School of Medicine

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  • Alexander Ioannidis

    Alexander Ioannidis

    Postdoctoral Research Fellow, Biomedical Data Sciences

    Bio Alexander 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),
    ???? ??? ???????? ???? ?? ?????
    ?Tell me what happened to you, tell me what you have lost.?
    [Rumi; Konya ms 67; translit. ?? ?? ?? ??????, ?? ?? ?? ??????]

  • Bibek Paudel

    Bibek Paudel

    Postdoctoral Research Fellow, Biomedical Data Sciences

    Bio I am a Postdoctoral Research Fellow at the Department of Biomedical Data Science. My research focuses on developing machine learning and statistical models to solve problems that are inter-disciplinary in nature, including those from the biomedical, ecological, and socio-political sciences. I received my Ph.D. in Computer Science from University of Zurich, Switzerland in 2019, where I developed new algorithms to improve recommendation diversity and algorithmic fairness. I used graph theory, deep learning, and latent-factor models to build documents representations, explainable knowledge base embeddings, and personalization systems. At Stanford, I am building new machine learning models for personalized medicine by combining biological domain knowledge and large heterogeneous datasets. My research spans both ends of the biomedical data spectrum: from single-cell observations to population health data. I am particularly interested in examining the disparate health impacts of environmental factors on vulnerable and minority populations and in understanding how these findings can guide policy interventions.

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