Stanford University
Showing 11-20 of 143 Results
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Luwen Wan
Postdoctoral Scholar, Earth System Science
BioLuwen is a Postdoctoral Fellow with the Stanford Institute for Human-Centered Artificial Intelligence, working with Dr. Kate Maher, Professor at Stanford University in the Department of Earth System Science. Her postdoctoral research focuses on developing tools for tracking the recovery and activity of the North American beaver from a computer version and evaluating beaver as a tool for fostering sustainable waterways. She received her Ph.D. in Earth and Environmental Science from Michigan State University, where she worked on nutrient transport modeling across the Great Lakes Basin and agricultural tile drainage mapping across the US Midwest region.
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Bing Wang
Postdoctoral Scholar, Stem Cell Transplantation
BioMy academic training and research experience have equipped me with multidisciplinary skills and knowledge of molecular biology and immunology.
I led two projects when I was an undergraduate, in which I got primary academic learning. My team member and I investigated the bacteria content in drinking water from two types of machines that are commonly used in colleges under the guidance of our experimental microbiology teacher Zhihong Zhong. Secondly, we produced a hybridoma cell line secreting monoclonal antibody against the core antigen of the hepatitis C virus (HCV) to develop an ELISA kit for the detection of HCV under the guidance of Dr. Rushi Liu and Minjing Liao.
Thereafter, as a Ph. D. candidate at Xiaoming Feng’s lab, my research primarily focused on understanding the biology of regulatory T cells (Treg) and CD11c+ myeloid cells using cutting-edge single-cell sequencing and conditional knockout mice under healthy and disease conditions. We first revealed the heterogeneity and bifurcated differentiation pathway of human Tregs from normal donors and transplanted patients at the single-cell transcriptome level. A subsequent first and corresponding author publication identified a key innate responsive protein in CD11c+ alveolar macrophages, NRP2, that protects mice from lung injury via promoting the phagocytosis of neutrophils. I also participated in two projects regarding the role of a serine/threonine kinase, LKB1, in mice CD11c+ dendritic cells from lymphoid tissues and adipose tissue with diet-induced obesity. These academic experiences guided me into a strong passion and independent capacities for biomedical studies.
For my postdoctoral training, I will focus on developing Treg therapies and genetic stem cell therapy to cure patients with IPEX syndrome (a severe autoimmune disease) at preclinical and clinical stages, and other immune disorders. My sponsor Dr. Rosa Bacchetta is a well-known leader in treating IPEX patients and developing Treg therapies. My co-mentor Dr. Maria Grazia Roncarolo is a well-recognized pediatric immunologist and also one of the pioneers in the stem cell and gene therapy field, who discovered the type 1 regulatory T cells or Tr1 cells and translate the scientific discoveries into novel Treg therapies. Both of them have an excellent record of training postdoctoral fellows. The proposed projects will provide me with great opportunities in cutting-edge technology and translational research and outline a set of career development including grant writing, public presentation, and lab management, which will enhance my ability to become an independent investigator and help me to reach my goal of developing efficient and safe Treg therapies for a wide range of immune disorders and associated human diseases. -
Chong Wang
Postdoctoral Scholar, Radiology
BioI am currently a Postdoctoral Scholar in the Department of Radiology at Stanford University School of Medicine, affiliated with the Center for Artificial Intelligence in Medicine and Imaging (AIMI). My research mainly focuses on AI and foundation models in healthcare, with an emphasis on developing trustworthy, robust, and efficient AI solutions for medical imaging. I earned my Ph.D degree, honored with the Doctoral Research Medal, in Computer Science from the Australian Institute for Machine Learning (AIML), The University of Adelaide.
