical Informatics
BioI am a postdoctoral scholar at the Center for Biomedical Informatics Research of Stanford University, advised by Prof. Tina Hernandez-Boussard.
My primary area of research is natural language processing, with expertise in medical and healthcare applications. My research areas of interest are Foundation Models for Medicine, Generative AI, Text Summarization, and Efficient Pretraining.
I hold a PhD in Computer Science and Engineering from the Indian Institute of Technology Kharagpur, where I worked with Prof. Niloy Ganguly and Prof. Shamik Sural. Here, I was part of the Complex Networks Research Group (CNeRG). My PhD thesis is titled “Domain Adaptation for Medical Language Understanding”, where I developed novel domain adaptation techniques to effectively and efficiently adapt open-domain AI models to the medical domain.
In summary, I have six years of experience working with medical NLP data, which includes clinical trial registry data (2018-2021), medical forum questions (2020-2021), DNA sequence data (2021-2024), biomedical scientific literature (2023 - 2025), clinical data (2021-2023) and EHR clinical notes (2025). My medical AI research experience includes 2.5 years at L3S Research Germany collaborating with Hannover Medical School as well as a 7-month research internship at GE HealthCare Technology and Innovation Center (HTIC) in Bangalore, India. I also presented a tutorial on March 10, 2025 titled "Building Trustworthy AI Models for Medicine" at WSDM 2025 held in Germany.
In my free time, I like hiking, and playing chess or table tennis. -
Erica Marie Rutherford
Data Wrangler, Biomedical Data Science
BioMy career spanning nine years as a data curator has given me a lot of experience and perspective into the workings of scientific data and metadata, and its organization. During my time before graduate school, I attained experience on a variety of fieldwork projects in ecology (2008-2013). During these temporary seasonal assignments, the importance of precision and care in data collection was impressed in me. When I went to graduate school at San Francisco State University (2013-2016), I gained experience in all parts of a molecular biology experiment, from fieldwork to labwork to data analysis. After graduation, I worked at a microbiome focused startup company, Second Genome, as their data curator (2016-2021). While there, I was responsible for curation of metadata for both internal studies for R&D and for clients, and for external studies being brought in for our internal Knowledgebase. While there, I developed an appreciate for ontologies, and developed a custom Second Genome Ontology to handle our metadata. I moved on to the Lattice group, located at Stanford University, where I continued to expand my skills in data curation (2021-present). I have gained experience in handling single cell datasets and their associated metadata, and curating them to meet precise standards. I strive to work collaboratively with data contributors in order to ensure FAIR data standards.
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Katrin Sangkuhl
Scientific Data Curator, Biomedical Data Science
Current Role at StanfordSenior Scientific Curator
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Andrew Shen
Ph.D. Student in Biomedical Data Science, admitted Autumn 2025
BioHi, my name is Andrew! I’m a current PhD student in Biomedical Data Science and an NSF Graduate Research Fellow. I am broadly interested in solving problems at the intersection of AI and science, but particularly in the areas of biology and medicine. Before my PhD, I worked at Harvard Medical School with Marinka Zitnik on developing machine learning methods for medicine and science.
Feel free to reach out to connect! -
John S. Tamaresis, PhD, MS
Biostatistician, Biomedical Data Science
BioDr. Tamaresis joined the Stanford University School of Medicine in Summer 2012. He earned the Ph.D. in Applied Mathematics from the University of California, Davis and received the M.S. in Statistics from the California State University, East Bay. He has conducted research in computational biology as a postdoctoral scholar at the University of California, Merced and as a biostatistician at the University of California, San Francisco.
As a statistician, Dr. Tamaresis has developed and validated a highly accurate statistical biomarker classifier for gynecologic disease by applying multivariate techniques to a large genomic data set. His statistical consultations have produced data analyses for published research studies and analysis plans for novel research proposals in grant applications. As an applied mathematician, Dr. Tamaresis has created computational biology models and devised numerical methods for their solution. He devised a probabilistic model to study how the number of binding sites on a novel therapeutic molecule affected contact time with cancer cells to advise medical researchers about its design. For his doctoral dissertation, he created and analyzed the first mathematical system model for a mechanosensory network in vascular endothelial cells to investigate the initial stage of atherosclerotic disease. -
Caroline Thorn
Scientific Data Curator 2, Biomedical Data Science
Current Role at StanfordScientific curator at ClinPGx
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Ryan Whaley
Technical Lead, Biomedical Data Science
Current Role at StanfordRyan is a software developer in the Department of Genetics and a co-technical lead of the PharmGKB. He is a Java developer with a background in database administration and project management and has been with the PharmGKB since 2007.
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Bo Xiong
Postdoctoral Scholar, Biomedical Informatics
Current Research and Scholarly InterestsAI, Foundation Models, Biomedical Data Science
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Harrison G. Zhang
MD Student, expected graduation Spring 2028
Ph.D. Student in Biomedical Data Science, admitted Autumn 2025
MSTP Student
Grad Student, Institute for Human-Centered Artificial Intelligence (HAI)BioHarrison is an MD-PhD student at Stanford University advancing precision medicine and global health using machine learning and genomics. He studied statistics and biology at Columbia University, where he was elected to Phi Beta Kappa and awarded Magna Cum Laude with Highest Honors in Field for his academic achievements.
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Weiruo Zhang
Affiliate, Biomedical Data Science
BioDr. Zhang is currently a research engineer at the Department of Biomedical Data Science, and the data manager in the Center for Cancer Systems Biology at Stanford. Dr. Zhang completed her M.S. and Ph.D. in Electrical Engineering, both from Stanford University. Her Ph.D. studies focused on developing machine learning (ML) algorithms for metabolomics data analysis using graph theory. She received Young Scientist Award from the Metabolomics Society for her algorithm on metabolic network analysis delineating the effects of genetic mutants and drug treatment on the metabolome. Her postdoctoral studies at the Department of Radiology, Stanford School of Medicine, integrated radiomic, genomic, transcriptomic, histopathologic and clinical data that identified a prognostic metabolic regulation biomarker for non-small cell lung cancer. She has developed open-source computational tools that have been appreciated by the broad research community and industry, including the CELESTA algorithm which has been incorporated into commercial analytical platform of NanoString. Dr. Zhang's research has made significant impacts in the fields of spatial multi-omics and cancer systems biology, and she has authored and co-authored publications including Cell, Nature Methods, Nature Communications etc.
Dr. Zhang's current research at Stanford primarily focuses on developing and implementing ML/AI approaches to integrate and analyze multi-modality data, including spatial multi-omics, radiologic imaging, histopathologic images and clinical data. Her research aims at bridging the gap between underlying disease molecular/cellular biology and clinical assessment to improve diagnostics, prognostics and treatment strategies. -
Yihan Zhao
Masters Student in Biomedical Data Science, admitted Autumn 2024
Bio* Part-time Adult, Lover for Hiking, Photograph, Jazz, Surfing, Pool
* AI4Health
* How Human make better AI? How AI make better Human?
* I want to make: Anticancer Drugs, Contraceptive for Male, Artificial Womb, Weight Loss Pills
Don't create opium, create a forest, create air and water
