School of Medicine
Showing 1-10 of 16 Results
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Kat Adams Shannon
Postdoctoral Scholar, Psychology
BioKat studies how young children adapt their attention and learning behaviors to best match different early environments, with particular focus on understanding variability and strengths in contexts of early adversity. A key aim of her research is to create and collaborate on innovative uses of technology and statistical methods to support education and developmental science.
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Sushruta Surappa
Postdoctoral Scholar, Radiology
BioSushruta Surappa is a postdoctoral researcher at the Canary Center for Early Cancer Detection at Stanford University. His current research focuses on developing various MEMS-based tools for the separation and capture of extracellular vesicles for medical diagnostics. Sushruta received his MS (‘15) and PhD (‘21) degrees in Mechanical Engineering from Georgia Institute of Technology, where he developed a new class of nonlinear MEMS transducers with applications in wireless power transfer, sensing and energy harvesting. He is passionate about developing low-cost, miniature technologies for medical diagnostics and is a keen proponent of science communication.
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Xiwei She
Postdoctoral Scholar, Neurology and Neurological Sciences
BioDr. Xiwei She is a postdoctoral scholar in the Department of Neurology. He received his B.S. degree in Computer Science from Shanghai Jiao Tong University in 2013, and his M.S. degree in Biomedical Engineering from Zhejiang University in 2016. Worked as a research assistant at the USC Neural Modeling and Interface Laboratory, he received his Ph.D. degree in Biomedical Engineering from the University of Southern California in 2022. After graduation, he joined Stanford University as a postdoctoral scholar at the Pediatric Neurostimulation Laboratory (Baumer Lab) and Wu Tsai Neuroscience Institute.
His research interests are largely directed toward identifying the causal relationship of neurons/brain regions and understanding how information is encoded in neural signals by employing machine learning models. Specifically, his postdoc research focuses on applying machine learning modeling techniques on EEG and TMS-EEG data to better understand the impact of interictal epileptiform discharges (IEDs) on brain activity in children with childhood epilepsy with centrotemporal spikes (CECTS).
