Incoming student

• ·Academic Excellence Award (Top 5% of class, 1 semester)
• ·Graduation GPA: 3.8/4.3

• ·Thesis: Improving Graph-based Recommendation with Unraveled Graph Contrastive Learning — co-authored publication in DMKD, Vol. 38, pp. 2440–2465 (2024)
• ·Graduation GPA: 3.63/4.3

• ·Designed and deployed automated futures and options strategies (maker & taker), coded trading logic into low-latency, scalable execution systems under risk constraints.
• ·Uncovered hidden factors driving system performance, opening a new dimension in latency analysis and reshaping the company's understanding of execution pipelines.
• ·Proposed and validated structural adjustments that reduced measurable latency by 50%+, prevented slippage, and improved execution quality of live trades.
• ·Led cross-functional research initiatives with trading, infrastructure, and MIS teams.

• ·Designed a graph-based recommendation framework using LightGCN and MLP models to mitigate the cold-start problem.
• ·Extracted and engineered features from 20+ SQL tables using PySpark on the Cloudera Data Platform.

• ·Led an NCHC-funded project to build a malicious account and contract detection system using blockchain.
• ·Engineered ML models (GNN, XGBoost); achieved 89.1% F1-score and 88.4% accuracy.

• ·Developed predictive maintenance ML models achieving 92% F1-score; reduced revenue losses by ~US$300K/year.
• ·Collected sensor data via Raspberry Pi in collaboration with production engineers.

• ·Selected for NTHU Garage, National Tsing Hua University's official incubator.
• ·Built and deployed the platform's RESTful API backend for a warehouse management system targeting plastic materials companies.