Summary
Hsin-han Lee is a software engineer with 11 years of experience who currently builds fraud-detection systems at NEXT BANK, following a data engineering role at POMO Network where he streamlined ETL with Argo Workflows and GitOps. He specializes in Python-driven pipelines, web scraping for diverse training datasets, and practical ML deployments—famously implementing a BERT-based product classifier that achieved ~90% accuracy with cost-conscious SageMaker deployment. His background blends bioinformatics research (PhD-level work using XGBoost, RNNs, and supercomputing to accelerate genomic analysis) with hands-on production engineering across e-commerce and finance. Comfortable across the full data lifecycle, he pairs academic rigor with pragmatic solutions that scale in serverless and cloud environments. Colleagues describe him as an enthusiastic team player who seeks inventive machine-learning applications to real-world problems.
10 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Taiwan International Graduate Program on Bioinfomatics, Doctor of Philosophy - PhD, Taiwan International Graduate Program on Bioinfomatics at Institute of Information Science, Academia Sinica
Master of Science - MS, Plant Pathology and Microbiology, Master of Science - MS, Plant Pathology and Microbiology at 國立臺灣大學