I enjoy designing and refining AI pipelines — whether it's building RAG systems, orchestrating AI agents, or optimizing end-to-end workflows for production.

Currently leading Research Engineering at Braincrew, building production AI systems end-to-end.

Previously led the SoundMind AI Ecosystem (RAG Pipeline optimization, Admin Console, B2B SaaS Platform) at Soundmind (2025.07 ~ 2026.03).

Research Engineering Team — Engineering Part Lead

• Leading the engineering part of the Research Engineering team

AI Product Engineering

• SoundMind-AI-Console — Admin Dashboard for RAG Pipeline auto-generation & one-click Docker deployment
• SoundMind-AI-Platform — B2B SaaS with Chat Agent & RAG Agent, up to 99 simultaneous RAG Pipelines

AI R&D

• Advanced RAG Pipeline — Query Rewrite, Hybrid Search, Reranking, RAGAS evaluation (+13%p quality improvement)

Member of Modulabs RAPIDS LAB, a research group focused on GPU-accelerated data science:

• GPU-accelerated End-to-End Full GPU-based AutoML System research
• GPU-accelerated ML study notes — https://github.com/Hyeongseob91/nvidia-rapids

AI R&D

• WIGVO — Real-time bidirectional speech translation over legacy PSTN calls (ACL 2026 Accepted, 1st Author)
• WigtnOCR — VLM-based Korean public document parsing framework, 2B model surpassing 30B Teacher (EMNLP 2026 In Prep)

Open Source

• WIGTN-Coding — Claude Code AI-Native development workflow plugins (7 Commands, 14 Agents, 7 Skills)
• TimeLens — Multimodal AI museum curator with voice + camera (Gemini Live Agent Challenge)
• LLM Loadtester — LLM serving performance benchmarking tool (TTFT/TPOT/Goodput visualization)

Business Products

• WIGVU — YouTube subtitle extraction, translation & AI analysis service
• WIGEX — Travel expense tracking mobile app with AI receipt OCR

• 🥈 Snowflake AI & Data Hackathon 2026 Korea — Tech Track 2nd Place
  WIGTN FLAKE — A purpose-driven local intelligence platform. Users pick what they want to do — open a cafe, run targeted rental marketing, place outdoor ads, invest in real estate — and an AI expert panel cross-reads four datasets (real estate, foot traffic, card sales, telecom contracts) to recommend the best neighborhoods, surface anomaly signals before they show up in headlines, and project six-month trends. Built on a hybrid Snowflake Cortex × GPT-4o orchestration that lets the analysis read like a conversation between domain experts rather than a dashboard.