Prof. Yang-Lang Chang

Professor and Chair of Electrical Engineering at National Taipei Univ of Technology
Chang, Yang-Lang
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SPIE Membership: 1.0 years total | 0.0 years voting
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Area of Expertise: remote sensing, high performance computing, pattern recognition, hyperspectral image analysis, deep learning
Websites: Personal Website | Company Website
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Profile Summary

Yang-Lang Chang received his BS degree in Electrical Engineering from Chung Yuan Christian University, Taiwan; his MS degree in Computer Engineering from Syracuse University; and his PhD degree in Computer Science and Information Engineering from the National Central University, Taiwan. He started his career with NDC IBM Taiwan as a Hardware Design Engineer before joining ALCATEL as a Software Development Engineer. He was a Visiting Scientist of Space Science and Engineering Center at University of Wisconsin-Madison and presently is Professor and Chair in the Department of Electrical Engineering, and Director of High Performance Computing and Deep Learning Lab and NVIDIA-Taipei Tech Embedded GPU Joint Lab in the Department of Electrical Engineering at National Taipei University of Technology. Dr. Chang is a Senior Member of IEEE, a Member of SPIE, Phi Tau Phi Scholastic Honor Society, the Chinese Society of Photogrammetry and Remote Sensing, and the Chinese Society of Image Processing and Pattern Recognition. He has been General Co-Chairs, Workshop Chair, Program Committee members and Session Chairs for several international conferences. He serves as Guest Editors for the special issue on High Performance Computing in Earth Observation and Remote Sensing in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, the special section of Journal of Applied Remote Sensing on High-Performance Computing in Applied Remote Sensing, and the special issue of Remote Sensing on GPU Computing for Geoscience and Remote Sensing. He also served as a General Secretary, and is currently the Chair of Taipei Chapter of IEEE Geoscience and Remote Sensing Society. His research interests are in Remote Sensing, High Performance Computing, Deep Learning, Pattern Recognition, Image Processing, and SAR and hyperspectral images analysis.

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