Zhuoning Yuan, Ph.D. Senior AI Research Scientist & Tech Lead @ Netflix Email: yzhuoning [at] gmail [dot] com Copy

About Me

I am a Senior AI Research Scientist at Netflix, where I build AI systems with personalized LLMs and VLMs scaling to millions of users. Before that, I received my PhD from University of Iowa advised by Prof. Tianbao Yang. Here is my Google Scholar Citation.

Research Interests

My research sits at the intersection of understanding, generation, and personalization. At Netflix, I am currently leading on:

• Multimodal Agents: Building AI agentic systems for content understanding and multimedia asset curation at scale.

• Generative Models: Training customized diffusion models for creative image and video generation tasks.

Experience

• June 2023 - Present, Senior AI Research Scientist & Tech Lead @ Netflix

• June 2018 - Aug. 2022, Research Intern @ Netflix, General Motors, Tencent AI Lab, KLA

Selected Publications Full List →

• NEW Vera: A Layered Diffusion Model for Content-Preserving Video Editing.

  Hongkai Zheng, Ta-Ying Cheng, Benjamin Klein, Yisong Yue, Zhuoning Yuan
  Transactions on Machine Learning Research (TMLR 2026)
  [Paper][Website][Dataset]

• NEW VOID: Video Object and Interaction Deletion.

  Saman Motamed, William Harvey, Benjamin Klein, Luc Van Gool, Zhuoning Yuan, Ta-Ying Cheng
  European Conference on Computer Vision (ECCV 2026)
  [Paper][Website][Code]

• NEW LoGAN: Multilingual Font Localization with Generative Agents.

  Zhuoning Yuan, Ta-Ying Cheng, Benjamin Klein
  European Conference on Computer Vision (ECCV 2026)
  [Paper][Website]

• LibAUC: A Deep Learning Library for X-risk Optimization.

  Zhuoning Yuan, Dixian Zhu, Zi-Hao Qiu, Gang Li, Xuanhui Wang, Tianbao Yang
  ACM Knowledge Discovery and Data Mining (KDD 2023)
  [Paper][Website][Code]

• Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance.

  Zhuoning Yuan, Yuexin Wu, Zihao Qiu, Xianzhi Du, Lijun Zhang, Denny Zhou, Tianbao Yang
  International Conference on Machine Learning (ICML 2022)
  [Paper][Code]

• Compositional Training for End-to-End Deep AUC Maximization.

  Zhuoning Yuan, Zhishuai Guo, Nitesh Chawla, Tianbao Yang
  International Conference on Learning Representations (ICLR 2022)
  [Paper][Code]

• A New Surrogate Loss and Empirical Studies on Medical Image Classification.

  Zhuoning Yuan, Yan Yan, Milan Sonka, Tianbao Yang
  International Conference on Computer Vision (ICCV 2021)
  [Paper][Code]

• Accelerating Deep Learning with Millions of Classes.

  Zhuoning Yuan, Zhishuai Guo, Xiaotian Yu, Xiaoyu Wang, Tianbao Yang
  European Conference on Computer Vision (ECCV 2020)
  [Paper]

• Stagewise Training Accelerates Convergence of Testing Error Over SGD.

  Zhuoning Yuan, Yan Yan, Rong Jin, Tianbao Yang
  Neural Information Processing Systems (NeurIPS 2019)
  [Paper] [Code]

• Hetero-ConvLSTM: A Deep Learning Approach to Traffic Accident Prediction on Heterogeneous Spatio-Temporal Data.

  Zhuoning Yuan, Xun Zhou, Tianbao Yang
  ACM Knowledge Discovery and Data Mining (KDD 2018)
  [Paper][Code] [Video]

Awards & Competitions

• 1st / 28, OGB Graph Property Prediction (molhiv), October 2021 (by Stanford SNAP)

• 1st / 180, CheXpert Competition, September 2020 (by Stanford ML Group)

• Top 1% (33rd / 3,314), SIIM-ISIC Melanoma Classification, August 2020 (by Kaggle)

Academic Services

• Reviewer, International Conference on Machine Learning (ICML)  ·  2021, 2022, 2023

• Reviewer, International Conference on Learning Representations (ICLR)  ·  2021, 2022, 2023

• Reviewer, Conference on Computer Vision and Pattern Recognition (CVPR)  ·  2021, 2022

• Reviewer, Neural Information Processing Systems (NeurIPS)  ·  2020, 2021

• Reviewer, International Joint Conference on Artificial Intelligence (IJCAI)  ·  2021, 2022, 2023