Thong Minh Lai (Tom)AI-something-related

Developed ML to predict abandoned checkout session's return probability for sending targeted email campaigns on Cottages.com and Hoseasons, achieving 84% recall in capture rate for positive customers likely to return after sending reminder email. Strategic labelling framework using timeline based criteria, engagement patterns for imbalanced datasets Based on prediction confidence to determine CRM contact strategies. Developed interactive dashboard for email strategy simulation to test on new recent unseen abandoned sessions using Streamlit.

Research on applying XAI methods for Deep Learning architectures widely known to be used in detecting credit card transaction fraud, including CNN and LSTM with attention mechanisms, trained on Sparkov's synthetic dataset. The main contribution lies in the integration and comparative analysis of three Explainable AI methods: SHAP, LIME and Anchors. Research further evaluates the effectiveness of each XAI method based on Faithfulness, Monotonicity, and Completeness metrics.

This project demonstrates the deployment and benchmarking of a virtual computer cluster on Microsoft Azure. The system consists of three Ubuntu 22.04 nodes (one headnode and two compute nodes) connected through a shared virtual network (HPC-vnet), using OpenMPI for parallel processing.