I am an AI research fellow at Korea Institute for Advanced Study
(KIAS).
At KIAS, I serve as part of my alternative military service as a technical research personnel until February 2027.
Short BIO: B.S. (IME, POSTECH) →
M.S./Ph.D. (SCLF Lab advised by Prof. Jaewook Lee, IE, SNU) →
Postdoc (CAINS advised by Prof. Jeong Han Kim,
KIAS) including a visiting Postdoc (ParkLabML hosted by Prof. Mi Jung Park,
UBC) → ??
I am always open to collaborations! Please refer to topics of interest below.
Note. Publications with overlap. J: journal, C: conference, W: workshop, and P: preprint.
Nov 2025. One paper on "time series diffusion" was accepted at KDD 2026. See you in Jeju Island!
Sep 2025. One paper on "differential privacy in machine learning" was accepted at NeurIPS 2025. See you in San Diego!
Aug 2025. One paper on "privacy in LLMs and RAG" was accepted at EMNLP Findings 2025.
Jun 2025. I will visit UBC (Vancouver, Canada) as a visiting Postdoc from June to July 2025. I will also attend ICML 2025 in person :)
Mar 2025. I moved to KIAS as an AI Research Fellow!
Jul 2024. I attended ICML 2024 in person. See you in Vienna!
Mar 2024. One paper on "DP-SGD with diffusion models" was accepted at CVPR 2024. See you in Seattle!
Jan 2024. One paper on "diffusion fairness" was accepted at AAAI 2024. See you in Vancouver!
Dec 2023. One paper on "robust generalization" was accepted at NeurIPS 2023.
Jul 2023. Two papers on "generalization in DP-SGD" and "generalization of SGD" were accepted at ICML 2023. See you in Hawaii!
Recent publications and preprints are available on Google Scholar.
[J]: Journal, [C]: Conference, [W]: Workshop. †: equal contribution. *: corresponding author.
[J6] Differentially private upsampling for enhanced anomaly detection in imbalanced data
Yujin Choi, Jinseong Park, Youngjoo Park, Jaewook Lee, Junyoung Byun
Engineering Applications of Artificial Intelligence, 2026
[J5] Modeling Asset Price Process: An Approach for Imaging Price Chart with Generative Diffusion Models
Jinseong Park, Hyungjin Ko, Jaewook Lee
Computational Economics, 2024
[J4] Fast sharpness-aware training for periodic time series classification and forecasting
Jinseong Park, Hoki Kim, Yujin Choi, Woojin Lee, Jaewook Lee
Applied Soft Computing, 2023
[J3] Generating Transferable Adversarial Examples for Speech Classification
Hoki Kim, Jinseong Park, Jaewook Lee
Pattern Recognition, 2023
[J2] Efficient differentially private kernel support vector classifier for multi-class classification
Jinseong Park, Yujin Choi, Junyoung Byun, Jaewook Lee, Saerom Park
Information Sciences, 2023
[J1] Exploring Diverse Feature Extractions for Adversarial Audio Detection
Yujin Choi, Jinseong Park, Jaewook Lee, Hoki Kim
IEEE Access, 2023
[C10] TimeBridge: Leveraging Priors via Diffusion Bridge for Time Series Generation
Jinseong Park†, Seungyun Lee†, Woojin Jeong, Yujin Choi, Jaewook Lee
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2026
[C9] Multi-Class Support Vector Machine with Differential Privacy
Jinseong Park, Yujin Choi, Jaewook Lee
Advances in Neural Information Processing Systems (NeurIPS), 2025
[C8] Safeguarding Privacy of Retrieval Data against Membership Inference Attacks: Is This Query Too Close to Home?
Yujin Choi, Youngjoo Park, Junyoung Byun, Jaewook Lee, Jinseong Park*
EMNLP Findings, 2025
[C7] Are Self-Attentions Effective for Time Series Forecasting?
Dongbin Kim, Jinseong Park, Jaewook Lee, Hoki Kim
Advances in Neural Information Processing Systems (NeurIPS), 2024
[C6] In-distribution Public Data Synthesis with Diffusion Models for Differentially Private Image Classification
Jinseong Park†, Yujin Choi†, Jaewook Lee
The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
[C5] Fair Sampling in Diffusion Models through Switching Mechanism
Yujin Choi†, Jinseong Park†, Hoki Kim, Jaewook Lee, Saerom Park
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024
[C4] Fantastic Robustness Measures: The Secrets of Robust Generalization
Hoki Kim, Jinseong Park, Yujin Choi, Jaewook Lee
Advances in Neural Information Processing Systems (NeurIPS), 2023
[C3] Differentially Private Sharpness-Aware Training
Jinseong Park, Hoki Kim, Yujin Choi, Jaewook Lee
International Conference on Machine Learning (ICML), 2023
[C2] Implicit Jacobian regularization weighted with impurity of probability output
Sungyoon Lee, Jinseong Park, Jaewook Lee
International Conference on Machine Learning (ICML), 2023
[W1] Enhancing non-linear asset volatility forecasting models with investor sentiment and Explainable AI
Seungju Lee, Jinseong Park, Jaewook Lee
Korea Computer Congress (KCC) XAI Workshop, 2023, Best Paper Award (2/37)
[C1] Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples
Sungyoon Lee, Woojin Lee, Jinseong Park, Jaewook Lee
Advances in Neural Information Processing Systems (NeurIPS), 2021
Advised by Prof. Jeong Han Kim.
Hosted by Prof. Mi Jung Park.
Advised by Prof. Jaewook Lee in Statistical Learning & Computational Finance (SLCF) Lab.
Ph.D. (Mar'22 - Feb'25) and M.S. (Mar'20 - Feb'22).
Thesis: Generalization Frameworks for Temporal and Private Deep Learning: From Synthetic Data Generation to Robust Optimization
[Project] COSMAX Dec. 2023 - Sep. 2024
Deep learning prediction and generative models for color cosmetics
[Project] LNG industry research project with POSCO EnergySep. 2019 - Dec. 2019
Researcher, with Prof. Ribin Seo at POSTECH
[Lecturer] Soongsil UniversitySep. 2024 - Feb. 2025
Analysis of Financial Time Series, Fall Semester 2024, School of Finance
[Invited Talks] DesiloJul. 2024
Deep Learning with Differential Privacy
[Attendee] Graduate Summer School on Algorithmic FairnessJul. 2022
Take the summer school organized by Cynthia Dwork, Guy Rothblum, and Noa Dagan, Institute for Pure & Applied Mathematics (IPAM) at UCLA
[Intern] Industrial Data Engineering & Analytics (IDEA) Lab.Sep. 2019 - Dec. 2019
Research Intern, hosted by Prof. Hyunbo Cho at POSTECH
[Intern] SK TelecomJun. 2018 - Aug. 2018
Intern, R&D Digital Transformation Team