About | Chaeri Jung

Hello, I’m Chaeri Jung

I am a senior at Sookmyung Women’s University, majoring in Artificial Intelligence and Big Data. I am also gaining hands-on experience as an undergraduate research intern at SNSec Lab, where I explore the intersection of machine learning and cybersecurity.

Currently, I study how AI can be applied to cybersecurity. My current focus is on building anomaly detection systems using Deep Learning and Self-Supervised Learning, aiming to make data-driven security more practical and reliable.

Research Interests

My core research focuses on Data-driven Security. I am particularly interested in leveraging advanced machine learning techniques to solve real-world security challenges:

Deep Learning & Self-Supervised Learning (SSL): Developing models that can learn robust representations from unlabeled data, especially for scenarios where labeled security data is scarce.
Anomaly & Intrusion Detection: Engineering algorithms to identify malicious behaviors and novel threats within complex network traffic and system logs.
Adversarial Machine Learning: Enhancing the robustness of AI models against adversarial attacks and ensuring security in the model’s deployment phase.

Tech Stack & Tools

I use a variety of tools for research and development, focusing on efficient data processing and model implementation:

Main Stacks: Linux, Python, PyTorch, Pandas, Scikit-learn, Git

Vision & Goal

Beyond building high-performance models, I constantly ask: “How reliable and explainable is this model in a real-world security operation?” My goal is to become a security intelligence engineer who builds trustworthy, data-driven defense systems that can withstand evolving digital threats.

Let’s Connect!

I’m always open to discussing research, collaboration, or potential opportunities. Feel free to reach out!