School of Medicine
Showing 1-11 of 11 Results
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Mahesh Pandit
Postdoctoral Scholar, Immunology and Rheumatology
BioI have completed my PhD in Immunology from Yeungnam University, South Korea. I studied adaptive immune cells especially focusing T cells and its relation to autoimmunity and tumor. I worked on different conditional knockout mice to investigate the cellular mechanisms. Similarly, I worked on disease induced mice to study its preventive and therapeutic approaches. Currently, I am working on Translational immunology as a Postdoctoral Researcher at Stanford University department of Immunology and Rheumatology. I focus on Epstein-Barr Virus, B cells and its relation with various autoimmune diseases.
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Jaspreet Pannu
Postdoctoral Scholar, General Internal Medicine
BioJassi Pannu, MD is a Physician and Fellow within Stanford University's School of Medicine.
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Shiva Pathak
Postdoctoral Scholar, Bone Marrow Transplantation
BioResearch interests: Type 1 Diabetes, Islet Transplantation, Bone Marrow Transplantation, Mesenchymal Stem Cells, Biomaterials.
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Ruoxi Pi
Postdoctoral Scholar, Infectious Diseases
BioI received my BS in Biological Sciences in Zhejiang University in China, where I conducted research in polyphasic taxonomy in anaerobic bacteria. I received my PhD in Yale University, where I studied the early events of retrovirus infection in animal models. Now in the Blish lab, I am investigating NK cell responses during HIV-1 infection and trying to manipulate the NK cells to target latently infected cells.
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Malvika Pillai
Postdoctoral Scholar, Biomedical Informatics
BioMalvika Pillai is a postdoctoral research fellow in the VA Big Data Scientist Training Enhancement Program (BD-STEP), jointly in Stanford University in Medicine (Biomedical Informatics) in the Boussard Lab and VA Palo Alto. She received her BS in Quantitative Biology and PhD in Health Informatics from the University of North Carolina at Chapel Hill. Her current work focuses on developing, evaluating, and implementing fair artificial intelligence/machine learning (AI/ML) models that can lead to high-quality, patient-centered care.
