I am a postdoctoral researcher at the Asai Laboratory at the University of Tokyo. My research focuses on spectral clustering, machine learning, and bioinformatics. Currently, I am developing machine learning algorithms for bioinformatics applications.
2025.12 - Published preprint “Large generative mRNA language foundation model for efficient coding sequence generation and design with mRNA-GPT” on bioRxiv.
2025.10 - Published preprint “Gradient-based Optimization for mRNA Sequence Design” on bioRxiv.
Professional Experience
2023.5 - Resumed postdoctoral research at the University of Tokyo.
2022.10 - Joined HAOMO.AI as a machine learning engineer for the “蓝色空间领航者” project.
2022.4 - Appointed as a researcher at the University of Tokyo (Details).
2022.3 - Received Ph.D. from the University of Tsukuba.
Publications
2025.12 - Co-authored “Large generative mRNA language foundation model for efficient coding sequence generation and design with mRNA-GPT” in bioRxiv. Link
2025.10 - Published “Gradient-based Optimization for mRNA Sequence Design” in bioRxiv. Link, Code
2023.9 - Co-authored “An Integrated Physical Approach to Earthquake-Induced Landslide Susceptibility Incorporating Geological Structure: A Case Study of the Diexi Catchment, Sichuan, China” in Engineering Geology. Link
2023.1 - Published “LSEC: Large-scale spectral ensemble clustering” in Intelligent Data Analysis. arXiv, Code
2022.7 - Published “Missing Value Imputation With Low-Rank Matrix Completion in Single-Cell RNA-Seq Data by Considering Cell Heterogeneity” in Frontiers in Genetics. Code
2022.6 - “Divide-and-conquer based Large-Scale Spectral Clustering” accepted by Neurocomputing. arXiv, Code
2020.11 - “Ensemble Learning for Spectral Clustering” published in ICDM 2020. PDF, Code
2020.11 - “Hubness-based Sampling Method for Nyström Spectral Clustering” published in IJCNN 2020. Link
2020.2 - “An Oversampling Framework for Imbalanced Classification Based on Laplacian Eigenmaps” published in Neurocomputing. Link
2019.8 - “Distributed Collaborative Feature Selection Based on Intermediate Representation” published in IJCAI 2019. Link
2019.8 - “Large Scale Spectral Clustering Using Sparse Representation Based on Hubness” published in CBDCom 2018. Link, Code
Funding
Research Grants
2025.10 - Google Grant: Input Data Differentiable Designer: A Novel ML Algorithm for Biological Sequence Optimization - $30,000
2024.4 - KAKENHI Young Researcher Grant for developing a large-scale language model integrating RNA sequences and text (Project Info)
Scholarships
2021.10 - JST SPRING Fellowship (Pioneering Research Initiated by the Next Generation)