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lhy0718/README.md

Hanyong Lee | 이한용

Building reliable NLP systems for real-world users

Ph.D. Student in Artificial Intelligence at CAU AutoML Lab
Interested in Natural Language Processing, Dialogue Systems, and Trustworthy AI

Email Blog Hugging Face X

I study language technologies that stay useful even when text is noisy, adversarial, or deeply human.

About Me

  • I am a Ph.D. student in the Department of Artificial Intelligence at Chung-Ang University, Seoul.
  • My research focuses on natural language processing, dialogue systems, and robust language understanding.
  • I enjoy turning research ideas into practical AI systems that people can actually use.

Research Snapshot

Topic Details
Current focus Trustworthy NLP, visually perturbed text, and LLM-based applications
Research interests Natural language processing, dialogue systems, evaluation, and deployment
Research style Bridging research ideas with practical AI systems
Based in Seoul, Korea

Tech Stack

Languages

Python Java C C++ C# JavaScript TypeScript Swift HTML5 CSS3

AI / ML

PyTorch TensorFlow Hugging Face LangChain LangGraph OpenAI OpenAI Agents scikit-learn Pandas TensorFlow Lite ONNX Weights and Biases

Web / App / Tools

Node.js Next.js React FastAPI Flask Django Unity Android Studio OpenGL Linux macOS Windows Raspberry Pi VS Code Vim

Timeline

Period Journey
2024.03 - Present Ph.D. Course, Department of Artificial Intelligence, Chung-Ang University
2022.03 - 2024.02 M.Sc. Course, Department of Artificial Intelligence, Chung-Ang University
2021.09 - 2021.12 Intern, S2W Inc.
2015.03 - 2022.02 B.Sc. Course, School of Computer Science and Engineering, Chung-Ang University
2013.03 - 2015.02 Hansung Science High School

Selected Publications

  • H. Lee, C. Lee, Y. Lee, J. Lee. "BitAbuse: A Dataset of Visually Perturbed Texts for Defending Phishing Attacks," Findings of NAACL 2025, New Mexico, USA, April 29 - May 4, 2025. Paper
  • K. Kim, H. Lee, J. Lee. "GoodGPT: Counseling-chat," ICCE 2025, Las Vegas, USA, January 11 - 14, 2025.
  • C. Lee, H. Lee, K. Kim, S. Kim, J. Lee. "An Efficient Fine-Tuning of Generative Language Model for Aspect-Based Sentiment Analysis," ICCE 2024, Las Vegas, USA, January 5 - 8, 2024.
  • H. Lee, J. Lee. "Exploitation of Character-Wise Language Model for Recovering Adversarial Text," ICEIC 2023, 2023.
  • A. Moon, S. Lee, S. Cho, T. Lee, H. Lee, J. Lee. "An Efficient Neural Network based on Early Compression of Sparse CT Slice Images," PlatCon 2021, pp. 1-5. doi: 10.1109/PlatCon53246.2021.9680749

Highlights

Awards

  • 3rd Prize, 2022 AI Graduate School Challenge, LG
  • 3rd Prize, 2021 Text Ethics Verification Data Hackathon Competition, National Information Society Agency (NIA)

R&D Projects

  • 2023.09 - 2024.12 Automatic Generation of Children's Song Lyrics and Improvement of Lyric Quality Based on Large Language Model
  • 2023.03 - 2024.12 Development of an Integrated Framework for Automatic Neural Network Generation and Deployment Optimized for Runtime Environments Cooperation Organization: ETRI (Electronics and Telecommunications Research Institute)

GitHub Snapshot

GitHub metrics

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In the News

Selected media and university coverage

Let's connect and build something meaningful

Portfolio Hugging Face Email

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