Sangyup Lee

Assistant Professor

Department of Computer Science, Incheon National University, South Korea

Ph.D. in Computer Science and Engineering

Graduate of Sungkyunkwan University (DASH Lab)

sangyup.lee@inu.ac.kr

About Me

Assistant Professor, Department of Computer Science @ Incheon National University (2026.03 - Current)
Principal Research Engineer, Hyundai Mobis (현대모비스), Cybersecurity Technology Management Team (2023.02 - 2026.02)
Ph.D. (Combined program) Computer Science, Sungkyunkwan University, Suwon-si, South Korea (2019.08 - 2023.02) (Transfered from SUNY Korea)
Ph.D. Computer Science, State University of New York - Korea, Yeonsu-gu, Incheon, South Korea (2017.02 - 2019.08)
Staff, Ssangyong Information & Communication Corp. (쌍용정보통신), Seoul, Korea (2016.01- 2017.03)
B.S. Computer Software, Kwangwoon University, Seoul, Korea (2010.03 - 2016.02)

I am an AI researcher with expertise in machine learning and deep learning, particularly focused on data feature analysis for security applications. My research spans a variety of areas, including anomaly detection using multivariate time-series data, deepfake detection, encryption and key management systems, and media forensics. I have applied these concepts to real-world projects, such as satellite data analysis, intrusion detection in vehicle Controller Area Networks, and deepfake video detection, where I developed deep learning models tailored to each problem.

Prior to joining academia, I worked at Hyundai Mobis, where I played a key role in developing an automatic vulnerability monitoring service that integrates internal and external data through Retrieval-Augmented Generation (RAG) and large language models (LLMs). This initiative enabled the automation of vulnerability detection and prioritization, significantly reducing response times in security operations.

At Incheon National University, I lead research on AI-based security and data analysis, focusing on multivariate and multimodal data modeling, anomaly detection, and trustworthy AI systems. My goal is to develop scalable and reliable AI technologies that address real-world security challenges while fostering strong collaboration between academia and industry.

Research Interests

A.I. / Machine Learning / Deep Learning / Big Data
Data & A.I.-based Time-series Analysis
- Anomaly Detection
- Forecasting
- Representation learning
- Adversarial examples
Fake Image Detection / Media Forensics
Key Management System / Cryptography