Mingsi Liao

Mingsi Liao is a Ph.D. candidate in the Genetics, Bioinformatics, and Computational Biology (GBCB) program in the School of Animal Sciences at Virginia Tech, advised by Dr. Rebecca R. Cockrum. She holds a Master of Engineering in Computer Science and Applications from Virginia Tech, a Master of Science in Bioinformatics and Computational Biology from George Mason University, and a Graduate Certificate in Data Analytics.

Her multidisciplinary background integrates computer science, artificial intelligence, and bioinformatics to address fundamental and applied challenges in animal health, management, and genomics. Her research centers on precision livestock farming and livestock genomics. In precision agriculture, she develops machine learning, computer vision, and multimodal frameworks for automated health monitoring and non-invasive phenotypic prediction in dairy calves. In genomics and bioinformatics, her work applies high-throughput sequencing, variant discovery, and microbiome analysis to investigate genetic selection signatures, complex production traits, and host disease resistance mechanisms in livestock populations.

Mingsi’s academic contributions have been recognized with honors including the USDA NRSP-8 Fellowship, multi-year John Lee Pratt Animal Nutrition Fellowships, and a 2nd Place Poster Presentation Award at the Virginia Tech GPSS Research Symposium. She actively publishes peer-reviewed research across smart agriculture and computational genomics, delivers presentations at major international conferences such as the Plant and Animal Genome Conference, and mentors undergraduate researchers. Looking forward, she plans to lead innovative research combining data-driven technologies and computational biology to address complex challenges in health, genetics, and biological systems.