Jongwoo Ko

Hello! I am a Senior Research Scientist at Microsoft ASG. I received my Ph.D. in the Graduate School of AI at KAIST under the supervision of Prof. Se-Young Yun, and my M.S. in Industrial and Systems Engineering at KAIST under the supervision of Prof. Heeyoung Kim. I also have gained diverse research and industry experiences at organizations including Amazon AGI and Microsoft. My research focuses on advancing small foundation models, particularly in (multi-modal) language models.

Contact me: (first-name)(last-name)96 [at] gmail [dot] com [CV / Scholar / Github / LinkedIn]

Selected Publications 📑

(*: Equal Contribution)

DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs

Jongwoo Ko, Tianyi Chen, Sungnyun Kim, Tianyu Ding, Luming Liang, Ilya Zharkov, Se-Young Yun
The Forty-Second International Conference on Machine Learning (ICML). 2025. Vancouver (Oral Presentation) [paper] [code]

DistiLLM: Towards Streamlined Distillation for Large Language Models

Jongwoo Ko, Sungnyun Kim, Tianyi Chen, Se-Young Yun.
The Forty-first International Conference on Machine Learning (ICML). 2024. Vienna [paper] [code (200+⭐)]
Selected as a WINNER in Qualcomm Innovation Fellowship Korea 2024 (QIFK 2024)

Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding

Sangmin Bae*, Jongwoo Ko*, Hwanjun Song^, Se-Young Yun^
The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2023. Singapore [paper] [code (50+⭐)]
🥈 Silver Prize, 30th Samsung Humantech Paper Awards

CUDA: Curriculum of Data Augmentation for Long-tailed Recognition

Sumyeong Ahn*, Jongwoo Ko*, Se-Young Yun
The Eleventh International Conference on Learning Representations (ICLR). 2023. Kigali. (Spotlight) [paper] [code]

FINE Samples for Learning with Noisy Labels

Taehyeon Kim*, Jongwoo Ko*, Sangwook Cho, Jinhwan Choi, Se-Young Yun.
The Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS). 2021. Virtual [paper] [code]
Selected as a WINNER in Qualcomm Innovation Fellowship Korea 2022 (QIFK 2022)

Experiences 🌏

Senior Researcher @Microsoft

Redmond, Washington, United States
Sep. 2025 - Present

Research Intern @Microsoft

Redmond, Washington, United States
Aug. 2024 - Nov. 2024 (12 Weeks)

Applied Scientist Intern @Amazon AGI

Sunnyvale, California, United States
Apr. 2024 - Jun. 2024

Awards & Honors 🏆

Winner, Qualcomm Innovation Fellowship Korea (2024)

DistiLLM: Towards Streamlined Distillation for Large Language Models

Silver Prize, 30th Samsung Humantech Paper Awards (2023)

Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding

Winner, Qualcomm Innovation Fellowship Korea (2022)

FINE Samples for Learning with Noisy Labels

Editor's Choice for Featured Article, IISE Transactions (2022)

Deep Gaussian Process Models for Integrating Multifidelity Experiments with Non-stationary Relationships

Education 🧑‍🎓

Korea Advanced Institue of Science and Technology (KAIST), Seoul, Korea, Mar. 2020 - Aug. 2025

Ph.D in Kim Jaechul Graduate School of Artificial Intelligence (Advisor: Se-Young Yun)

Dissertation: Optimizing the Training Strategies of Small Language Models for On-Device Applications

Korea Advanced Institue of Science and Technology (KAIST), Daejeon, Korea, Mar. 2018 - Feb. 2020

M.S. in Department of Industrial and Systems Engineering (Advisor: Heeyoung Kim)

Thesis: Deep Gaussian Process Models for Integrating Multifidelity Experiments with Non-stationary Relationships

Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea, Mar. 2014 - Feb. 2018

B.S. in Department of Industrial and Systems Engineering (Magna Cum Laude)

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