I'm an AI researcher and developer specializing in protein structure prediction and large language models. Currently serving as CTO at mefriend.ai and as a Visiting Scientist at KIAS, I combine expertise in PyTorch multi-GPU computing, kernel optimization, and cloud infrastructure. My work spans from deep learning research to production deployment, with accomplishments in protein language models, and AI system optimization.
Currently researching protein 3D structure prediction using Protein Language Model and diffusion models, developing rapid MSA generation methods, and implementing ensemble prediction approaches while managing cloud-based protein databases.
Spearheading cutting-edge research in language model algorithms and overseeing the deployment of machine learning operations. Focused on enhancing model performance and operational efficiency, contributing to the development of scalable AI solutions.
Leading the technical direction of an AI entertainment platform as CTO and co-founder with 300,000 global users. Fully responsible for the core inference system development and optimization. Oversee all technical aspects while also participating in overall strategic planning and vision as a founding member.
Developed EnsBolz, an ensemble generation tool utilizing Boltz. (selected as a speaker for the LA Biophysics Society 2025)
Successfully led a comprehensive migration from CRA to Next.js with progressive enhancement framework. Implemented monorepo architecture enabling simultaneous web and mobile app development using Capacitor. Achieved significant performance improvements with Web Vitals score increasing from 30 to 80 points, and successfully launched both enhanced web and mobile applications.
Developed plmMSA, a fast and diverse multiple sequence alignment tool utilizing a Protein Language Model. Co-first author of the submitted manuscript. (Presented at CASP16 and LA Biophysics Society 2025)
Achieved 3rd place in the Antibody/Peptide category. Developed plmMSA, a fast and diverse multiple sequence alignment tool utilizing a Protein Language Model.
Led the development of AI speaker's inference system and complex intelligence components, focusing on optimizing model performance and implementing advanced conversational capabilities.
Served as Team Leader in the 2023 Samsung Computer Engineering Challenge, addressing the challenge of accelerating LLaMa inference. My role encompassed the leadership and direction of the team's efforts in developing and integrating Kernel Fusing techniques. I was also responsible for orchestrating the Scheduler to ensure efficient task allocation and execution. The project culminated with me leading the final evaluation to assess our project's performance and deliverables.
As the Lead Developer for a cafe management platform designed for cafe operators, I was responsible for the comprehensive development of the platform. This included constructing the database, building APIs, designing and implementing the frontend, and designing the network architecture for application serving.
As the Lead Developer for the SW Expert Training Program's Healthcare Project, I was tasked with implementing MLOps using TFX. My responsibilities included frontend design, database architecture and construction, API development, and deploying services using a Kubernetes environment. Additionally, I managed the network infrastructure setup and oversaw the overall development process.
Advanced expertise in distributed deep learning optimization using PyTorch's DDP and FSDP frameworks for large-scale language model training. Specialized in custom CUDA kernel fusion implementation for computational graph optimization, gradient accumulation strategies, and mixed-precision training with automatic loss scaling. Proficient in memory-efficient training techniques including gradient checkpointing, ZeRO optimizer states, and advanced tensor parallelism for multi-billion parameter models.
Advanced expertise in containerized application deployment using Docker and Kubernetes orchestration with production-grade cluster management. Specialized in GitOps workflows with ArgoCD for automated continuous deployment, implementing comprehensive CI/CD pipelines through Jenkins with integrated testing and security scanning. Proficient in agile project management using Jira and enterprise-level secrets management with Infisical for secure credential distribution across environments.
Expert in designing cost-efficient, scalable cloud infrastructures for startup environments. Specialized in AWS resource optimization using Reserved Instances, Spot Instances, and auto-scaling strategies. Proficient in implementing Infrastructure as Code (IaC) using Terraform/CloudFormation, and establishing comprehensive monitoring with CloudWatch and cost alerting systems for budget-conscious deployments.
Expert in modern frontend architecture using Next.js with SSR/SSG optimization, advanced React patterns including custom hooks and context management. Proficient in TypeScript for type-safe development and component libraries, with extensive experience in CSS-in-JS solutions and Tailwind CSS for scalable design systems.
Advanced cross-platform development using Capacitor framework with native plugin integration. Expertise in bridging web technologies to native iOS/Android APIs, implementing performance optimization strategies for hybrid applications, and managing platform-specific build configurations for production deployment.
Proficient in developing RESTful APIs using FastAPI and Express.js frameworks. Experienced in designing and managing both SQL (PostgreSQL, MySQL) and NoSQL (MongoDB) databases, with expertise in Prisma ORM for type-safe database operations.
Selected for the 2025 DIPS Project (Leading AI Startup in Korea) (mefriend.ai) (Thanks to my team-mates!)
Selected as a speaker for the LA Biophysics Society 2025 to present research on complex ensemble generation using deep learning methods (Thanks to my advisor and co-workers!)
Won the SKKU Creative ICT Competition for developing an AI speaker with the naly.ai team
Selected for the Youth Entrepreneurship Training Program, a prestigious government-backed initiative supporting young entrepreneurs
Secured the 7th place in the Samsung Computer Engineering Challenge for accelerating inference in LLM models within a multi-GPU environment.
Achieved 1st place in the SW Expert Training Program for outstanding performance in a company-led project.
Won the Popularity Award in the SW Expert Training Program by securing a high number of votes in a company-led project.