School of Medicine
Showing 71-80 of 148 Results
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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). -
Junming Seraphina Shi
Postdoctoral Scholar, Radiation Biology
BioI am a postdoctoral fellow at Stanford University, jointly mentored by Dr. Mohammad Shahrokh Esfahani and Dr. Md Tauhidul Islam. My research focuses on developing robust statistical machine learning methods for noninvasive, cost-effective cancer diagnostics, with applications in early detection, treatment monitoring, and precision oncology.
I received my Ph.D. from UC Berkeley, where my dissertation centered on advancing biostatistical machine learning approaches for complex biomedical challenges. My work addressed causal inference for continuous treatments, bias and measurement patterns in ICU electronic health records, and deep learning–based biclustering and prediction of cancer-drug responses. Across these projects, I developed interpretable and scalable tools for analyzing high-dimensional, multimodal clinical data.
At Stanford, I continue to build novel statistical learning frameworks tailored to real-world clinical needs—particularly through the analysis of liquid biopsy (cell-free DNA) and cancer imaging data. My current work aims to improve cancer detection and monitoring, with a focus on noninvasive, accessible, and clinically meaningful solutions to pressing challenges in oncology. I enjoy interdisciplinary collaborations and working across fields to drive innovation in biomedical research. Deeply committed to cancer research, I aim to bridge rigorous computational methodology with patient-centered impact by designing tools that are scalable, equitable, and translational. -
Palca Shibale
Postdoctoral Scholar, Plastic and Reconstructive Surgery
BioShibale, Palca is a post-doctoral fellow in the Hagey Laboratory under mentorship of Dr. Derrick Wan and Michael Longaker. She earned her BS in Molecular and Cellular Biology at the University of Washington (UW), her MS in Medical Physiology and Biophysics at Case Western University and her MD from UW. She has previously conducted translational research on drug efficacy and clinical research in trauma and vascular surgery. Her current works focus on understanding the mechanisms of tissue regeneration and fibrosis with nano materials and as well, the roles of fibroblast subpopulations in the foreign body response model
