Felix Juefei Xu (publish under F. Juefei-Xu) received the Ph.D. degree in Electrical and
Computer Engineering from Carnegie Mellon University. During his Ph.D studies, he
was working in a research group specializing in pattern recognition, machine learning,
computer vision, and image processing, especially as applied to the field of biometrics,
in Carnegie Mellon CyLab Biometrics Center under the supervision of Prof. Marios Savvides.
His current research is focused on a fuller understanding of deep learning where he
is actively exploring new methods in deep learning that are statistically efficient and
adversarially robust. His Ph.D. work is primarily focused on tackling the Pose, Expression, Resolution, Illumination, and Occlusion (Perio) challenges for unconstrained
periocular face recognition using shallow and deep discriminative and generative methods, especially under the dome of self-supervised predictive learning. He also has
broader interests in pattern recognition, computer vision, machine learning, optimization, statistics, compressive sensing, and image processing. He is the recipient of
multiple best/distinguished paper awards, including the Best Poster Paper Award of
the IEEE/IAPR International Joint Conference on Biometrics (IJCB) in 2011, the Best Paper
Award of the IEEE International Conference on Biometrics: Theory, Applications and Systems
(BTAS) in 2015, the Best Student Paper Award of the IEEE BTAS in 2016, the ACM
SIGSOFT Distinguished Paper Award of the IEEE/ACM International Conference on
Automated Software Engineering (ASE) in 2018, and the Best Student Paper Award of the
14th Asian Conference on Computer Vision (ACCV) in 2018.