Zongheng Yang

News: I'm building SkyPilot, a framework for running Machine Learning and Data Science on any cloud with ease of use and massive cost savings Star. Join us in making the clouds easier and cheaper to use than ever before. Docs, Blog, Media, Podcast, Talk

I'm a postdoctoral researcher in the Sky Computing Lab at UC Berkeley. In 2022, I received my Ph.D. in computer science from UC Berkeley, advised by Ion Stoica. My Ph.D. dissertation uses deep learning to both improve and learn to perform query optimization in data systems.

In a previous life, I worked at Google Brain (TensorFlow & deep learning research; 2016-2017). I received my Bachelors in computer science and math from UC Berkeley in 2015.

Publications

• SkyPilot: An Intercloud Broker for Sky Computing.
  Zongheng Yang*, Zhanghao Wu*, Michael Luo, Wei-Lin Chiang, Romil Bhardwaj, Woosuk Kwon, Siyuan Zhuang, Frank Sifei Luan, Gautam Mittal, Scott Shenker, Ion Stoica. (*equal contribution)
  NSDI 2023. Star
• Machine Learning for Query Optimization.
  Ph.D. dissertation. 2022.
• Balsa: Learning a Query Optimizer Without Expert Demonstrations.
  Zongheng Yang, Wei-Lin Chiang*, Sifei Luan*, Gautam Mittal, Michael Luo, Ion Stoica. (*equal contribution)
  SIGMOD 2022. Arxiv Talk Slides Star
• NeuroCard: One Cardinality Estimator for All Tables.
  Zongheng Yang, Amog Kamsetty*, Sifei Luan*, Eric Liang, Yan Duan, Xi Chen, Ion Stoica. (*equal contribution)
  VLDB 2021 / PVLDB 14. Arxiv Talk Slides Star
• Variable Skipping for Autoregressive Range Density Estimation.
  Eric Liang*, Zongheng Yang*, Ion Stoica, Pieter Abbeel, Yan Duan, Xi Chen. (*equal contribution)
  ICML 2020. Website Code
• Qd-tree: Learning Data Layouts for Big Data Analytics.
  Zongheng Yang, Badrish Chandramouli, Chi Wang, Johannes Gehrke, Yinan Li, Umar Farooq Minhas, Per-Ake Larson, Donald Kossmann, Rajeev Acharya.
  SIGMOD 2020. Website Talk Slides

• Deep Unsupervised Cardinality Estimation.
  Zongheng Yang, Eric Liang, Amog Kamsetty, Chenggang Wu, Yan Duan, Xi Chen, Pieter Abbeel, Joseph M. Hellerstein, Sanjay Krishnan, Ion Stoica.
  VLDB 2020 / PLVDB 13. Arxiv Talk Slides Star

• Learning to Optimize Join Queries With Deep Reinforcement Learning.
  Sanjay Krishnan, Zongheng Yang, Ken Goldberg, Joseph Hellerstein, Ion Stoica.
  arXiv, 2018. Blog
• Ray: A Distributed Framework for Emerging AI Applications.
  Philipp Moritz, Robert Nishihara, Stephanie Wang, Alexey Tumanov, Richard Liaw, Eric Liang, Melih Elibol, Zongheng Yang, William Paul, Michael I. Jordan, Ion Stoica.
  OSDI 2018.

Earlier Work

• Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions.
  Jonathan Shen, Ruoming Pang, Ron J. Weiss, Mike Schuster, Navdeep Jaitly, Zongheng Yang, Zhifeng Chen, Yu Zhang, Yuxuan Wang, RJ Skerry-Ryan, Rif A. Saurous, Yannis Agiomyrgiannakis, Yonghui Wu.
  ICASSP 2018.
• Tacotron: Towards End-to-End Speech Synthesis.
  Yuxuan Wang, RJ Skerry-Ryan, Daisy Stanton, Yonghui Wu, Ron J. Weiss, Navdeep Jaitly, Zongheng Yang, Ying Xiao, Zhifeng Chen, Samy Bengio, Quoc Le, Yannis Agiomyrgiannakis, Rob Clark, Rif A. Saurous.
  INTERSPEECH 2017.
• ZipG: A Memory-efficient Graph Store for Interactive Queries.
  Anurag Khandelwal, Zongheng Yang, Evan Ye, Rachit Agarwal, Ion Stoica.
  SIGMOD 2017.
• Ernest: Efficient Performance Prediction for Large-Scale Advanced Analytics.
  Shivaram Venkataraman, Zongheng Yang, Michael Franklin, Benjamin Recht, Ion Stoica.
  NSDI 2016.
• SparkR: Scaling R Programs with Spark.
  Shivaram Venkataraman, Zongheng Yang, Davies Liu, Eric Liang, Hossein Falaki, Xiangrui Meng, Reynold Xin, Ali Ghodsi, Michael Franklin, Ion Stoica, Matei Zaharia.
  SIGMOD 2016 (industrial track).