School of Medicine
Showing 1,161-1,180 of 1,566 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
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Mahasish Shome
Postdoctoral Scholar, Genetics
BioDr. Mahasish Shome is interested in understanding the underlying mechanism of disease progression. He uses various omics profiling to identify biomarkers relevant to the disease. He studies antibodies, cytokines, proteins and microbiome profile to decipher the connection of disease with markers. Connecting various omics provide a holistic overview of the disease profile and can help in early diagnosis, understanding disease state and drug/vaccine effectiveness.
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Pilleriin Sikka
Postdoctoral Scholar, Anesthesiology, Perioperative and Pain Medicine
Current Research and Scholarly InterestsWhat makes certain experiences transformative, and how can we harness them to support resilience and mental health? I explore this question by studying emotions across various states of consciousness—waking, dreaming, anesthesia, psychedelics, and meditation. With a background in psychology, neuroscience, and anesthesiology, I bring together methods that are rarely combined: daily diaries and surveys, language and narrative analysis, neurophysiological recordings, lab experiments, and clinical trials. My work has three main aims: (1) to understand how affective experiences unfold across states; (2) to test whether these experiences can be deliberately shaped to support mental health; and (3) to identify the mechanisms that make them transformative. This interdisciplinary approach has led to the first controlled studies of anesthesia-induced dreams for trauma, new insights into peace of mind and emotion regulation, and cross-state comparisons showing how affective experiences in altered states can foster resilience. My long-term goal is to develop a new frontier in affective science: the study of how transformative experiences across different states of mind can improve well-being.
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Benjamin Singer
Member, Maternal & Child Health Research Institute (MCHRI)
BioBen Singer is a postdoctoral scholar with interests in mathematical epidemiology and global public health. Ben's research career began with an internship at the Okinawa Institute of Science and Technology, where he applied quantitative skills he had learnt studying physics at the University of Oxford to the study of nematode locomotion. Ben further pursued quantitative methods in life sciences in the Interdisciplinary Bioscience Doctoral Training Partnership at the University of Oxford, earning a DPhil (PhD equivalent) in mathematical methods for evaluating pandemic risk and control. During these studies he maintained an interest in global public health policy, interning with the UK government's Department for International Development, where he developed models of international COVID-19 vaccine distribution. Ben is now working in Nathan Lo's research group at Stanford, creating infectious disease models informing public health policy for schistosomiasis, hepatitis E, and other infections.
