Sizhe Liu

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Hello! I’m a senior undergraduate at USC studying computer science. I am a student researcher at Liang’s Lab, advised by Prof. Liang Chen, and at FORTIS Lab, advised by Prof. Yue Zhao. I also work closely with Prof. Tianfan Fu and Prof. Tea Jashashvili.

Additionally, I’m a visiting student at Westlake University, working with Jun Xia under the supervision of Prof. Stan Z. Li.

My research focuses on developing machine learning methods for biomedical applications, with key areas including:

  • ML models for biomedical discovery: Developing geometric and generative models for biological tasks such as de novo peptide sequencing, gene perturbation, drug-target interaction, etc.
  • ML systems: Designing and building ML systems that make these discoveries efficient, reliable, and trustworthy.
  • Automating scientific research: Using LLM agents to streamline and automate scientific research workflows.

news

Oct 15, 2024 One paper accepted at AIDrugX@NeurIPS 2024 (Spotlight)
Sep 26, 2024 Two papers have been accpeted by NeurIPS 2024 :sparkles:
Sep 15, 2024 We have a new paper published in Human Molecular Genetics :sparkles:

selected publications

  1. HMG
    Deciphering single-cell gene expression variability and its role in drug response
    Sizhe Liu, and Liang Chen
    Human Molecular Genetics, Sep 2024
  2. NeurIPS
    FlexMol: A Flexible Toolkit for Benchmarking Molecular Relational Learning
    Sizhe Liu, Jun Xia, Lecheng Zhang, Yuchen Liu, and 7 more authors
    In Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks, Sep 2024
  3. Bioinformatics
    SP-DTI: Subpocket-Informed Transformer for Drug-Target Interaction Prediction
    Sizhe Liu, Yuchen Liu, Haofeng Xu, Jun Xia, and 1 more author
    Under Review, Jun 2024
  4. ICLR
    Bridging the Gap between Database Search and De Novo Peptide Sequencing with SearchNovo
    Jun Xia, Sizhe Liu, Jingbo Zhou, Shaorong Chen, and 4 more authors
    Under Review, Oct 2024
  5. AABA
    Multi-Bone Micro-CT Scanning with a Leap Towards Reproducibility and Efficiency Using Automated Tools
    Tea Jashashvili, Sizhe Liu, and Kristian J. Carlson
    In American Association of Biological Anthropologists (AABA) Conference, Mar 2024
  6. NeurIPS
    NovoBench: Benchmarking Deep Learning-based \emphDe Novo Sequencing Methods in Proteomics
    Jingbo Zhou, Shaorong Chen, Jun Xia, Sizhe Liu, and 5 more authors
    In Neural Information Processing Systems (NeurIPS) Track on Datasets and Benchmarks, Sep 2024