About Me
I build AI systems that help people communicate across languages and cultures — at the intersection of research and production.
As a Staff Engineer at Samsung Electronics, I'm part of the team building machine translation for Galaxy AI, working alongside global research labs to ship multilingual AI features to hundreds of millions of devices worldwide. My current focus is on automation — building data pipelines, quality inspection systems, and CI/CD infrastructure that make model iteration faster and more reliable.
I hold a Ph.D. in Computer Science from Korea University's NLP & AI Lab, where my research on dialogue systems — grounding conversations in persona and world knowledge — was published at EMNLP, AAAI, COLING, and ACL. Along the way I collaborated with Naver, Hyundai Motor, and NCSoft on real-world NLP challenges that shaped my belief that the best research ships.
News
Research Interests
Industry
- Developing multilingual neural machine translation models powering Galaxy AI features — including Live Translate (calls), Interpreter, Writing Assist, Note Assist, and Browsing Assist — deployed across Galaxy smartphones and tablets worldwide
- Collaborating with overseas research labs to research and align multilingual MT models across diverse language pairs and regional requirements
- Building a data augmentation pipeline to automatically generate and diversify training data for low-resource language pairs
- Designing automated data inspection workflows for quality control and noise filtering at scale
- Implementing CI/CD pipelines for automated model build, evaluation, and deployment — reducing iteration cycles and enabling continuous model improvement
- Explored new digital services for enhancing digital competitiveness
- Collaborated with UX/UI designers to introduce new services via MVP model
- Built the first Korean document-level relation extraction dataset from Naver's encyclopedia
- Developed coreference-resolution-enhanced models for entity relation classification
- Developed intent classification and slot-filling model for in-vehicle dialogue
- Applied multi-task training on language models for simultaneous intent and slot prediction
- Created FoCus — a dialogue dataset grounding user persona and knowledge via Amazon MTurk
- Built dialogue system informing users about Wikipedia knowledge based on persona
Publications
Research Projects
- Developed image retrieval services for end users
- Explored relative image components for canvas-based interaction
- Built first Korean document-level RE dataset from Naver Encyclopedia documents
- Model combining coreference resolution, entity typing, and relation extraction
- Intent classification and slot filling for Hyundai vehicle dialogue
- Multi-task training for simultaneous intent and slot prediction
- Created FoCus dataset grounding user persona and knowledge via Amazon MTurk
- Built dialogue system informing users about Wikipedia knowledge of landmarks