School of Medicine
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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. -
Mengxiong Wang
Postdoctoral Scholar, Radiation Biology
Current Research and Scholarly Interests1. To investigate the role of p53 in regulating the regression of lung adenocarcinoma and tumor microenvironment.
2. To determine synthetic lethal partner for p53 mutations in the context of lung adenocarcinoma. -
Jiangbin Ye
Assistant Professor of Radiation Oncology
Current Research and Scholarly InterestsOne hallmark of cancer is that malignant cells modulate metabolic pathways to promote cancer progression. My professional interest is to investigate the causes and consequences of the abnormal metabolic phenotypes of cancer cells in response to microenvironmental stresses such as hypoxia and nutrient deprivation, with the prospect that therapeutic approaches might be developed to target these metabolic pathways to improve cancer treatment.
