Research & Publications

My research spans machine learning in finance, NLP, and aviation safety systems.

2024

Improving the Efficiency of the Global Minimum Variance Portfolio through Technical Signals from Moving Averages NM Nhat, ND Trung, THM Tan Asian Journal of Economics and Banking (AJEB), 2024

This paper explores how technical indicators derived from moving averages can enhance the construction of minimum variance portfolios — bridging quantitative finance and machine learning.

A semi-supervised approach for Vietnamese stock news classification with deep learning NM Nhat, THM Tan Journal of Finance-Marketing Research, pp. 138–150, 2024

We propose a semi-supervised deep learning approach to classify Vietnamese financial news articles, addressing the challenge of limited labeled data in low-resource language settings.

2019

An Adaptive Hash-Based Text Deduplication for ADS-B Data-Dependent Trajectory Clustering Problem Tran, T., Pham, D.T., Duong, Q. and Mai, A. IEEE RIVF 2019 — International Conference on Computing and Communication Technologies

Introduces a hashing approach to efficiently deduplicate ADS-B trajectory data at scale for air traffic clustering.

A Simplified Framework for Air Route Clustering Based on ADS-B Data Duong, Q., Tran, T., Pham, D.T. and Mai, A. IEEE RIVF 2019 — International Conference on Computing and Communication Technologies

Presents a simplified, data-driven clustering framework for modeling air routes from surveillance data.