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+<WRAP centeralign>##Data Science Seminar##\\ Hosted by the Department of Mathematics and Statistics</WRAP>
+  * Date: Tuesday, November 28, 2023
+  * Time: 12:00-1:00 EST
+  * Room: zoom
+  * Speaker: Dr. Li Zhang  (University of California San Francisco)
+  * Title: NAIR Software: Unlocking the Immune System's Secrets by Network Analysis and Advanced Machine Learning.
+<WRAP center box 80%>
+<WRAP centeralign>**//Abstract//**</WRAP>
+ \\
+Immunotherapy has revolutionized cancer treatment, which depends on the immune system to
+mediate responses. Significant advances have been made through high-dimension sequences to
+dissect the immune responses in patients. T cells play a vital role in our body's immune defence,
+combating cancer. Advanced sequencing technology allows us to delve deeper T-cell receptor
+(TCR) repertoire and gene expression. To better understand the adaptive immune system, we
+have developed the Network Analysis of Immune Repertoire (NAIR) software, utilizing cutting-
+edge statistical approaches and machine learning tools. NAIR constructed sequence networks,
+and more importantly, it can identify critical disease-associated TCR clusters and shared public
+TCR clusters across multiple samples. This reveals potential disease-specific signatures, paving
+the way for targeted therapies. NAIR accommodates both bulk and single-cell sequencing data,
+unravelling insights at cell level. Expanding NAIR's capabilities, we've integrated single-cell
+gene expression data using a Graph deep learning model, offering unprecedented insights into T
+cell functionality. Additionally, NAIR employs an innovative technique to predict binding
+peptides by integrating TCR sequence vectorization, V/J gene and HLA genotype in a deep
+learning framework. Through network analysis, advanced statistics, and deep learning, NAIR
+represents a powerful platform to unlock the complex interplay between adaptive immune
+system, disease progression, and clinical outcomes, advancing our understanding of immune
+system dynamics.. \\
+Biography of the speaker: Dr. Li Zhang is a Professor of Biostatistics in the Department of Medicine, Division of Hematology and Oncology, with a joint appointment in the Department of
+Epidemiology and Biostatistics at the University of California San Francisco (UCSF).
+She obtained her Ph.D. in Statistics from the University of Florida, and before joining
+UCSF, she was an Assistant Professor at the Cleveland Clinic. She has extensive
+experience in applying statistics and developing advanced approaches in biomedical
+research and expertise in cancer research with high-throughput sequencing data
+analysis. She has published more than 150 papers and designed more than 60 Phase
+I and II clinical trial studies. Dr. Zhang also serves on Global Action Plan 6 Project for
+Movember Foundation as the UCSF site PI. She has been or is on multiple NIH, DOD,
+and foundation grants as a co-Investigator. Her research interest focuses on
+Immuno-informatics, and she is currently the PI on NIH R21 and R01 projects
+focusing on cancer Immunoinformatics. In addition to regularly teaching
+Biostatistics and serving on students&#39; master committee at UCSF, she leads the
+UCSF&#39;s Fellowship Advancement and Skills Training in Clinical Research (FASTCaR).
+She also initiated and organizes the annual UCSF cancer center Biostatistics
+workshop, which aims to provide education to scientists, post-docs, and technicians.
+Dr. Zhang is very active member of professional community, she was the president
+of the San Francisco Bay Area Chapter of American Statistical Association (SFASA),
+now serves the Director of Education in SFASA. She is also a member of the
+Pathways To Promotion Committee of ASA Statistical Consulting Section. She received
+outstanding services award from ASA in 2021.
+</WRAP>