AICLab
Dream. Excellence. Teamwork.
Welcome to AICLab!
We are excited to embark on this journey of innovation and discovery in Applied AI and Computer Vision. Our lab brings together passionate researchers from diverse backgrounds, united by a common vision to create impactful solutions that bridge academic excellence with industry needs.
Professor KIM Tae-Kyung
Principal Investigator, AICLab
Mission & Vision
Mission: AICLab was established with the mission of pursuing applied AI and computer vision for industry and academic purposes.
Vision: We aim to be the trusted problem solver for industry in terms of Applied AI and computer vision initiatives and solutions to improve pain points and operational efficiency. Together with our partners and clients, we strive to achieve excellence in our work.
To set our target as broad as the peak of the mountain. Pursue our dream while maintaining excellence in our work, and by collaborating with our highly talented team members who share the same vision and mission.
Latest News
Stay Updated with Our Recent Achievements and Milestones
Welcome Mr. THON Sopheap to AICLab!
We warmly welcome Mr. THON Sopheap to AI Convergence Lab. Mr. Thon is pursuing his Master's degree in Big Data Engineering at Chungbuk National University and will be contributing to research in Big Data Engineering, MLOps, and Cloud Infrastructure.
Paper Published in Array
Mr. CHAN Sokheang and collaborators published "ASG-LLM: An LLM-based pipeline for automated scraping code generation in security-sensitive environments" in Array (SCOPUS), introducing an LLM-driven pipeline that generates scraping code for environments where security constraints matter.
Survey Published in ICT Express
Ms. CHIV Kimchhor published "A comprehensive survey of quantum computing approaches for portfolio optimization in FinTech" in ICT Express (SCIE), surveying how quantum computing methods are being applied to portfolio optimization in FinTech.
Research Team
Talented Minds Pursuing Excellence Together
Big Data | AI | Software Education
WSN | Swarm Intelligence | IoT
Computer Vision, LLM, VLM
Computer Vision, LLM, VLM
NL2SQL, Data Analytics, LLM
Quantum Machine Learning, Quantum Computing
Computer Vision, LLM
LLM, Cybersecurity
Publications
Building the Future of Applied AI
ASG-LLM: An LLM-based pipeline for automated scraping code generation in security-sensitive environments
Array, Vol. 31, 101135, Sep. 2026 (SCOPUS) - View Paper
A comprehensive survey of quantum computing approaches for portfolio optimization in FinTech
ICT Express, Aug. 2026 (SCIE) - View Paper
MRS-Agent: A map-reduce framework for quantifiable schema grounding in Text-to-SQL
ICT Express, Jul. 2026 (SCIE) - View Paper
Research Projects
Bridging AI Research with Real-World Impact
Arm Robot for Bin-Picking in Unstructured Environments
The Project aims to develop an intelligent bin-picking system that enables robots to detect, localize, and grasp objects in cluttered, unstructured environments. By combining advanced vision techniques such as instance segmentation, graph-transformer reasoning, depth refinement, shape completion, and 6D pose estimation, the project seeks to overcome challenges like occlusion and sensor noise.
IntelliScrape: An AI-assisted Web Scraping Module Generator
The project aims to develop an AI-assisted module development system that partially automated COOCON’s scraping module creation process. Leveraging artificial intelligence, network traffic analysis, and browser automation technologies, the proposed system aims to reduce manual effort, minimize human error, and accelerate the overall development lifecycle of COOCON developer.
Fall Detection Systems
The project aims to develop a real-time fall detection system using YOLO for high-speed human pose estimation to extract skeletal keypoints from video streams. Through feature engineering, it computes a dozen biomechanical angles capturing body orientation and velocity, which are then fed into a classification-based model to accurately distinguish intentional movements from sudden, unintentional falls.
Members' Activities
Building Excellence Through Collaboration and Learning