AI Research Scientist · Tech Lead at NAVER Cloud

I am a Senior AI Research Scientist and Tech Lead in the Voice team at NAVER Cloud. My research focuses on Speech-Language & Multimodal AI and Large Language Models, with the goal of building AI systems that understand, reason, and interact across speech, language, and context.

I work on language and speech technologies for real-world AI products, spanning pronunciation modeling, phrase break prediction, data generation, and model evaluation. Recently, I have been exploring how LLMs can extend these systems through multimodal reasoning, tool use, and scalable agentic applications.

I connect research and engineering through technical leadership, mentoring, and production deployment. Since 2026, I have also served as an AI Technical Mentor at AI·SW Maestro.

• Speech-Language & Multimodal AI — unified understanding, reasoning, and generation across speech, language, and context
• LLMs & Agentic Applications — post-training, evaluation, tool use, and scalable real-world applications

• EMNLP 2026 — Phonemizing User-Generated Text: A Benchmark, Taxonomy, and Compositional Approach
• INTERSPEECH 2026 — LLM-Based Multi-Reference Evaluation for Efficient and Robust Assessment of Phrase Break Annotations
• INTERSPEECH 2025 — Synthetic Data Generation for Phrase Break Prediction with Large Language Model
• EMNLP 2024 — A Two-Step Approach for Data-Efficient French Pronunciation Learning

For a complete publication list, please visit my Google Scholar profile.

• — a multilingual G2P benchmark for user-generated text, published at EMNLP 2026
• — practical NLP tutorials and reproducible implementations in Jupyter notebooks

I enjoy turning research ideas into clear, reproducible resources and dependable AI systems. If you are interested in Speech-Language & Multimodal AI, LLMs, agentic applications, or research collaboration, feel free to reach out.