Jongwoo Ko

Hello! I am a Member of Technical Staff at Microsoft AI (MAI), working on post-training frontier language models. My research focuses on advancing model reasoning and capabilities through reinforcement learning and on-policy distillation. Previously, I gained research and industry experience at Amazon AGI and Microsoft. I received my Ph.D. from 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.

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

Selected Publications 📑

(*: Equal Contribution)

Scaling Reasoning Efficiently via Relaxed On-Policy Distillation

Jongwoo Ko, Sara Abdali, Young Jin Kim, Tianyi Chen, Pashmina Cameron
The Fortieth Annual Conference on Neural Information Processing Systems (NeurIPS). 2026. Sydney
ICML 2026 Workshop on Resource-Adaptive Foundation Model Inference (AdaptFM). 2026. Seoul [paper]

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 (50+⭐)]

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 (250+⭐)]
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

Experiences 🌏

Member of Technical Staff @Microsoft AI

Redmond, Washington, United States
Nov. 2026 - Present

Senior Research Scientist @Microsoft

Redmond, Washington, United States
Sep. 2025 - Nov. 2026

Research Intern @Microsoft

Redmond, Washington, United States
Aug. 2024 - Nov. 2024

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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