Fei Gao is currently with School of Computer Science and Technology, in Hangzhou Dianzi University (HDU). He received his Bachelor Degree in Electronic Engineering and Ph.D. Degree in Information and Communication Engineering from Xidian University (Xi'an, China) in 2009 and 2015, respectively. His Ph.D. advisor is Prof. Xinbo Gao. From Oct. 2012 to Sep. 2013, he was a Visiting Ph.D. Candidate in Prof. Dacheng Tao's Group, in University of Technology, Sydney (UTS) in Australia.

He mainly applies machine learning techniques to computer vision problems. His research interests include visual quality assessment, biometric quality assessment, face recognization, image generation, deep learning, etc. His research results have expounded in 10+ publications at prestigious journals and conferences, such as IEEE T-NNLS, Neurocomputing, and Signal Processing; with one best paper award, i.e. the best poster award in the China National Computer Congress (CNCC) '14. He serverd for a number of journals and conferences, including IEEE Trans. on Image Processing (TIP), IEEE Trans. on Cybernetics (TC), IEEE Trans. on Multimedia (TMM), IEEE Trans. on Circuits and Systems for Video Technology (TCSVT), Information Sciences, Signal Processing, Neurocomputing, and CVPR, etc.


Boimetric Quality Assessment for Facial Images in-the-Wild
supported by the China National Natural Science Foundation (Grant No. 61601158), Jan. 2017 - Dec. 2019, PI: Fei Gao.
Structured Visual Quality Assessment of Large-Scale Heterogeneous Images
supported by the Natural Science Foundation of Zhejiang Province (Grant No. LQ16F030004), Jan. 2016 - Dec. 2018, PI: Fei Gao. 

Latest News

Apr. 2018
Paper submitted to Pattern Recognition was accepted
Paper titled "Blind Image Quality Prediction by Exploiting Multi-level Deep Representations" was accepted by the SCI indexed journal Pattern Recognition Letters .
Aug. 2017
Paper submitted to Pattern Recognition Letters was accepted
Paper titled "Face biometric quality assessment via light CNN" was accepted by the SCI indexed journal Pattern Recognition Letters .
Dec. 2016
Paper submitted to Neurocomputing was accepted
Paper titled "Deep similarity for image quality assessment" was accepted by the SCI indexed journal Neurocomputing.