Jiangtong Li (李江彤)

Jiangtong Li (李江彤)

PhD Candidate

Shanghai Jiao Tong University

Biography

Jiangtong Li (李江彤) is currently a Ph.D candiadate at Department of Computer Science and Technology in Shanghai Jiao Tong University in China. His also selected into Wenjun Wu Honored Ph.D Class. His research advisors are Prof. Liqing Zhang, Prof. Li Niu and Prof. James Tin-Yau Kwok. Prior to that, he obtained his B.E. degree from the Shanghai Jiao Tong University in 2019.

Previously, he was a research intern in Tencent AI Lab, supervised by Wei Bi and a research assistant supervised by Prof. Hai Zhao.

His research interests include computer vision, natural language processing, especially the language-guided vision understanding and casual inference.

Interests

  • Computer Vision
  • Neural Language Processing
  • Language-guided Vision Understanding
  • Casual Inference

Education

  • PhD in Computer Science, 2019 - Now

    Shanghai Jiao Tong University

  • BSc in Chemistry, 2015 - 2019

    Shanghai Jiao Tong University

Experience

 
 
 
 
 

Ph.D Candidate

MoE Key Lab of Artificial Intelligence, Shanghai Jiao Tong University

Sep 2019 – Present Shanghai, China
Research area include:

  • Language-guided Vision Understanding
  • Casual Inference
  • Image-Text Retrieval
  • Image-Video Retrieval
  • Zero-shot Retrieval
 
 
 
 
 

Research Intern

Tencent AI Lab

Jan 2019 – Sep 2019 Shenzhen, Guangzhou, China
Research on Interactive Dialogue System based on topic transfer and Transfer Learning on Pre-trained Language Model
 
 
 
 
 

Research Asistant

Center for Brain-like Computing and Machine Intelligence, Shanghai Jiao Tong University

Jun 2017 – Jun 2019 Shanghai, China
Research area include:

  • Interactive Dialogue System
  • Word Segementation
  • Neural Machine Translation
  • Neural Language Generation

Publications

(2021). Video Semantic Segmentation via Sparse Temporal Transformer,. The 29th ACM International Conference on Multimedia (ACM MM 2021).

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(2021). Activity image-to-video retrieval by disentangling appearance and motion. Proceedings of the 35th AAAI Conference on Artifical Intelligence (AAAI 2021).

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(2019). Lattice-Based Transformer Encoder for Neural Machine Translation,. The 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019).

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(2019). Effective Subword Segmentation for Text Comprehension. IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP 2019).

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(2018). Modeling Multi-turn Conversation with Deep Utterance Aggregation. Proceedings of the 27th International Conference on Computational Linguistics (COLING2018).

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