Shuai Zheng

Ph.D. Candidate
Department of Computer Science and Engineering
Hong Kong University of Science and Technology
Clear Water Bay, Kowloon, Hong Kong, China
Office: Room 4215, Academic Building (near lift 19)
szhengac@cse.ust.hk
Github

About Me

I am currently a fourth-year Ph.D. candidate at Hong Kong University of Science and Technology, working on the topic of stochastic optimization and deep learning with James T. Kwok. I worked as an Applied Scientist Intern at AWS Deep Learning. I obtained my M.Phil. degree in Computer Science and Engineering from Hong Kong University of Science and Technology in 2015. Before joining HKUST, I received my Bachelor degree in Software Engineering from Beijing Jiaotong University in 2013.

Research Interests

  • Large-Scale Machine Learning Algorithm
  • Stochastic Convex Optimization and Distributed Optimization
  • Optimization in Deep Learning
  • Deep Learning
  • Reinforcement Learning
  • Neural Machine Translation

Working Experience

  • Applied Scientist Intern, AWS Deep Learning, Amazon AI
    Palo Alto, CA, USA, Feb 2018 - Aug 2018
  • Research Intern, VIPL Group, Institute of Computing Technology, Chinese Academy of Sciences
    Beijing, China, August 2012 - April 2013

Projects

  • Gluon NLP: GluonNLP is a toolkit that enables easy text preprocessing, datasets loading and neural models building to help you speed up your Natural Language Processing (NLP) research.

Publications

  1. Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data [supplementary]
    Shuai Zheng, James T. Kwok
    The 35th International Conference on Machine Learning (ICML), Stockholm, Sweden, July 2018

  2. Follow the Moving Leader in Deep Learning [supplementary]
    Shuai Zheng, James T. Kwok
    The 34th International Conference on Machine Learning (ICML), Sydney, Australia, August 2017

  3. Fast-and-Light Stochastic ADMM [supplementary] [longer arxiv version]
    Shuai Zheng, James T. Kwok
    The 25th International Joint Conference on Artificial Intelligence (IJCAI), New York, New York, USA, July 2016

  4. Fast Nonsmooth Regularized Risk Minimization with Continuation [supplementary]
    Shuai Zheng, Ruiliang Zhang, James T. Kwok
    The 30th AAAI Conference on Artificial Intelligence (AAAI), Phoenix, Arizona, USA, Feb 2016

  5. Asynchronous Distributed Semi-Stochastic Gradient Optimization [supplementary]
    Ruiliang Zhang, Shuai Zheng, James T. Kwok
    The 30th AAAI Conference on Artificial Intelligence (AAAI), Phoenix, Arizona, USA, Feb 2016

  6. Accurate Integration of Aerosol Predictions by Smoothing on a Manifold [code][data]
    Shuai Zheng, James T. Kwok
    The 28th AAAI Conference on Artificial Intelligence (AAAI), Quebec City, Canada, July 2014

  7. Flexible Navigation in Smartphones and Tablets using Scalable Storyboards
    Shuai Zheng, Luis Herranz, Shuqiang Jiang
    The 3rd ACM International Conference on Multimedia Retrieval (ICMR), Dallas, Texas, USA, April 2013

Preprints

Awards

  • Postgraduate Studentship, HKUST 2015-Present
  • Travel Award, AAAI 2014, IJCAI 2016, ICML 2017, 2018
  • Undergraduate Scholarship, BJTU 2012

Academic Services

  • PC member for ACML 2018, AAAI 2019
  • Reviewer of ICML 2017, NIPS 2018
  • Reviewer of Machine Learning
  • Reviewer of IEEE Access
  • Reviewer of IEEE/ACM Transactions on Networking (TON)
  • Reviewer of IEEE Transactions on Signal and Information Processing over Networks (IEEE TSIPN)
  • Reviewer of IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS)

Talks & Presentations

  • Scalable Neural Machine Translation
    Palo Alto, CA, USA, August 2018, Amazon AI
  • Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data [video]
    Stockholm, Sweden, July 2018, ICML
  • Optimization in Deep Learning
    Hangzhou, Zhejiang, China, September 2017, Alibaba
  • Follow the Moving Leader in Deep Learning [video]
    Sydney, Australia, August 2017, ICML

Teaching Experience

  • TA of COMP5212 Machine Learning (PG)
  • TA of MSBD5012 Machine Learning (MSC)
  • TA of COMP4211 Machine Learning (UG)
  • TA of COMP4331 Introduction to Data Mining (UG)
  • TA of COMP2012H Honors Object-Oriented Programming and Data Structures (UG)