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XJTU Doctor honored with 2023 World Artificial Intelligence Conference Youth Outstanding Paper Award

August 28, 2023
  L M S

The award ceremony for the 2023 World Artificial Intelligence Conference Youth Outstanding Paper Award recently took place in Shanghai. Dr. Yang Yan from the School of Mathematics and Statistics at Xi'an Jiaotong University (XJTU) was honored with the award for her work "ADMM-CSNet: A Deep Learning Approach for Image Compressive Sensing."

Dr. Yang's paper was published in the top international journal of artificial intelligence, IEEE Transactions on Pattern Analysis and Machine Intelligence. It has been cited 413 times on Google Scholar and has received high praise from experts in various fields.

Furthermore, her research has found applications in more than 10 different domains, including medical imaging, intelligent communications, and geological exploration.

The World Artificial Intelligence Conference is jointly organized by the National Development and Reform Commission, Ministry of Industry and Information Technology, Ministry of Science and Technology, Cyberspace Administration of China, Chinese Academy of Sciences, Chinese Academy of Engineering, China Association for Science and Technology, and Shanghai Municipal People's Government.

The conference has established the Young Outstanding Paper Award and held it three times. For this year's selection, a total of 235 papers were submitted by renowned universities, research institutions, and enterprises from both domestic and international sources. After undergoing initial evaluation and final assessment by experts, the award was ultimately granted to 10 papers through a voting process.

Dr. Yang earned her Ph.D. in 2022 from XJTU and is now an assistant professor at the School of Mathematics and Statistics.

Her research spans the intersection of basic artificial intelligence models and algorithms, artificial intelligence and mathematics, and medicine. She has made significant advancements in areas such as AI theories and methods driven by optimization and statistics, as well as deep learning models and methods for medical imaging.