School of Medicine
Showing 181-200 of 1,564 Results
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Xi Ying Amanda Chen
Postdoctoral Scholar, Stem Cell Transplantation
BioDr. Chen completed a Bachelor of Science (Honours) at the University of Sydney (NSW, Australia), with majors in Molecular Biology and Immunobiology. She graduated with the University Medal for her Honours research project where she investigated the novel role of DNA damage repair machinery on telomerase recruitment to telomeres. She then undertook her graduate studies at the Peter MacCallum Cancer Centre (The University of Melbourne, VIC, Australia) in the Beavis laboratory, where she developed a CRISPR knock-in strategy to engineer armored CAR T cells to express therapeutic payloads in a tumor-restricted manner. She joined the Porteus laboratory in the Department of Pediatrics at Stanford University in March 2025, where she is developing strategies to enhance gene-edited hematopoietic stem cell transplantation.
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Tianqi Chen
Postdoctoral Scholar, Oncology
BioMy research interest lies in liquid biopsy and early cancer diagnostics, e.g. development of bioassay for detection of cancer biomarkers (proteins and genes) and single-cell research. As well as the integration of 3D-printed microfluidics.
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Wenting Chen
Postdoctoral Scholar, Radiation Physics
BioI am currently a Postdoc Fellow in the Department of Radiation Oncology of Stanford University, advised by Prof. Lei Xing. Before joining Stanford, I obtained my Ph.D degree in the Department of Electrical Engineering, City University of Hong Kong, supervised by Prof. Yixuan YUAN, Prof. W.S Tommy Chow, and Prof. L.H. Leanne Chan. I visited Massachusetts General Hospital and Harvard Medical School, supervised by Prof. Xiang Li and Prof. Quanzheng Li. Before that, I received the B. Eng and M. Eng degree from College of Computer Science and Software Engineering in Shenzhen University of China in 2017 and 2020, supervised by Prof. Linlin Shen. From Dec. 2019 to Nov. 2020, I had interned in Tencent Jarvis Lab, supervised by Dr. Shuang Yu and Prof. Yefeng Zheng.
My research interests lie in vision-language model, multi-modal large language model, generative AI, computer vision and their applications on medical AI, with a focus on report generation, medical image synthesis, endoscopy super-resolution, retinal image segmentation, multi-modality diagnosis, etc. -
Yiyun Chen
Postdoctoral Scholar, Stanford Cancer Institute
BioYiyun Chen, Ph.D. is a Postdoctoral Fellow at Professor Crystal Mackall’s group at Stanford Cancer Institute.
Dr. Chen studied biochemistry and structural biology in her undergraduate and master trainings at The Hong Kong University of Science and Technology, where she eventually obtained her Ph.D. degree in computational biology under the supervision of Professor Jiguang Wang. During her Ph.D. training, she has developed her skill sets in analyzing and integrating various types of patient-derived sequencing data, published three first-author and four co-author papers, and received two awards for top postgraduate students. Through interdisciplinary collaborations with cancer biologist and clinicians in US and Asia, her work has uncovered tumor-specific immune cell subtypes and novel noncoding RNAs and generated new insights into precision medicine in glioma, lymphoma and gastric cancer.
Applying her expertise in computational cancer biology and immunology, her current research is focused on identifying molecular mechanisms that contribute to the clinical outcomes of patients undergoing CAR-T immunotherapy. At Mackall Lab, she will contribute to tailoring computational pipelines for profiling the spatiotemporal dynamics of the tumor and immune microenvironment and translate new discoveries into cancer therapeutics. -
Jordan C. Cheng, DMD, PhD
Postdoctoral Scholar, Stanford Cancer Institute
Current Research and Scholarly InterestsMy research direction involves the evalutation of single-stranded library prepartion methods versus conventional double-stranded methods of cell-free DNA for non-invasive cancer profiling applications. The exploration of these technologies allow for the inference of the genomic and epigenetic features of both local and distant cell types associated with a biofluid.
