School of Medicine


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  • Minhaj Nur Alam

    Minhaj Nur Alam

    Postdoctoral Research Fellow, Biomedical Data Sciences

    Bio I am a Postdoctoral Scientist at the Stanford Department of Biomedical Data Sciences, with a research focus on Medical AI/ML applications and quantitative image processing (Ophthalmology and Radiology). I have extensive experience in quantitative image biomarker development and incorporating machine learning algorithms for computer aided diagnosis/classification in Ophthalmology and Radiology. I hold a PhD in Bioengineering (CV/AI applications in Ophthalmology) from University of Illinois at Chicago.

  • Roxana Daneshjou

    Roxana Daneshjou

    Clinical Scholar, Dermatology

    Bio I am interested in bridging new technologies such as genomics and machine learning with clinical medicine. I am also interested in the use of Twitter for scientific communication and medical education. I am on Twitter: @RoxanaDaneshjou.

  • Florian Dubost

    Florian Dubost

    Postdoctoral Research Fellow, Biomedical Data Sciences

    Bio My research objectives are focused on the development of artificial intelligence technologies for neurology research. My graduate training revolved around medical engineering and offered me a multidisciplinary advanced education in computer science, physics, mathematics, biology, and chemistry. As I was progressing towards the start of my PhD, I decided to develop my expertise in machine learning— a type of artificial intelligence—and neurology, working for example on the automatic classification of fMRI signals of the auditory cortex under the supervision of Dr. Takerkart during my studies in Centrale Marseille, France. In Germany, I strengthened my expertise in machine learning in Prof. Navab's chair and developed and published an automated method for the segmentation of medical images based on Markov Chain Monte Carlo. During my PhD in the Netherlands, I focused on deep learning and neurology and developed methods for weakly supervised learning, regression neural networks, and brain lesion detection and quantification from MRI. One of my major contribution is my work on the automated quantification and detection of enlarged perivascular spaces—a type of brain lesion related to cerebral small vessel disease. During my PhD, I visited Prof. Rost group at MGH, Harvard Medical School, to strengthen my expertise in neurology research, and developed and published deep learning registration methods for clinical brain MRI. I am now doing my postdoctoral training in Prof. Daniel Rubin's group at Stanford with the additional supervision of the neurologist Prof. Lee-Messer. I am developing deep learning methods to detect and predict seizures from EEG and video recordings of epileptic patients.

  • Alexander Ioannidis

    Alexander Ioannidis

    Postdoctoral Research Fellow, Biomedical Data Sciences

    Bio Alexander Ioannidis (PhD, MPhil) graduated summa cum laude from Harvard University in Chemistry and Physics and earned an M.Phil in Computational Biology and Diploma in Greek from the University of Cambridge. His Ph.D. from Stanford University was in Computational and Mathematical Engineering, where he teaches machine learning and data science. He also has an M.S. in Mgmt. Sci. and Eng. (Optimization) from Stanford. Prior to Stanford, he worked in superconducting computing logic and quantum computing 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 genomics and population genetics.

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    I work 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 history and population genetics, including work with native communities. As the grandson of Cappadocian refugees expelled from their native land, I try to engage with the complex sentiments of displaced indigenous 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 dispossession. Combined alongside a dialogue with native communities, however, genetics can play a small role in helping to reclaim ancestral stories and dispersed ancestral connections. I hope our work in this area plays a constructive role in that process.

    As written by the poet Rumi in the language of the Cappadocians (Rûm),
    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]

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