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Kun Yuan (袁坤)

Kun Yuan (袁坤)

Assistant Professor

Center for Machine Learning Research (CMLR), Peking University

Optimization Theory & AlgorithmsMachine LearningSignal ProcessingEfficient LLM Pre-training & Post-trainingAI for MathematicsDistributed & Decentralized Learning

Kun Yuan is an Assistant Professor at the Center for Machine Learning Research (CMLR), Peking University. His research lies in the theoretical and algorithmic foundations of optimization, signal processing, and machine learning. He currently focuses on efficient pre-training and post-training for large language models, and AI for Math.

Before joining Peking University, he was a staff algorithm engineer in the Decision Intelligence Lab at Alibaba (US) Group, led by Prof. Wotao Yin. He completed his Ph.D. in Electrical and Computer Engineering at the University of California, Los Angeles (UCLA) in 2019, under the supervision of Prof. Ali H. Sayed, and was a visiting researcher at EPFL from January to June 2018.

Education

  • Ph.D. in Electrical and Computer Engineering, University of California, Los Angeles (UCLA), 2019 — Advisor: Prof. Ali H. Sayed
  • Visiting Researcher, École Polytechnique Fédérale de Lausanne (EPFL), Jan–Jun 2018

Experience

  • Assistant Professor, Center for Machine Learning Research, Peking University (current)
  • Staff Algorithm Engineer, Decision Intelligence Lab, Alibaba (US) Group — led by Prof. Wotao Yin

Honors & Awards

  • IEEE CloudCom Distinguished Paper Award, 2025
  • IEEE Signal Processing Society Young Author Best Paper Award, 2017 (with Dr. Wei Shi)
  • ICCM Best Paper Award, 2017

Service

  • Associate Editor, IEEE Transactions on Signal Processing (from Jan 2026)
  • Area Chair, NeurIPS (2024, 2025)
  • Area Chair, ICML (2025)