Xiaojiang Peng

Full Professor, College of Big Data and Internet, Shenzhen Technology University.

 

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Contact

广东省深圳市坪山区兰田路3002号 pengxiaojiang@sztu.edu.cn / xiaojiangp@gmail.com

About Me

Xiaojiang Peng (IEEE Senior Member) is a full professor at the College of Big Data and Internet, Shenzhen Technology University, and serves as the dean of artificial intelligence department. He received his Ph.D. degrees from Southwest Jiaotong University. He was an associate professor at Shenzhen Technology University from 1/11/2020 to 31/12/2023. He was an associate professor at Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences from 9/10/2017 to 31/10/2020. He was a postdoctoral researcher at Idiap, Switzerland from 1/7/2016 to 30/9/2017 where he worked with Prof. Francois Fleuret. He was a postdoctoral researcher at Inria LEAR/THOTH, France from 1/3/2015 to 30/6/2016 where he worked with Cordelia Schmid. He has published more than 70 top journal/conference papers (e.g., TIP, CVPR, ICCV, ECCV, IJCAI, AAAI). His research interests include computer vision, affective computing, and generative AI applications.

Opening positions

We are recruiting Associate/assistant Professors (Researchers), Postdoctors, and Masters. Please send your CV to pengxiaojiang@sztu.edu.cn. Better to have backgrounds and/or foundation in machine learning and/or computer vision research. Looking forward to working with you!

News

  1. The multimodal emotion understanding model Emotion-LLaMA has been accepted at the NeurIPS 2024 conference. 2024/10/16
  2. One paper on facial expression recognition has been accepted by Transactions on Multimedia. 2024/10/16
  3. Two papers on emotion recognition and stance detection were accepted by the top-tier ACM MM 2024 conference. 2024/7/16
  4. Works on content generation authentication of various types of Stable Diffusion were accepted by the top-level PRCV conference in China. 2024/7/10
  5. Causal spatio-temporal reasoning work was accepted by the ICLR conference. 2024/3/10
  6. The dialogue stance detection work was accepted by the NLP conference COLING, and the team ranked third in the video dialogue emotion understanding competition at NAACL. 2024/2/10
  7. Selected for the Stanford University 2022 global top 2% scientists list. 2023/10/25
  8. One paper on multimodal emotion recognition is accepted by ACM MM. 2023/07/17
  9. We are the runner up in the Grand Challenge (MER 2023) of ACM MM. 2023/07/17
  10. Two papers on vehicle smoke detection are accepted by Applied Sciences. 2023/04/17
  11. I was selected by Stanford University as one of the top 2% of scientists in 2021. ( News). 2022/10/21
  12. One paper on rail detection is accepted by ACM MM. 2022/07/02
  13. Special Issue "New Trends in Computer Vision, Deep Learning and Artificial Intelligence" is opened in Mathematics.
  14. One paper on cross-domain facial expression recognition is accepted by Applied Sciences. 2022/05/02
  15. One paper on training large-scale face recognition data is accepted by CVPR. 2022/03/08
  16. One paper on person re-identification is accepted by Pattern Recognition. 2022/01/17
  17. One paper on context emotion recognition is accepted by IJCB2021. 2021/07/01
  18. Two papers on human-object-interaction are accepted by CVPR2021. 2021/03/22
  19. One paper on action anticipation is accepted by Neurocomputing. 2021/01/25
  20. Three papers are accepted by ECCV 2020, topics include noisy supervised learning、multi-label classification、HOI recognition. 2020/07/03
  21. One paper on Product Image Classification with Noisy labels is accepted by CVIU 2020. 2020/04/02
  22. One paper on Large-scale Facial Expression Recognition is accepted by CVPR 2020. 2020/02/4

Awards

  1. 2019年广东省科学进步奖技术发明一等奖, 5/7
  2. 2019年中国人工智能协会吴文俊人工智能科技进步奖二等奖, 4/6
  3. 2019年深圳市科技进步奖二等奖, 4/6
  4. 深圳市孔雀人才C、南山领航人才

Professional Activity

PC/SPC

PC: CVPR (2019-), ECCV (2018-), ICCV (2019-), AAAI (2019-), IJCAI (2018-)

SPC:IJCAI (2021)

Bachelor/master Courses

  1. Deep learning and applications for UG students
  2. Java Programming, Python Programming, Computer Vision for UG students
  3. Neural Networks and Deep Learning, for PG students