About
I am a PhD researcher at the University of New South Wales (UNSW), conducting research at the Victor Chang Cardiac Research Institute in the areas of AI for Biology, AI for Genomics, and biological foundation models. My work focuses on developing machine learning approaches to decode how genomic sequences encode biological functions and how genetic and epigenetic programs change during ageing.
I am an intern at Shanghai AI Laboratory, where I work with A/Prof. Siqi Sun in the BEAM Lab on AI-driven scientific discovery. I am also doing a long term visiting at Center for Artificial Intelligence Research and Innovation (CAIRI AI Lab), led by Prof. Stan Z. Li. I am engaging with AI for Science (AI4Sci), particularly on protein structure prediction, RNA virus indentification and microbiome foundation model.
My long-term vision is to build AI-driven digital twins of human health by integrating genomic, molecular, microbial, and clinical information across biological scales.
Research Interests
My research interests lie at the intersection of AI and Biology, with a particular focus on:
- AI for Biology and Biological Foundation Models
- Computational and Regulatory Genomics
- Genetics and Epigenetics of Ageing
- Microbiome Intelligence and RNA Virus Discovery
- Digital Twins for Human Health
Education
- 2025.06 - Present Ph.D at University of New South Wales (UNSW)
- 2020.09 - 2023.06 M.Phil at Harbin Institute of Technology (HIT)
- 2016.09 - 2020.06 B.sc at Jilin Agricultural University (JLAU)
Internship and Working
- 2026.06 - present Research Intern, Shanghai AI Lab
- 2025.06 - present Visiting Scholar, CAIRI, Westlake University
- 2024.01 - 2025.05 Research Assistnat, CAIRI and EMBLab, Westlake University
- 2023.09 - 2025.05 Research Intern, UNSW Microbiome Research Center.
- 2022.12 - 2023.08 Research Intern, AI for Healthcare Group, Chinese University of Hong Kong.
- 2021.04 - 2022.04 Visiting Student, Southern University of Science and Technology.
Publication & Software
Representative publications (including preprint and under preparation)
📄 CompRanking: a pipeline for quantitatively ranking the risk antimicrobial resistance in environmental metagenomic samples
Authors: Gaoyang Luo
Software: Open-sourced
This pipeline is used to quantitatively ranking AMR risk in environmental metagenomic samples
📄 Expanding the RNA Virus Universe by Deep Learning Discovery
Authors: Gaoyang Luo#, Zelin Zang, Ling Yuan, Jingbo Zhou, Ao Dong, Yufei Huang, Stan Z. Li, Feng Ju*
Journal Artile: BioRxiv
Identification of RNA virus using Deep Learning
📄 Rider: A deep learning method for fast RNA identification
Authors: Gaoyang Luo
Software: Open-sourced
Identification of RNA virus using deep learning
📄 Determining Antimicrobial Resistance in the Plastisphere: Lower Risks of Nonbiodegradable vs Higher Risks of Biodegradable Microplastics
Authors: Gaoyang Luo, Lu Fan, Bin Liang, Jianhua Guo, Shu-Hong Gao*
Journal Article: Environmental Science & Technology, 2025 (Nature Index Journal, Q1 Top)
Quantifing the AMR risk in the plastisphere
📄 Determining the Contribution of Micro/Nanoplastics to Antimicrobial Resistance: Challenges and Perspectives
Authors: Gaoyang Luo, Bin Liang, Hanlin Cui, Yuanyuan Kang, Xu Zhou, Yu Tao, Lu Lu, Lu Fan, Jianhua Guo, Aijie Wang, *Shu-Hong Gao*
Journal Article: Environmental Science & Technology, 2023 (Nature Index Journal, Q1 Top)
Review of AMR risk in the plastisphere