Thomas Lee

Thomas Lee

Northeastern University Information Systems

Data-Driven, Impact-Oriented.

Hi, I’m Thomas — a curious problem solver with a background in both chemistry and data science. I started my journey in the lab, where precision and attention to detail shaped the way I see the world. Over time, that same mindset naturally pulled me toward data — discovering patterns, solving complex problems, and turning messy numbers into meaningful insights.

Right now, I’m pursuing my Master’s in Information Systems at Northeastern University. Along the way, I’ve dived deep into machine learning, data engineering, and statistical analysis — skills I love applying to real-world challenges. Whether it’s detecting cracks in concrete with deep learning models or predicting housing prices with spatial data, I’m always drawn to projects that bridge data and impact.

Before grad school, I worked as a Process Engineer in the semiconductor industry. That’s where I truly learned the power of data-driven decisions — optimizing processes, automating measurements, and seeing firsthand how numbers improve production quality (and even win you awards!).

Outside of work, you’ll probably find me exploring new Python libraries, learning about the latest AI trends, or enjoying a good cup of coffee while diving into data visualizations. I’m passionate about continuous learning, connecting ideas across disciplines, and finding ways data can make life — and business — a little smarter.

Work Experience

  • Process Engineer, Kinsus Interconnect Technology Corp., Hsinchu, Taiwan, May 2022 - Sept 2023
    • Conducted statistical analysis and Design of Experiments (DOE) to optimize production processes, achieving a 100% reduction in defect rate and enabling mass production, which earned the Star Award for excellence.
    • Developed and implemented automated measurement systems integrated with Statistical Process Control (SPC) databases, improving measurement accuracy by 20-fold and capacity by 14-fold.
    • Leveraged ETL techniques (data extraction, transformation, and validation) to preprocess accuracy metrics such as Gauge Repeatability and Reproducibility (GRR), significantly reducing measurement errors.
    • Applied Excel Macros and VBA scripting to optimize process parameters, enhancing sorting accuracy and improving defect detection capabilities in production workflows.

Education

  • Master of Information Systems, Northeastern University, Seattle, WA, USA, Sept 2024 -Expected Jun 2026
    • Relevant Coursework: Data Science Engineering, Database Design, Program Structure and Algorithms.
  • Bachelor of Applied Chemistry, National Yang Ming Chiao Tung University, Hsinchu, Taiwan, Sept 2017 - Jun 2021
    • Relevant Coursework: Analytical Chemistry, Integrated Chemistry Laboratory, Calculus.

Resume

You can find my resume here.