About
Research leader at the intersection of AI systems, backend engineering, and GPU-accelerated databases
Current Affiliations
Algorix Corporation
Head of Research
Leading research initiatives in AI systems, backend engineering, and system optimization
POSTECH DBLab
Undergraduate Research Intern (July 2025 - Present)
Researching GPU-accelerated graph database management systems, focusing on performance optimization and system design
POSTECH
Undergraduate Student
Double Major: Electronics Engineering & Computer Science (expected)
Research Focus
As Head of Research at Algorix, I lead research initiatives in AI systems and backend engineering, focusing on practical implementations that bridge research and production. My work involves developing AI systems with PyTorch, building scalable backend architectures using TypeScript, Go, and Python, and optimizing system performance.
In parallel, I conduct research at POSTECH DBLab on GPU-accelerated graph database management systems. Since joining in July 2025, I've been exploring how parallel computing with CUDA can dramatically improve query performance for complex graph operations, bridging theoretical database design with practical system implementation.
Beyond research, I'm active in the security community through POSTECH PLUS and other hacking/security activities, which helps me maintain a holistic view of system design that considers both performance and security.
Technical Expertise
Systems & Databases
- Graph DBMS Design
- GPU/CUDA Programming
- System Optimization
- Performance Tuning
- Distributed Systems
AI & Machine Learning
- PyTorch Implementation
- Model Optimization
- AI System Integration
- Deep Learning
- TensorRT Serving
- Agentic AI
Backend Engineering
- TypeScript / Node.js
- Go / Python
- API Design
- Database Architecture
- Docker / Kubernetes
Security
- CTF Competitions
- POSTECH PLUS
Research Approach
Theory meets Practice
Bridging academic research with production systems, ensuring theoretical innovations translate to real-world performance gains.
Performance-Driven
Obsessive focus on optimization—from GPU kernel efficiency to system-level bottlenecks—backed by rigorous benchmarking.
Security-Conscious
Drawing from CTF and penetration testing experience to build systems that are both fast and secure.
Open Collaboration
Believing in open-source contributions and knowledge sharing to advance the broader research community.