معرفی
Tung Kieu is a Tenure Track Assistant Professor in the Department of Computer Science at Aalborg University (Denmark), affiliated with The Technical Faculty of IT and Design and the Daisy Center for Data-intensive Systems. His research focuses on data engineering, time series analysis, anomaly detection, and machine learning applications in traffic forecasting and smart systems.
Education: Ph.D. in Computer Science (Awarded May 2021).
Research interests include time series forecasting, traffic modeling, robust autoencoder architectures for anomaly detection, and spatio-temporal data analysis. His work contributes to UN Sustainable Development Goals related to smart cities and infrastructure.
Recent publications explore bias mitigation in text-video retrieval (BiMa), topology-aware traffic forecasting (TEAM), and stochastic routing in uncertain road networks. His frameworks emphasize lightweight algorithms (LightTS), causal relational learning, and continual calibration for quantized models (QCore).
Collaborations involve international teams in data management and AI, with notable work on ensemble methods, explainable AI, and transfer learning in smart building systems.
