About

I am Yoshitaka Inoue, a Ph.D. candidate in Computer Science at the University of Minnesota, advised by Prof. Rui Kuang, and a pre-doctoral fellow at the National Library of Medicine / National Cancer Institute, co-advised by Dr. Augustin Luna.

My research develops machine learning methods for molecular medicine, with a focus on drug response prediction, graph representation learning, perturbation modeling, and LLM-based biomedical reasoning for precision oncology.

I am currently seeking 2027 research internship opportunities and postdoctoral opportunities starting in September 2027.

Previously, I received my M.Eng. in Information Science from the Nara Institute of Science and Technology and was a visiting scholar at the UC Davis Genome Center and DataLab.

Recent News

• Jun 2026: Two papers, DrugAgent and drGT, were accepted for oral presentations at ISMB 2026.
• Jun 2026: DrugAgent was accepted to the ICML 2026 Workshop on FM4LS.
• Jun 2026: Drug Discovery in the Era of Artificial Intelligence: From Target Identification to Clinical Trials was posted as a preprint.
• May 2026: drGT was selected as one of four Outstanding Postgraduate Fellow Finalists at the 26th Annual CCR-FYI Colloquium.
• Feb 2026: drGT was accepted by BMC Bioinformatics.

Research Interests

• Machine learning for molecular medicine
• Drug response prediction and treatment response modeling
• Graph representation learning for biological and pharmacological data
• Single-cell, perturbation, and intervention-aware representation learning
• LLM-based biomedical reasoning and evidence integration

Selected Publications

• DrugAgent: Reliable Multi-Agent Aggregation under Conflicting Biomedical Evidence
  Yoshitaka Inoue, Tianci Song, Xinlin Wang, Augustin Luna, Tianfan Fu
  Scientific Reports, under revision, 2026 · ICML 2026 Workshop on FM4LS · paper

• drGT: Attention-Guided Gene Assessment of Drug Response Utilizing a Drug-Cell-Gene Heterogeneous Network
  Yoshitaka Inoue, Hunmin Lee, Tianfan Fu, Rui Kuang, Augustin Luna
  BMC Bioinformatics, 2026 · paper

• Drug Discovery in the Era of Artificial Intelligence: From Target Identification to Clinical Trials
  Yoshitaka Inoue, Ning Hao, Yuting Lu, Tianfan Fu, Augustin Luna
  Health Data Science, under revision, 2026 · paper

• GraphPINE: Graph Importance Propagation for Interpretable Drug Response Prediction
  Yoshitaka Inoue, Tianfan Fu, Augustin Luna
  ICLR 2025 Workshop on MLGenX · paper