Stanford University
Showing 201-220 of 362 Results
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Wen-yang Lin
Postdoctoral Scholar, Genetics
Current Research and Scholarly InterestsThe broad goal of my research interest is to identify intrinsic and extrinsic mediators of tumor growth and plasticity. My past research experiences will synergize with the expertise of Dr. Monte Winslow’s laboratory to allow the discovery of novel mechanisms of cancer progression. The integration of our molecular measurements with multiple types of ‘omics’ data will ultimately improve the diagnostic precision medicine.
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Xiangping Lin
Postdoctoral Scholar, Genetics
BioXiangping Lin, Ph.D., is a Postdoctoral Scholar at Stanford University. He received his Ph.D. in Chemistry from Sorbonne Paris North University, Paris. Dr. Lin’s research focuses on analytical chemistry, especially mass spectrometry (Orbitrap, Q-TOF, QqQ) and NMR-based omics studies. These include, but are not limited to, metabolomics, exposomics, lipidomics, and the application in biomedical and environmental research, such as metabolism, liver disease, cancer, environmental chemicals exposure biomarkers. In addition, he has extensive experience in multivariate statistics (PCA, PLS-DA, et cetera.), variable selection (logistic regression, LASSO regression, et cetera.), and R programming. In his free time, he enjoys going to the gym, playing badminton (he organizes the Stanford postdoc badminton club), swimming, fitness, cuisine, traveling, and spending time with family and friends.
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Lorraine Ling
Postdoctoral Scholar, Genetics
Current Research and Scholarly InterestsMy research focuses on the cell biology and biochemistry underlying the symbiotic relationship between corals and their partners, microscopic algae of the genus Symbiodinium. The algae live in the coral's gut tissue and provide its host products of photosynthesis while the coral provides inorganic carbon, nitrogen, and a safe habitat. I'm investigating the signaling pathways involved in 1) recognizing the correct algae partner 2) transfer of nutrients between the two.
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Joseph (Joe) Lipsick
Professor of Pathology and of Genetics
Current Research and Scholarly InterestsFunction and evolution of the Myb oncogene family; function and evolution of E2F transcriptional regulators and RB tumor suppressors; epigenetic regulation of chromatin and chromosomes; cancer genetics.
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Xin Liu
Basic Life Science Research Scientist, Genetics
BioXin Liu is a postdoctoral Research Scientist in the Department of Genetics at Stanford University. Xin holds a PhD in Chemistry from the University of Michigan, Ann Arbor. Her basic research interests include RNA and protein biochemistry, enzymology, cancer immunology, and autoimmune disease. She has published papers in several prestigious journals in the field of biochemistry, including Nature Communications, Journal of American Chemical Society, and Nucleic Acids Research. The highlight of her multidisciplinary research includes the development of high-throughput enzymatic methods to discover anti-microbial agents and to reveal mechanisms behind human mitochondrial diseases, as well as innovative applications of genome engineering and machine-learning to decode principles of RNA editing in human cells. Her current research focuses on the mechanistic study of innate immune pathways.
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Romain Lopez
Affiliate, Genetics
Visiting Postdoctoral Scholar, GeneticsBioSince Fall 2021, I am a joint postdoctoral scholar at Stanford University and Genentech Research and Early Development, hosted by Jonathan Pritchard and Aviv Regev. I recently obtained my PhD degree from the department of Electrical Engineering and Computer Sciences at UC Berkeley, advised by Mike Jordan & Nir Yosef. My research interests lie at the intersection of statistics, computation and modeling with a focus on biological applications.
A significant part of my research is driven by building more statistically accurate and faster machine learning software for analyzing single-cell omics data. I developed single-cell Variational Inference (scVI), a flexible model and a scalable inference method for comprehensive analysis of single-cell transcriptomes. I co-developed scvi-tools, an open-source software suite for fully-probabilistic modeling of single-cell multi-omics data. You may learn more about these topics in my guest lecture of the Deep Learning in the Life Sciences class at MIT.
More generally, I am interested in the broader area of ML + Science. Deep generative models provide an appealing and flexible paradigm for learning distributions, but quite some work is needed to fully exploit them as part of a scientific hypothesis testing pipeline (e.g., causality, interpretability, disentanglement, decision-making).
Previously, I worked on counterfactual inference and offline policy learning methods in collaboration with technology companies. In 2018, I visited Le Song at Ant Financial in Hangzhou. In 2019, I visited Inderjit Dhillon at Amazon in Berkeley. Before graduate school, I obtained a MSc in applied mathematics from Ecole polytechnique, Palaiseau in 2016. Additionally, I worked as an intern at the Harvard Medical School with Allon Klein in 2016. I was born and grew up in Bedarieux, France.
