School of Medicine
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Postdoctoral Research Fellow, Biomedical Data Sciences
BioAlexander graduated from Harvard in Chemistry and Physics and earned an M.Phil in Computational Biology and Diploma in Greek from the University of Cambridge. He has a Ph.D. in Computational and Mathematical Engineering from Stanford, where he teaches machine learning and data science. Prior to Stanford, he worked in superconducting computing research at Northrop Grumman. As a current research fellow in the Stanford School of Medicine (Department of Biomedical Data Science), his work focuses on applying computational methods to problems in human genetics and population history.
I work on methods for creating synthetic genomic data for DNA privacy, as well as on novel algorithm design (particularly ancestry related) for several large-scale genomic studies that aim at understanding genetic causes of disease.
I also focus on projects at the intersection of computational history and population genetics, including work with native communities. As the grandson of Cappadocians expelled from their homeland, I try to engage with the complex sentiments of displaced native peoples in these projects. Pain over the disruption of community heritage and over dispossession from traditional sites often remains raw. If engagement with descendant communities is lacking, research into our past can often feel like a continuation, even a legitimation, of our dispossession. Combined alongside a dialogue with indigenous peoples, however, genetics can play a small role in helping us to reclaim ancestral stories and dispersed community connections. I hope my work in this area plays a constructive role in that process.
As written by the poet Rumi in the language of the Cappadocians (Rum),
پیمی تیِ پَاثیِسْ پیمی تی خاسِس
“Tell me what happened to you, tell me what you have lost.”
[Rumi; Konya ms 67; translit. πε με τι έπαθες, πε με τι έχασες]
John P.A. Ioannidis
C. F. Rehnborg Professor in Disease Prevention in the School of Medicine, Professor of Medicine, of Health Research and Policy (Epidemiology) and by courtesy, of Statistics and of Biomedical Data Science
Current Research and Scholarly InterestsMeta-research
Clinical and molecular epidemiology
Human genome epidemiology
Reporting of research
Empirical evaluation of bias in research
Statistical methods and modeling
Meta-analysis and large-scale evidence
Prognosis, predictive, personalized, precision medicine and health
Sociology of science