Paper accepted by KDD 2025 titled 'Oldie but Goodie: Re-illuminating Label Propagation on Graphs with Partially Observed Features'
Paper accepted by Applied Network Science in 2024 titled 'Influence maximization on temporal networks: a review'
Paper accepted by PAKDD 2024 titled 'DEGNN: Dual Experts Graph Neural Network Handling Both Edge and Node Feature Noise'
Paper accepted by Machine Learning in 2023 titled 'Predicting Potential Real-time Donations in YouTube Live Streaming Services via Continuous-time Dynamic Graph'
Best Paper Award at the 1st Workshop on Visual Continual Learning in 2023 for 'Class-Incremental Learning using Diffusion Model for Distillation and Replay'
Research Experience
Guided doctoral students in research on real-time donation prediction, link prediction, etc.; Delivered a lecture at the AIST AI seminar.
Background
Research interests include artificial intelligence, network science, machine learning, and Web mining.
Miscellany
Welcomes international student applications to join the lab; Encourages applicants to take TOEIC or TOEFL to demonstrate English proficiency.