Zheng-Hua Tan
Scholar

Zheng-Hua Tan

Google Scholar ID: fugL2E8AAAAJ
Professor of Machine Learning and Speech Processing, Aalborg University and Pioneer Centre for AI
Machine learningdeep learningself-supervised learningspeech processingmultimodal.
Citations & Impact
All-time
Citations
6,117
 
H-index
34
 
i10-index
93
 
Publications
20
 
Co-authors
96
list available
Contact
Resume (English only)
Academic Achievements
  • - Over 250 refereed journal and conference publications in machine learning, deep learning, self-supervised learning, pattern recognition, speech and speaker recognition, noise-robust speech processing, multimodal signal processing, and social robotics
  • - IEEE Signal Processing Society 2022 Best Paper Award
  • - International Speech Communication Association (ISCA) 2022 Best Research Paper Award
Research Experience
  • - Visiting Scientist/Professor at the Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT), Cambridge, USA, in 2022, 2017, and 2012
  • - Associate Professor in the Department of Electronic Engineering at Shanghai Jiao Tong University, China
  • - Postdoctoral fellow at AI Spoken Language Lab, Department of Computer Science at KAIST, Korea
Education
  • - B.S. in Electrical Engineering from Hunan University, China, in 1990
  • - M.S. in Electrical Engineering from Hunan University, China, in 1996
  • - Ph.D. in Electronic Engineering from Shanghai Jiao Tong University, China, in 1999
Background
  • Professor of Machine Learning and Speech Processing at the Department of Electronic Systems, Aalborg University (AAU), Denmark. He is a Co-Head of the Centre for Acoustic Signal Processing Research (CASPR), the Machine Learning Research Group Leader, and the Head of the Electrical and Electronic Engineering (EEE) Doctoral Programme at Aalborg University, Denmark. He is also a Co-Lead of the Pioneer Centre for Artificial Intelligence, Denmark.
Miscellany
  • His teaching focuses on machine learning and AI. He has established and taught several courses including Machine Learning, Deep Learning, Self-Supervised Learning, and Introduction to AI. He has served as an Editorial Board Member/Associate Editor for several journals and held important roles in various international conferences.