Associate Professor Wei Qi Yan

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Associate Professor of Computer Science

Phone: +64 9 921 9999 Ext 5107

Email: wyan [at] aut.ac.nz

Physical Address:

AUT Tower, WT1.07B
No. 2-14 Wakefield Street, Auckland

Postal Address:

Department of Computer Science
School of Engineering, Computer and Mathematical Sciences
Private Bag 92006
Auckland 1142, New Zealand

Memberships and Affiliations:

Biography:

Dr. Wei Qi Yan is the Director of Centre for Robotics & Vision (CeRV), Auckland University of Technology (AUT) and the Director of the joint Lab between AUT and Shandong Academy of Sciences (SDAS); his expertise is in digital security, surveillance, privacy, and forensics; he is leading the Computing Cybersecurity (CCS) Research Group at AUT. Dr. Yan was an exchange computer scientist between the Royal Society of New Zealand (RSNZ) and the Chinese Academy of Sciences (CAS), China. Dr. Yan is a guest (adjunct) professor with PhD supervision of the Chinese Academy of Sciences, China, he was a visiting professor with the National University of Singapore (NUS), the University of Auckland (UOA), and the Massey University, New Zealand.

  • General Chair, ISGV'20
  • Area Chair, ICME'20
  • Associate Editor, Computer Science (Springer Nature), 2020
  • Director, Joint Laboratory between Shandong Academy of Sciences (SDAS) and AUT, 2019
  • Director, CeRV, 2019
  • Deputy Director, CeRV, 2015-2019
  • Publication Chair: ACPR'19
  • Chair, AAGM'19
  • Chair, FakeMM'19
  • Editor-in-Chief Emeritus, IJDCF (IGI Global, ESCI&EI), 2019
  • Editor-in-Chief, IJDCF (IGI Global, ESCI&EI), 2014-2019
  • Program Chair, AVSS'18
  • Chair, FakeMM'18

Teaching Areas:

  • PhDs in Computer Science
  • Masters in Computer Science
  • Bachelors in Computer Science

Research Areas:

  • Computing Cybersecurity: Crypto, Forensics, Surveillance, and Privacy
  • Visual Computing: Graphics, Image, Video, Vision, and Multimedia
  • Computational Intelligence: Event Computing and Deep Learning

Research Summary:

Recent Talks:
  • The State-of-the-art Technologies in Deep Learning
  • PG Mathematics for Deep Learning
  • Advanced Deep Learning
  • Deeply Learn Deep Learning
  • Ten Talks on Deep Learning
  • Secret Sharing
  • Currency Security
  • Analogy: An AI Approach
  • Privacy Preservation of Social Media
  • Intelligent Navigation
  • Visual Event Computing
  • Intelligent Surveillance
  • Content-Based Visual Cryptography
  • Analytics of Visual Cryptography
  • Visual Cryptography and Its Applications

Publications:

  • M. Niitsuma, Y. Tomita, W. Yan, D. Bell. (2018) Towards musicologist-driven mining of handwritten scores. IEEE Intelligent Systems, 33(4): 24-34 (ERA A, IF: 3.53).
  • M. Reis, R. Beers, C. Craigie, W. Yan, R. Klette, P. Shorten, M. Al-Sarayreh, W. Saeys. (2018) Chemometrics and hyperspectral imaging applied to assessment of chemical, textural and structural characteristics of meat. Meat Science, 144:100-109 (IF: 3.55).
  • X. Wu, J. Weng, W. Yan. (2018) Adopting secret sharing into reversible data hiding in encrypted images. Elsevier Signal Processing, 143: 269-281. (IF: 3.470)
  • W. Yan. (2019) Introduction to Intelligent Surveillance (3rd Edition). Springer.
  • X. Wang, W. Yan. (2019) Cross-view gait recognition through ensemble learning. Springer Neural Computing and Applications (IF: 4.21)
  • M. Al-Sarayreh, M. Reis, W. Yan, and R. Klette. (2019) A sequential CNN approach for foreign object detection in hyperspectral images. CAIP’19, pp. 271-283 (Akira Nakamura Award).
  • X. Wang, J. Zhang, W. Yan. (2019) Gait recognition using multichannel convolution neural networks. Springer Neural Computing and Applications (IF: 4.21).
  • X. Wang, S. Feng, W. Yan. (2019) Human Gait Recognition Based on SAHMM, IEEE/ACM Transactions on Biology and Bioinformatics (IF: 2.89).
  • X. Wang, W. Yan. (2019) Human gait recognition based on frame-by-frame gait energy images and convolutional long short term memory. International Journal of Neural Systems, 30(1): 1950027:1-1950027:12 (2020) (IF: 6.507).
  • M. Al-Sarayreh, M. Reis, W. Yan, and R. Klette. (2020) Potential of deep learning and snapshot hyperspectral imaging for classification of species in meat. Food Control (IF: 4.248).
  • Others: Google Scholar; DBLP