School of Medicine
Showing 1-92 of 92 Results
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Shaimaa Bakr
Postdoctoral Scholar, Biomedical Informatics
Masters Student in Biomedical Informatics, admitted Autumn 2020BioShaimaa is a graduate of the Ph.D. program, the Department of Electrical Engineering at Stanford. Shaimaa is a member of the Gevaert and RIIPL labs. Prior to Stanford, Shaimaa received her B.Sc. (Summa Cum Laude) from the American University in Cairo, where she studied Electronics Engineering and Computer Science. She obtained her MS degree in Electrical Engineering from Rensselaer Polytechnic Institute, working in the Cognitive and Immersive Systems lab, and advised by Professor Richard Radke. Shaimaa is interested in applying and developing machine learning methods for medical imaging and molecular data.
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Henry C. Cousins
MD Student, expected graduation Spring 2024
Ph.D. Student in Biomedical Informatics, admitted Autumn 2021
MSTP StudentBioHenry is an MD-PhD candidate and Knight-Hennessy Scholar in the Medical Scientist Training Program and the Biomedical Informatics Program, where he is advised by Professor Russ Altman. He develops machine-learning methods to study the effects of complex genetic variation on human disease mechanisms, with focus on neurological and ophthalmic disorders. His goal is to translate genomic discoveries into disease-modifying therapies.
He received an AB summa cum laude from Harvard University in 2017, where he studied genetic mechanisms of retinal development with Professor Joshua Sanes. He then graduated with an MPhil with distinction from the University of Cambridge as a Gates Cambridge Scholar. He previously worked at Leaps by Bayer and the Massachusetts Eye and Ear Infirmary and has received a number of awards related to research and teaching. -
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.
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Asef Islam
Masters Student in Biomedical Informatics, admitted Winter 2023
Masters Student in Computer Science, admitted Autumn 2022Current Research and Scholarly InterestsAI in medicine and other fields, particularly ML and CV techniques
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Timothy Keyes
MD Student, expected graduation Spring 2024
Ph.D. Student in Cancer Biology, admitted Winter 2018
MSTP Student
Masters Student in Biomedical Informatics, admitted Winter 2021BioTimothy is an MD/PhD student studying cancer biology and biomedical informatics at the Stanford University School of Medicine. He is a joint member of Kara Davis's laboratory in the Department of Pediatrics and Garry Nolan's Laboratory in the Department of Pathology.
As a biomedical data scientist, Timothy's research focuses on the application of machine learning to single-cell data analysis in the context of pediatric leukemia. Through the use of emerging, high-throughout single-cell technologies such as mass cytometry and sequence-based cytometry, Timothy's research is designed to build predictive models of patient outcomes - such as relapse or minimal residual disease (MRD) - at the point of diagnosis. To do so, he uses a variety of computational tools including generalized linear models, clustering, and deep learning. In addition, his work prioritizes constructing easy-to-use, highly-reproducible data analysis pipelines that can be shared as open-source tools for the scientific community.
Outside of science, Timothy has a longstanding interest in human rights and social justice work among members of the lesbian, gay, bisexual, transgender, and queer (LGBTQ+) community. He currently serves as the resident data scientist for the Medical Student Pride Alliance (MSPA), a 501(c)(3) non-profit organization that advocates for diversity, equity, and inclusion for LGBTQ+ medicals students in medical schools across the United States. As a data scientist at MSPA, Timothy analyzes and visualizes data to guide MSPA's strategic decision-making as well as for academic publication. He also advises and mentors other student members of MSPA performing data analysis in Python and R.
In recognition of his accomplishments, Timothy has received several institutional and national award for both research and advocacy. These include a National Research Service Award (NRSA) from the National Cancer Institute, a Junior Leadership Award from the Building the Next Generation of Academic Physicians (BNGAP) LGBT Workforce, Stanford Medicine’s Integrated Strategic Plan Star Award, and a Point Foundation Scholarship. -
Cassie Ann Ludwig, MD, MS (she/her/hers)
Assistant Professor of Ophthalmology (Research/Clinical Trials)
Masters Student in Biomedical Informatics, admitted Autumn 2023Current Research and Scholarly InterestsMy research at present focuses on better understanding high and pathologic myopia and their retina sequelae (retinal detachments, myopic traction maculopathy, myopic macular degeneration) through informatics and data-driven research. My goal is to make discoveries within the field of Ophthalmology that will impact the rest of medicine, taking advantage of our ready access to the only visible portion of the central nervous system.
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Minh Nguyen
Ph.D. Student in Biomedical Informatics, admitted Autumn 2018
Ph.D. Minor, Management Science and EngineeringBio@DARE fellow (Diversifying Academia, Recruiting Excellence) https://vpge.stanford.edu/people/minh-nguyen
@Data Science Scholar
https://datascience.stanford.edu/people/minh-nguyen -
Thodsawit Tiyarattanachai
Masters Student in Biomedical Informatics, admitted Autumn 2023
Current Research and Scholarly Interestsartificial intelligence
medical imaging
ultrasound
screening and surveillance of liver cancer
cancer prediction models
cancer biomarkers