Profile Overview
Name: Joonhyung Lee
Position: AI Research Scientist
Company: NAVER Corp
Location: Republic of Korea
LinkedIn: [Joonhyung Lee](https://www.linkedin.com/in/veritas9872)
GitHub: [veritas9872](https://github.com/veritas9872)
Slideshare: [Joonhyung Lee](https://www.slideshare.net/ssuserc416e2)
Professional Background
- Current Role: AI Research Scientist at NAVER Corp
- Industry: Technology / Software / Internet
- Specializations: Artificial Intelligence, Deep Learning, Machine Learning
Education
- Alma Mater: Korea Advanced Institute of Science and Technology (KAIST)
Technical Contributions and Projects
Joonhyung Lee has completed various influential projects and contributions in the field of AI and Medical Imaging. His GitHub profile ([veritas9872](https://github.com/veritas9872)) reveals multiple notable projects, including:
- Medical-Imaging-Tutorial: Documented work on MRI and X-ray CT imaging using techniques like SENSE, GRAPPA, and linear CT reconstruction.
- fastMRI-kspace: Code for tackling the fastMRI challenge, demonstrating expertise in MRI acceleration techniques.
- Memory-Efficient-Self-Attention: Implementation of efficient self-attention in neural networks, indicating a deep understanding of optimization in machine learning models.
- Knowledge-Distillation-Task: Work on distilling knowledge in neural networks using the CIFAR10 dataset, showcasing skills in model compression and efficiency.
Research and Publications
- Scholar Profile: [Google Scholar](https://scholar.google.com/citations?user=f21CmP0AAAAJ&hl=ko)
- SlideShare Presentations: Joonhyung has contributed several high-impact presentations on cutting-edge AI topics such as:
- DeepLab V3+: Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
- AlphaGo Zero: Mastering the Game of Go Without Human Knowledge
- StarGAN and InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
Key Presentations
1. DeepLab V3+::
- Focus: Semantic image segmentation using encoder-decoder architecture with atrous separable convolution.
- Views: 2,298
2. AlphaGo Zero:
- Focus: Reinforcement learning and game mastery without human knowledge.
- Views: 533
3. StarGAN:
- Focus: Generative Adversarial Networks (GANs) for diverse image translation tasks.
- Views: 1,112
Professional Skills and Interests
Joonhyung Lee's areas of expertise include:
- AI and Machine Learning: Specializing in convolutional neural networks (CNNs), generative adversarial networks (GANs), reinforcement learning, and segmentation algorithms.
- Deep Learning: A particular focus on image processing and medical imaging, highlighted through various repositories and projects.
Highlighted Skills
- Image Imaging
- Medical Imaging (CT and MRI)
- Reinforcement Learning
- Semantic Segmentation
- Self-Attention Mechanisms
- Knowledge Distillation
- AI Research and Algorithm Development
Social and Professional Contributions
- Presentations and Tutorials: Prolific in the academic and professional community with tutorials and educational contributions on platforms like Slideshare and GitHub.
- Research Impact: Active contributor to advancements in deep learning methods related to biomedical imaging, CNN efficiency, and GAN applications.
Joonhyung Lee stands out as a highly skilled AI research scientist with a solid educational foundation from KAIST and a prolific presence in professional and academic communities. His role at NAVER Corp focuses on leveraging cutting-edge AI techniques to innovate and solve complex problems in technology and healthcare.
