Catherine Hae Seung Jeon

Ewha Womans University, Seoul, South Korea

prof_pic.jpg

Hello! Catherine Jeon here. πŸ‘‹

I am a 2nd-year graduate student at Ewha Womans University in Seoul, pursuing a Master’s degree in Computer Science and Engineering. Currently, I work as a graduate research assistant under the supervision of Prof. S.E. Oh, and as a part-time researcher with Prof. N. Kim at Purdue University. Previously, I worked as an undergraduate research assistant with Prof. S.E. Oh at Ewha Womans University and as a visiting researcher with Prof. M.S. Rahman at the University of Texas at El Paso.

Broadly, I’m dedicated to advancing AI agents that can address real-world challenges and ultimately enhance human life. To achieve this goal, I focus on two core missions:

(1) Developing reliable agents that remain robust and effective under real-world conditions. It is well known that even frontier models can fail dramatically in noisy, out-of-distribution, or concept-drifted environments. This creates the need for AI agents that are not only effective on benchmark datasets, but also robust and dependable in real-world deployment. To this end, I use methodologies such as contrastive learning, metric learning, feature embedding networks, data augmentation, and normalization.

(2) Building practical systems that reduce the computational and data requirements while addressing domain-specific problems. In an era where AI technologies are rapidly scaling up, we often face substantial memory, compute, and data costs, which form a major bottleneck to the accessibility of AI. We can address this problem across the entire AI stack and pipeline, from hardware to software and from dataset construction to model inference. In this line of work, I have explored techniques such as continual learning, generative replay, few-shot learning, and data-efficient learning methods, and have published multiple papers.

Building on my background, I am currently deeply interested in (1) developing (1) developing versatile and robust models and (2) designing efficient models that can simulate our complex, physical real-world.

A few moments of my life! πŸ‘©β€πŸŽ“ πŸƒβ€β™€οΈ

News

Aug 10, 2026 Happy to share that my first-authored paper is accepted to CCS 2026.
Mar 15, 2026 Three papers are accepted to the ACM WWW, PAKDD, and JASA in 2026 so far 😎
Jan 13, 2026 A first-authored paper is accepted in the top-tier conference, The Web Conference 2026! πŸŽ‰
Aug 28, 2025 Presented a first-authored paper at the 20th ACM Asia Conference on Computer and Communications Security.
Sep 01, 2024 Joined the AI Security Lab at Ewha Womans University as a graduate student!

Selected publications

  1. CCS
    Brewing Under Pressure: More Realistic Tor Flow Correlation Considering Low FPRs
    Haeseung Jeon, Yeonseo Cho, Nate Mathews, and 3 more authors
    To appear in The 33rd ACM Conference on Computer and Communications Security, 2026
  2. WWW
    RoFiRe: Robust Website Fingerprinting on Real-World Tor Traffic via Improved Augmentation and Normalization
    Haeseung Jeon*, Sujin Kim*, Nate Mathews, and 2 more authors
    In Proceedings of the ACM Web Conference 2026, 2026
  3. ASIACCS
    Enhancing Search Privacy on Tor: Advanced Deep Keyword Fingerprinting Attacks and BurstGuard Defense
    Chaiwon Hwang*, Haeseung Jeon*, Jiwoo Hong, and 4 more authors
    In Proceedings of the 20th ACM Asia Conference on Computer and Communications Security, 2025