Junggeun Do

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I am currently pursuing a Master of Science in Computer Science at Texas A&M University. I previously earned my BS in Physics and BA in Economics from Seoul National University in 2024, along with a minor in Computer Science and Engineering.

Before beginning my graduate studies, I worked as a Machine Learning Engineer across diverse environments, from early-stage startups to large enterprises in the Korean tech industry. These experiences have shaped my interest in bridging machine learning research with scalable engineering practices to build real-world products.

My research interests lie in developing reliable and interpretable deep learning models, particularly in natural language processing. I am especially interested in approaches that integrate real-world knowledge and constraints, with an emphasis on multilingual capabilities. Ultimately, I aim to develop systems that are not only high-performing, but also transparent and trustworthy, ensuring their safe and effective deployment across diverse applications worldwide.

publications

  1. ICCV workshop
    SEAL-Pose: Enhancing 3D Human Pose Estimation through Trainable Loss Function
    Junggeun Do , and Jay-Yoon Lee
    ICCV 2025 workshop SP4V
  2. NAACL
    ContrastiveMix: Overcoming Code-Mixing Dilemma in Cross-Lingual Transfer for Information Retrieval
    Junggeun DoJaeseong Lee, and Seung-won Hwang
    NAACL 2024 (oral)