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Years of research
Profile
About Me
My research focuses on developing advanced machine learning techniques, specifically in structural-temporal analysis, multivariate sequential learning, and longitudinal analysis. I am working on designing robust algorithms for anomaly detection and investigating the capabilities of large language models to improve their application across various domains.
My current projects involve applying these methodologies to areas such as sports doping and healthcare analytics. By combining theoretical advancements with practical applications, I aim to contribute to the development of data-driven solutions that address complex challenges in these fields.
Selected work
Recent
Publications
(2026). DiGAN: Diffusion-Guided Attention Network for Early Alzheimer's Disease Detection. In 1st AI for Healthy Aging and Longevity Workshop (AIAA): AAAI Conference on Artificial Intelligence (AAAI 2026)
(2024). Incorporating Metabolic Information into LLMs for Anomaly Detection in Clinical Time-Series. In Workshop on Time Series in the Age of Large Models: Neural Information Processing Systems (NeurIPS 2024)
(2024). SACNN: Self Attention-based Convolutional Neural Network for Fraudulent Behaviour Detection in Sports. In Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI 24)
Explore All Publications →Updates
News
Two papers (Main Track, Workshop) accepted at ICML 2026, Seoul.Publication
Paper accepted at Nature Scientific Reports.Publication
Best Paper Award at AIAA workshop, AAAI 2026, Singapore.Award
Workshop paper accepted at AAAI 2026, Singapore.Publication
Two main conference papers accepted at ICIS 2024, Bangkok, Thailand.Publication
Workshop paper accepted at NeurIPS 2024, Vancouver, Canada.Publication
Two main conference papers accepted at WITS 2024, Bangkok, Thailand.Publication
Main conference paper accepted at IJCAI 2024, Jeju, South Korea.Publication