Stanford University
Showing 1-50 of 206 Results
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Ruohan Xia
Postdoctoral Scholar, Psychiatry
BioRuohan's research centers around understanding the genetic and environmental mechanisms supporting infants' and young children's socioemotional development through the lens of developmental cognitive neuroscience. Her PhD research focused on uncovering he neural and caregiver correlates on infants' emotion-perception neural circuitry during live interactions in typically developing children using electroencephalogram (EEG). At Stanford, she is pursuing research questions using a combination of magnetic resonance imaging (MRI) and EEG to identify the endophenotype of the neural anatomy and function in children with rare genetic conditions such as neurofibromatosis type 1 (NF1) and Noonan Syndrome (NS) differ from typically developing counterparts, and explore how such neural differences may lead to unique developmental trajectory of social communication.
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Yan Xia
Professor of Chemistry
Current Research and Scholarly InterestsPolymer Chemistry, Microporous Polymer Membranes, Responsive Polymers, Degradable Polymers, Polymers with Unique Mechanical Behaviors, Polymer Networks, Organic Electronic Materials
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Jinxi Xiang
Postdoctoral Scholar, Radiation Physics
Current Research and Scholarly InterestsI develop machine leanring methods to autonomate the digital pathology.
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Tiange Xiang
Ph.D. Student in Computer Science, admitted Autumn 2022
BioTiange Xiang is a Ph.D. student in Computer Science at Stanford University, where he is a member of the Stanford AI Lab (SAIL) and Stanford Vision and Learning Lab (SVL). His research interests include machine learning and computer vision in general. He received a bachelor's degree in Computer Science and Technology (Advanced)(Honors) from the University of Sydney, where he was awarded Honors Class I and the University Medal.
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Haopeng Xiao
Assistant Professor of Biochemistry
Current Research and Scholarly InterestsWe develop mass spectrometry (MS)-based chemical systems biology approaches, combined with machine learning and biochemistry, to uncover the molecular mechanisms of metabolic regulation in physiology and disease. In parallel, we systematically investigate the ligandability and druggability of the human proteome, providing a foundation for the discovery of new therapeutic strategies for aging, metabolic disease, and cancer.
