Data Scientist
I’m a PhD Candidate in Statistics at NTNU. I have 5 years of experience in data analysis and machine learning across distributed acoustic sensing (at CGF – NTNU), customer analytics (at Heineken, Techcombank), and aerospace manufacturing (at Airbus).
Key areas: Machine Learning · Data Engineering · Signal Processing
Technical tools: Python (Scikit-learn, LightGBM, PyTorch) · SQL · Microsoft Azure
Detection with Distributed Acoustic Sensing
During my PhD, I've contributed to developing event-detection algorithms for DAS.
Whale Vocalization Detection in Svalbard
(Truong et al., 2026)
Traffic Monitoring in Astfjord
(Truong et al., 2024)
Rockfall Detection in Trondheim
(Truong et al., 2023)
Identifying the Most Potential Customers in Banking
As part of a bank's data science team, I helped develop propensity models to target suitable customers for financial products.
Feature Engineering (PySpark) · Propensity Model (LightGBM) · Data Pipeline Orchestration (Airflow) · Project Management
Standard Assembly Process Detection at Airbus
Airbus has thousands of unclassified assembly processes.
I worked with shop-floor engineers to define standard processes to improve manufacturing efficiency.
Unsupervised Machine Learning (DBSCAN, Hierarchical Clustering, K-Means) · Dimensionality Reduction (PCA) · Visualization (t-SNE)