Peng Li
About Peng Li
Peng Li is a Staff Scientist specializing in Bioinformatics at the National Institutes of Health, where he has worked since 2012. He has a strong background in software development and data mining for biological data, with advanced degrees in Computer Science and Computational Science.
Current Role at National Institutes of Health
Peng Li serves as a Staff Scientist in Bioinformatics at the National Institutes of Health (NIH) in Bethesda, Maryland. He has held this position since 2012, contributing to the field for over a decade. His work focuses on supporting molecular immunology and genomics through the development of innovative software solutions. His expertise in bioinformatics plays a crucial role in advancing research initiatives at NIH.
Previous Experience at National Institutes of Health
Prior to his current role, Peng Li worked at the National Institutes of Health as a Research Fellow in Bioinformatics from 2010 to 2012. He also served as a Visiting Fellow at NIH for 11 months in 2009 to 2010. During these periods, he developed skills in bioinformatics and contributed to various research projects, enhancing his knowledge and experience in the field.
Education and Expertise
Peng Li holds a PhD in Computational Science from The University of Southern Mississippi, where he studied from 2005 to 2009. He also earned a Master's degree in Computer Science from Xidian University, completing his studies from 2002 to 2005. Additionally, he obtained a Bachelor's degree in Computer Science from the same institution from 1998 to 2002. His educational background provides a strong foundation for his specialization in the analysis of next-generation sequencing data and other genome-wide assays.
Previous Work Experience
Before joining NIH, Peng Li worked as a Research Assistant and Graduate Student at the University of Southern Mississippi from 2005 to 2009. He also had a brief tenure as a Software Developer at Hanna Strategies (AutoDesk R&D) in Shanghai, China, in 2005. In these roles, he developed software products and data mining technologies tailored for high-throughput biological data, which contributed to his expertise in bioinformatics.