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✉️ Contact : [email protected] https://github.com/sallysooo ℹ️ LinkedIn : https://www.linkedin.com/in/jisoo-kim-66619b2bb/ 🔗 My Site (currently building…) : xxxx.com

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🍵 About Me

My research centers on anomaly detection and machine learning for security, particularly in the context of intrusion detection and trustworthy AI systems. I am interested in developing data-driven methods for identifying anomalous or adversarial behavior across diverse security domains—network traffic, bot activities, automotive environments, and LLM security.

I am motivated by research that combines rigorous experimentation with practical system building. To this end, I actively engage in reproducing and extending recent research papers, designing security-focused projects and CTF challenges, and exploring how modern deep learning and MLOps practices can support robust, scalable, and security-aware AI systems.

I aspire to become a researcher and engineer who advances reliable and trustworthy AI by connecting theoretical insight with real-world security applications!

🎓 Sookmyung Women’s University (SMWU)

• Major: Data Science & Big Data Engineering / Senior
• GPA : 4.45/4.5
• Recent Interest
  • Core Research: Anomaly Detection, Data-driven Security
  • Security Applications: Bot Detection, Intrusion Detection, Network Security
  • Emerging Interests: LLM Security
• Main Stacks : Linux(Ubuntu/Rocky Linux), Docker, PyTorch, Python

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