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General Information

Full Name Hao Yuan
Position Postdoctoral Fellow, Department of Molecular Biosciences, University of Texas at Austin
Email hao.yuan@austin.utexas.edu
Phone (517) 402-1770
Languages English, Chinese

Education

  • 2021-2026
    PhD in Genetics and Genome Sciences & Ecology, Evolution and Behavior
    Michigan State University, MI, USA
    • Topic
      • Contextualizing Biological Associations Across Genes, Cell Types, Species, and Evolution
    • Advisor
      • Ingo Braasch
      • Arjun Krishnan
  • 2016-2019
    MS in Biology
    Shanghai Ocean University, Shanghai, China
    • Topic
      • Assembly and Filtering of Enriched Data from Exon Capture Across Species
    • Advisor
      • Chenhong Li
  • 2012-2016
    BS in Marine Biology
    Shanghai Ocean University, Shanghai, China
    • Advisor
      • Chenhong Li

Experience

  • 2026-
    Postdoctoral Fellow
    Marcotte Lab, University of Texas at Austin
  • 2021-2026
    Graduate Assistant
    Braasch Lab & Krishnan Lab, Michigan State University
  • 2020-2021
    Bioinformatician
    Shanghai Amplicongene Bioscience Co. LTD.
  • 2019
    Bioinformatician
    Genergy Biotechnology Co. LTD

Open Source Projects

  • 2026
    ICePop
    • Linking Genetic Risk to Disease-Relevant Cellular States via Metacell-Informed Modeling with ICePop
  • 2024
    txt2onto2.0
    • Annotating publicly-available samples and studies using interpretable modeling of unstructured metadata
  • 2023
    CONE
    • CONE: COntext-specific Network Embedding via Contextualized Graph Attention
  • 2018-2019
    Assexon
    • Assexon: Assembling Exon Using Gene Capture Data

Skills

  • Computational Background and Skills
    • Well-versed with Python, R, Linux command line and version control using GitHub
    • Experience with Python package development
    • Experience working with high-performance computing resources
  • Computational Genomics, Network Modeling, and Text Mining Skills
    • Well-versed with genomic data analysis including genomic sequences, bulk and single-cell transcriptomics
    • Experience with graph learning methods using protein-protein interaction networks and integrated analysis with omic data
    • Experience with statistical modeling using single cell omic data
    • Experience with using large language models for large-scale text mining and metadata analysis
  • Statistics, Data Science, and Machine Learning
    • Data wrangling and visualization in Python with pandas, matplotlib, and seaborn
    • Statistical modeling and machine learning in Python with numpy, numba, statsmodels, scipy, scikit-learn and PyTorch

Honors and Awards

  • 2026
    • Genetics and Genome Sciences Program Outstanding Student Award
  • 2023
    • Summer College of Natural Science Outstanding Scholar Fellowship

Talks

  • Sep 2024
    CONE: COntext-specific Network Embedding via Contextualized Graph Attention
    Machine Learning in Computational Biology 2024, Seattle, WA
  • Mar 2024
    Discovering context-specific functionally equivalent genes in research organisms using cross species transcriptome-based machine learning
    The Allied Genetics Conference 2024, Metro Washington, DC
  • Dec 2022
    An ML framework for precision medicine: from patient-specific gene networks to translational animal models
    Rocky 2022 Bioinformatics Conference, Snowmass, CO
  • Oct 2016
    Genome-wide detection of sites under selection using a modified method of evolutionary probability - a case study on adaptive evolution of Homo species
    23rd Academic Annual Meeting of China Zoological Society, Wuhan, China
  • Oct 2024
    Annotating public omics samples and studies using interpretable modeling of unstructured metadata by txt2onto 2.0
    Genetics and Genome Sciences Forum, Michigan State University
  • Feb 2024
    An ML framework for precision medicine: from patient-specific gene networks to translational research organisms
    Genetics and Genome Sciences Forum, Michigan State University
  • Oct 2023
    Reconstruct patient-specific gene networks from transcriptomic data
    Genetics and Genome Sciences Forum, Michigan State University
  • Oct 2022
    An ML framework for precision medicine: from patient-specific gene networks to translational animal models
    Computational Biology Forum, Michigan State University

Posters

  • 2025
    Evolutionary Implications of the Teleost Genome Duplication Revealed by Cross-Species Single-Cell Transcriptomic Comparison
    American Society for Biochemistry and Molecular Biology 2025: Evolution and Core Processes in Gene Expression, Kansas City, MO
  • 2025
    ICePop: Identifying Disease-Affected Cell Types Through Network-Based Analysis of Gene Module Overexpression in Single-Cell Data
    Network Biology 2025, Cold Spring Harbor, NY
  • 2024
    ICePop: Identifying Disease-Affected Cell Types Through Network-Based Analysis of Gene Module Overexpression in Single-Cell Data
    Biological Data Science 2024, Cold Spring Harbor, NY
  • 2024
    Tracking dynamic regulatory changes in rare diseases using single sample networks
    Annual Meeting of American Society of Human Genetics 2024, Denver, CO
  • 2024
    CONE: COntext-specific Network Embedding via Contextualized Graph Attention
    Machine Learning in Computational Biology 2024, Seattle, WA
  • 2023
    Interpretable text-based machine learning for inferring systematic tissue and disease annotations of public transcriptome samples
    Genome Informatics 2023, Cold Spring Harbor, NY
  • 2023
    An ML framework for precision medicine: from patient-specific gene networks to translational animal models
    Network Biology 2023, Cold Spring Harbor, NY
  • 2022
    An ML framework for precision medicine: from patient-specific gene networks to translational animal models
    Rocky 2022 Bioinformatics Conference, Snowmass, CO
  • 2022
    Cross-species transcriptome-based regression to discover equivalents of human samples and genes in biomedical research organisms
    30th Conference on Intelligent Systems for Molecular Biology, Madison, WI
  • 2018
    EXpipe: An Assembly Pipeline for Exon Capture Data Across Large Scales of Divergence
    1st AsiaEvo Conference, Shenzhen, China

Teaching and Mentoring

  • Teaching
    • 2023: IBIO341 Fundamental Genetics, Teaching Assistant
  • Mentoring (Post-baccalaureate)
    • 2023-2025: Lydia Valtadoros, Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus
  • Mentoring (Junior Graduate Student)
    • 2023-2026: Parker Hicks, Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus

Professional Service

  • Reviewing Service
    • 2026: G3: Genes, Genomes, Genetics (2 manuscripts)
    • 2025: G3: Genes, Genomes, Genetics (1 manuscript)
    • 2024: Journal of Experimental Zoology Part B: Molecular and Developmental Evolution (1 manuscript, co-review with Dr. Ingo Braasch)
    • 2023: Genome Biology (1 manuscript, co-review with Dr. Arjun Krishnan)
    • 2022: Genome Research (1 manuscript, co-review with Dr. Arjun Krishnan)
  • Community Service
    • 2023-2025: Genetics and Genome Sciences Program Seminar Coordinator
    • 2023-2025: Genetics and Genome Sciences Program Graduate Student Organization
  • Career Development Activities
    • Jan 2023: Graduate Student Career Forum
    • Apr 2022: APIDA Virtual Career Panel: Careers in Data, Analytics, Technology, & Engineering
    • Apr 2022: Boost your professional power skills
  • STEM Outreach
    • Dec 2023: AP Biology DeWitt High School Visit Day

Academic Interests

  • Biomedicine
    • Heterogeneity of complex diseases
    • Gene network analysis of complex diseases
    • Statistical modeling of single cell data
  • Evolution
    • Cross-species knowledge transfer between research organism and human
    • Cell type evolution

Other Interests

  • Hobbies: Cooking, Video Game