Yi Li, Ph.D.

Associate Director of Machine Learning & Imaging Services

Integrative analysis of multi-omics data; integrative cross-species analysis of multi-omics data; AI and machine learning method development for and applications to bio-medical fields; image analysis.

My overall goal is to apply and develop computational tools that analyze biological data to better understand the mechanisms of complex diseases, with a particular focus on AI and machine learning methods. As the Associate Director of Machine Learning & Imaging, Computational Sciences, The Jackson Laboratory, I strive for deep understanding of the most recent machine learning theories and development and identifying their applications in biomedicine, as well as developing new methods for improved analysis. I participated in the MODEL-AD project during the past five years which aims to develop and evaluate various mouse models for human late onset Alzheimer’s disease (AD). When I applied deep learning methods to extract MRI image features and linked them to genetics and metabolites for an AD study of the MODEL-AD project, I realized existing tools are insufficient to enable us to know which mouse strains best reflect the AD mechanisms in human. Hence, my group recently developed a graph neural network-based cross-species gene expression data analysis framework that aims to maximize the similarity between mouse disease models and human disease data. The longer-term goal of my group is to develop an expandable AI framework for cross-species analysis of multi-omics data which not only include genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microbiome data, but also images, including cell images, MRI, fMRI, DTI, CT and multiplexed tissue images.

I have published more than 45 peer-reviewed papers in various journals, including first or co-first author publications in Nature Genetics, American Journal of Human Genetics, Machine Learning, Journal of Computer and System Sciences, and IEEE Transactions on Information Theory.

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Yi Li on Google Scholar

Education and experience


  • 1997– 2000: National Univ. of Singapore, Singapore
    Awarded degree: PhD in Computer Science. (awarded IDA gold medal and prize for being the PhD student with the best thesis in 2001)
    Thesis title: “From support vector machines to large margin classifiers” (Supervisor: Prof. Phil Long)
  • 1990– 1993: Xi’an Jiaotong Univ., P R China. Computer Science.
    Awarded Degree: M. Eng.
  • 1986– 1990; Xi’an Jiaotong Univ., P R China. Computer Science.
    Awarded Degree: B. Sci. (top 5%) (admitted to the university without taking the national university entrance examinations)

Work Experience:

  • Jun 2007 – now: senior computational scientist at Computational Sciences, The Jackson Laboratory, Farmington, CT, US
  • Jan 2007 – Jun 2017: staff scientist at Human Genetics, Genome Institute of Singapore, Singapore.
  • Apr 2002 – Dec 2006: Postdoc at Information & Mathematical Sciences, Genome Institute of Singapore, Singapore
  • Jan 2001 – Apr 2002: Research assistant at Dept. of Engineering Mathematics, Univ. of Bristol. U.K.