Dr. Jun Li joined the City University of Hong Kong in February 2018 as an Assistant Professor in Bioinformatics.
He graduated from Tianjin University with a bachelor's degree in physics and then joined Beijing Genomics Institute (BGI) in Beijing in 2003. In BGI, he was trained as a bioinformatician and served as senior project leader for over 3 years, leading a team focused on comparative genomics, evolution, and population genetics.
He received his Ph.D. degree from the University of Hong Kong (HKU) in 2013 under the supervision of Prof. Frederick Leung, working in the fields of comparative genomics/transcriptomics for viruses and bacteria. Afterward, he joined the lab of Dr. Gianni Panagiotou as a postdoctoral researcher at HKU and the Hans Knoll Institute in Germany, studying the microbiome of humans and animals and various other environments.
Dr. Li is interested in developing mathematical models and using computational skills to analyze multi-omics, structural and phenotypic data to understand the intrinsic nature of the biological processes and dynamics, especially in the field of health-related microbiome and drug development.
Dr. Jun Li joined the City University of Hong Kong in February 2018 as an Assistant Professor in Bioinformatics.
He graduated from Tianjin University with a bachelor's degree in physics and then joined Beijing Genomics Institute (BGI) in Beijing in 2003. In BGI, he was trained as a bioinformatician and served as senior project leader for over 3 years, leading a team focused on comparative genomics, evolution, and population genetics.
He received his Ph.D. degree from the University of Hong Kong (HKU) in 2013 under the supervision of Prof. Frederick Leung, working in the fields of comparative genomics/transcriptomics for viruses and bacteria. Afterward, he joined the lab of Dr. Gianni Panagiotou as a postdoctoral researcher at HKU and the Hans Knoll Institute in Germany, studying the microbiome of humans and animals and various other environments.
Dr. Li is interested in developing mathematical models and using computational skills to analyze multi-omics, structural and phenotypic data to understand the intrinsic nature of the biological processes and dynamics, especially in the field of health-related microbiome and drug development.