welcome!

Hello, I’m Soungmin (Min) Lee, a BS/MS student in Computer Science at Georgia Tech, specializing in NLP and web development. Currently focused on NLP research and integrating LLM-powered features into web/mobile services, I enjoy building software solutions that optimize critical processes and solve complex problems.


Publications

  • Words That Unite The World: A Unified Framework for Deciphering Central Bank Communications Globally
    • Agam Shah, Siddhant Sukhani, Huzaifa Pardawala, Saketh Budideti†, Riya Bhadani†, Rudra Gopal†, Siddhartha Somani†, Michael Galarnyk†, Soungmin Lee†, et al. NeurIPS 2025 [Paper] · [Website] · [Dataset] · [Code]

Career

  • Software Development Engineer Intern · Amazon Web Services (AWS) · Aug 2025 – Present
    • Elastic Block Storage VMDS Team
  • Undergraduate Researcher · Georgia Tech VIP Program · Jan 2024 – Aug 2025
    • Core contributing author of the World Central Banks (WCB) dataset paper, published at NeurIPS 2025, introducing the largest monetary policy corpus to date and benchmarking state-of-the-art language models for stance, temporal, and uncertainty detection.
    • Implemented pipelines and filtration techniques to counter intentional mixed tone of central banks of countries such as the USA, South Korea, Turkey, etc.
    • Engineered a new dataset format which drastically improves classification accuracy of hawkish/dovish stances of the Fed using pre-trained language models.
    • Analyzed NLP models such as StockNet from mid-2010s using Python and TensorFlow, evaluating if the models hold accuracy with modern data.
  • Software Engineer Intern · LG Innotek · Jul 2024 – Aug 2024
    • Developed a trilateration localization system using BLE beacons from NXP, implemented in C and packaged with CMake, achieving 9 yard accuracy for Bluetooth device positioning.
    • Applied and trained the ECA-ResNet model using Python and TensorFlow on a RSSI localization system, improving vehicle tracking accuracy by 15% and identifying key error factors for further optimization.
    • Implemented a customized particle filter for UWB data, reducing location measurement error by 55% within an 10 yard range, enhancing mobile digital key functionality.
  • Software Engineer Intern · VITAON · May 2024 – Jun 2024
    • Developed the frontend and backend of VITAON, a cross-platform e-commerce application using ReactJS and Node.js, enabling personalized nutritional supplement recommendations based on user data.
    • Designed and deployed a Microsoft Azure-based machine learning model to classify dietary supplements from images, extracting key product details (e.g., RDA, market data) with 97% Top-5 accuracy.
    • Engineered a recommendation algorithm that tailors supplement suggestions based on user attributes (age, gender, dietary restrictions, current intake) using Python, enhancing user experience and safety.
  • Software Developer, Sergeant · Republic of Korea Air Force · Sep 2021 – Mar 2023
    • Built a computer vision model using PyTorch to track bullet marks on targets, replacing the manual evaluation process and accelerating rifle training assessments by 75%.
    • Launched a suite of features for 5+ military facility websites such as personnel management and room reservation using Vue and Spring Boot, improving operational efficiency.
    • Refined and maintained databases with 500,000+ entities using MySQL and MySQL Workbench, reducing query processing time by approximately 20% and enhancing nationwide workflow efficiency.

Education

  • B.S./M.S. in Computer Science · Georgia Tech
    • Expected B.S. Graduation: Spring 2026
      • Concentration: Info-Internetworks / Intelligence
    • Expected M.S. Graduation: Spring 2027
      • Concentration: Machine Learning