About me

Jingqing Zhang (张敬卿) is a final-year PhD (HiPEDS) at Department of Computing , Imperial College London under the supervision of Prof. Yi-Ke Guo. His research interest includes Natural Language Processing, Text Mining, Data Mining and Deep Learning. He received his BEng degree in Computer Science and Technology from Tsinghua University, 2016, and MRes degree with distinction in Computing from Imperial College London, 2017. I am also a technical co-founder of Pangaea Data.


  • [06/2020] PEGASUS, a pre-training model tailored for abstractive text summarization which achieves state-of-the-art on 12 datasets, is now public (including code and checkpoints). This work is completed together with my excellent colleagues during my internship at Google Research, Brain Team. PEGASUS is accepted by ICML 2020.
  • [06/2020] Our book about Deep Reinforcement Learning by Springer is available for pre-order now.
  • [04/2020] I was invited to share our research about clinical NLP at LexisNexis HPCC Tech Talk. Video
  • [02/2019] I was invited to share our research about clinical NLP at Elsevier: talk and slides.
  • [10/2019] Two papers accepted by BIBM 2019. One about unsupervised phenotype annotation on medical notes [more] and the other using VAE to extract low dimentional features from multi-omics data [more].
  • [04/2019] TensorLayer 2.0 has been released! [Github] [Doc]
  • [03/2019] Our paper about zero-shot text classification was presented as a talk in NAACL-HLT’19 [more].
  • [12/2018] Together with Dr. Luo Mai, we gave a talk at GDG DevFest London 2018 about TensorLayer: video
  • [10/2018] I gave a talk at the 2018 HPCC Systems Community Day: video and slides.
  • [08/2018] Our papers about traffic prediction using online search query appeared in KDD’18 and ACMMM’18.
  • [03/2018] Our Chinese Deep Learning book is now published: “Deep Learning Using TensorLayer” 《深度学习:一起玩转TensorLayer》[Press] [Github]


Selected Projects on GitHub