Laboratories (S-Lab) (Eng)

https://bcilab.handong.edu/

Projects

• BCI-based drone control
• Development of a quantification app for movement disorders
• MRI brain image analysis
• Development of neurofeedback games for depression improvement
• BCI game development

http://cgvlab.handong.edu/

CGV Lab (Computer Graphics & Vision Lab)

CGV Lab focuses on various applications of computer graphics and vision, including image processing, augmented reality, VSLAM, 3D reconstruction & compression, and autonomous vehicles.
We have conducted a wide range of projects, such as AR with cubes, drone control using indoor maps, projector-based touch games, image-based stress measurement, automatic generation of vehicle undercarriage images (in collaboration with VAIDAS), and marker-based multi-user AR games.

Projects

• 3D reconstruction using multi-view images
• 3D reflectance estimation
• Multi-user AR systems
• Feature matching for fisheye lenses
• Initialization robust slam Depth estimation
• Illumination robust place recognition

http://deeplearning.handong.edu/

• NCSoft: Research on speech synthesis style modeling using GANs
• Development of a data model adapter module for interoperation between machine learning training and inference engines (ETRI)
• Development of deep learning engines for video recognition in mobile environments
• Deep learning-based image recognition engine development
• Foundational research on natural language dialogue processing
• Implementation of the deep learning open-source framework WICWIU

Our research focuses on structured prediction, outlier detection, time-series modeling, and natural language understanding, applying these technologies to diverse domains, including healthcare, energy, literature, finance, and imaging.

• Development of machine learning/AI frameworks
• Analysis and prediction of medical data
• Development of a search engine for the Unified Big Data Center
• Fiji solar map development
• Development of automated video summarization technology for surveillance cameras
• Kaggle, Kagglers: Participation in competitions and hackathons

https://isel.handong.edu/

• Development of enhanced automated bug-fixing techniques
• Research on security vulnerability detection and automated patching using bytecode Pre-trained models
• Development of an automatic grading engine for Java programming assignments

Our core values  exploring new technologies, developing effective solutions, and growing together through collaboration.

At LAB INSIGHT, everything we do is for students — we exist to support and empower them. We turn ideas into action, and innovation into real-world results.

https://mcnl.handong.edu/

• Development of an MPEG-DASH (Dynamic Adaptive Streaming over HTTP)-based Augmented Reality streaming system
• Mobile Edge Computing technology for Augmented Reality services
• Construction of a Mesh WiFi network using Raspberry Pi and Software Defined Networking technologies

https://milab.handong.edu

Graduate students collaborate on various research topics related to deep learning and reinforcement learning and participate in multiple projects led by the professor.

Undergraduate students are involved in deep learning-related capstone and engineering project planning or join the S-Lab with an interest in deep learning and machine learning.

• Development of AI-based virtual network management technology
• Development of reinforcement learning models for autonomous driving and parking (VADAS)
• Research on recurrent neural network-based audio compression techniques (June 2020 – November 2020)

Under the supervision of Professor Youngsik Kim, the lab consists of four graduate students and eight undergraduate students, and is located in NTH 317.

• Wake-up Receiver and Analog-to-Digital Converter Chip Design
• Development of multi-camera interfaces
• Development of an image recognition and driving control platform for autonomous driving
• Development of data acquisition and processing devices for ocean observation radar
• Adaptive Echo-canceling Headphone Design
• Pipeline Inspection Robot

• Research on titanium dioxide thin films
• Development of VOC-detecting gas sensors
• Development of an in vitro gut-mimicking analysis and diagnostic platform

https://sirl.handong.edu/

Therefore, our research covers not only Hardware but also Software, System Integration, seamless communication between Software Components, and user experience design. Creating functional, interactive robots provides a strong sense of accomplishment, and the skills acquired in this lab can be applied to various fields beyond robotics.

• ITDA: A robot service that connects emotions
• Research on remote control methods for robotic arms using VR
• Development of 3D avatar design and interaction in virtual environments
• Development of recommendation algorithms for childcare counseling service robots

https://notion.site/Venturers/

Major Awards (2024-2025)

• 2024:

  • Selected for the Preliminary Startup Package Program (4 teams)

  • Selected for the Innopolis Campus Program (4 teams)

  • Grand Prize at the G-star Startup Competition

  • Grand Prize at the 16th Gyeongbuk Women's Startup Idea Competition

  • Grand Prize at the POSTECH Mini I-Core

  • Excellence Award at the Innopolis Campus Startup Capability Enhancement Education

• 2025:

  • Selected for the Innovatech Discovery and Startup Support Program (3 teams)

  • Selected for the Public Technology-Based Market-Linked Startup Exploration Support Program (2 teams)

  • Selected for the Preliminary Startup Package Program (1 team)

  • Selected for the K-Local Startup School Support Program (2 teams)

• For awards prior to 2023, please refer to the Notion link.

http://walab.handong.edu/

• Development of a platform for utilizing proximity-based network resources
• LearnTube: A learning management system utilizing YouTube videos
• CSEE online application integration service
• Development of a wireless tag-based safety support system for children’s commuting and outdoor activities
• LearnTube 2: Enhancement of the YouTube-based learning support service
• Development of a portfolio management system for software engineering majors

Our goal is to enable smooth autonomous driving by processing image data in the ROS environment, recognizing lanes, vehicles, and pedestrians through image processing and machine learning, and optimizing speed and steering control. We also aim to incorporate LiDAR-based control and enhance performance for success in autonomous driving competitions.

• Object recognition and control using machine learning
• Development of lane-changing algorithms
• Optimization of driving control under various environmental conditions

Our S-Lab (Intelligent Systems Lab) conducts research on image processing and artificial intelligence technologies.

Specifically, we focus on medical image processing, deep learning techniques, and applied software development. Our research includes fundamental knowledge acquisition, academic paper studies, system development, the Industrial - Academic Cooperation  projects, engineering project planning, and capstone research.

• Development of software for improving X-ray scatter correction
• Study on machine learning techniques for Grid Artifact suppression
• Development of Bone Suppression software for chest X-ray images