About me

Welcome to Wei-Lin Chiang’s page!

  • I am a first-year PhD student in the UC Berkeley RISElab.
  • I obtained my bachelor’s and Master’s degree from National Taiwan University under the supervision of Prof. Chih-Jen Lin.
  • My research interests include optimization for machine learning, data mining, scalable ML algorithms and its system design.
  • I enjoy developing ML softwares and I am always happy to learn how it is being used! Email me if you have questions or find our softwares useful.
  • More details can be found in my CV.

Work Experience

  • Intern@Google Research, Mountain View (Dec. 2018 - Mar. 2019)
    Developing efficient algorithms for training large and deep GCN models
  • Intern@Alibaba Group, Hangzhou (July 2017 - Sept. 2017)
    Developing distributed ML algorithms on Alibaba’s parameter server (KunPeng)
  • Intern@Microsoft Research Asia, Beijing (Dec. 2016 - Feb. 2017)
    Investigating distributed training methods on deep learning frameworks
  • Intern@Microsoft, Redmond (July 2016 - Oct. 2016)
    Developing large-scale ML algorithms on Microsoft’s distributed platform (REEF)

Publications (Google Scholar Profile)


  • Cluster-GCN
    TensorFlow implementation of an efficient algorithm for large (million-scale) and deep GCN
    Achieved state-of-the-art performance on some public datasets (e.g., PPI, Reddit)
  • Distributed LIBLINEAR
    Distributed extension of a widely-used linear classification package, LIBLINEAR
    Developed L1-regularized LR solver for solving large (billion-scale) tasks
  • Multi-core LIBLINEAR
    Multi-core extension of a widely-used linear classification package, LIBLINEAR
    Developed efficient parallel algorithms for primal and dual solvers