Researcher profile / trustworthy AI and research systems
Hanyong Lee이한용
Building trustworthy NLP and autonomous research systems
I build language systems that remain useful under noisy, adversarial, and real-world conditions, and I care as much about disciplined execution as I do about model quality.
Research focus
- Trustworthy NLP
- Autonomous Research Systems
- LLM-based Applications
- Experiment Governance
- Robust Language Understanding
My work connects trustworthy NLP, LLM applications, and research infrastructure, with an emphasis on governed workflows, evidence-aware evaluation, and AI systems that can be inspected, resumed, and trusted.
Overview
Research snapshot
A concise view of the questions, environments, and deployment mindset shaping my work.
Featured Build
Project spotlight
A representative system that reflects how I think about AI research, tooling, and reliability.
AutoLabOS
An operating system for autonomous research
AutoLabOS is a research systems project for running literature-grounded, checkpointed, and inspectable workflows from paper collection to manuscript drafting. Instead of treating research as a single generation step, it structures the process as a governed loop with explicit review, evidence tracking, and resumable state.
TypeScriptNode.jsReactOpenAICodex CLISemantic Scholar
Fixed multi-stage workflow for research execution instead of open-ended agent drift
Checkpointed runs with inspectable artifacts and resumable progress
Evidence-bound claim review that limits conclusions to what the run actually supports
Terminal and web interfaces for operating autonomous research pipelines
Output
Selected publications
Representative publications across phishing defense, adversarial robustness, dialogue systems, and practical language model development.
2025
BitAbuse: A Dataset of Visually Perturbed Texts for Defending Phishing Attacks
New Mexico, USA | April 29 - May 4, 2025
View publication2025
GoodGPT: Counseling-chat
Las Vegas, USA | January 11 - 14, 2025
Conference record2024
An Efficient Fine-Tuning of Generative Language Model for Aspect-Based Sentiment Analysis
Las Vegas, USA | January 5 - 8, 2024
Conference record2023
Exploitation of Character-Wise Language Model for Recovering Adversarial Text
Conference publication
Conference record2021
An Efficient Neural Network based on Early Compression of Sparse CT Slice Images
pp. 1-5 | doi: 10.1109/PlatCon53246.2021.9680749
Conference recordJourney
Academic timeline
From computer science training to current doctoral research in AI.
Ph.D. Course, Department of Artificial Intelligence
Chung-Ang University
M.Sc. Course, Department of Artificial Intelligence
Chung-Ang University
Intern
S2W Inc.
B.Sc. Course, School of Computer Science and Engineering
Chung-Ang University
Hansung Science High School
Science-focused secondary education
Impact
Awards and selected builds
Recognition and projects that connect academic research with deployable AI systems.
- 3rd Prize, 2022 AI Graduate School Challenge, LG
- 3rd Prize, 2021 Text Ethics Verification Data Hackathon Competition, National Information Society Agency (NIA)
AutoLabOS
Designed and built an autonomous research system that organizes literature review, hypothesis generation, experiment planning, review gating, and manuscript drafting inside a governed execution loop.
Open-source projectAutomatic Generation of Children's Song Lyrics and Improvement of Lyric Quality Based on Large Language Model
Research and development project focused on creative language generation and quality improvement with large language models.
Integrated Framework for Automatic Neural Network Generation and Deployment Optimized for Runtime Environments
Developed an end-to-end framework for generating and deploying neural networks across runtime-constrained environments.
In cooperation with ETRICapabilities
Tech stack
Tools I use to move from research ideas to governed experiments, prototypes, and production-facing systems.
PythonJavaCC++C#JavaScriptTypeScriptSwiftHTML5CSS3
PyTorchTensorFlowHugging FaceLangChainLangGraphOpenAIOpenAI AgentsSemantic Scholarscikit-learnPandasTensorFlow LiteONNXWeights and Biases
Node.jsNext.jsReactVitestFastAPIFlaskDjangoUnityAndroid StudioOpenGLLinuxmacOSWindowsRaspberry PiVS CodeVim
Coverage
In the news
Selected media and university coverage related to my research and collaborations.
Contact
Let's build something meaningful.
I'm especially interested in trustworthy NLP, autonomous research systems, and collaborations that turn strong ideas into reliable and inspectable AI products.