Mo Zhou Stage Director Prior to this, i received my ph.d. from the electrical and computer engineering dept at johns hopkins university, where i was advised by prof. vishal m. patel. i earned my bachelor’s and master’s degrees from xidian university, under the supervision of prof. zhenxing niu. Co authors zhenxing niu (牛振兴) xidian university le wang xi'an jiaotong university gang hua director of applied science, ai, amazon , inc., ieee & iapr fellow vishal m. patel associate professor,.
About Mo Zhou Stage Director View mo zhou’s profile on linkedin, a professional community of 1 billion members. [email protected] ©2026 viu lab | wordpress theme by superbthemes. Deep neural network classifiers are vulnerable to adversarial attack, where an imperceptible perturbation could result in misclassification. however, the vulnerability of dnn based image ranking. Johns hopkins university bloomberg school of public health: baltimore, md, us 2013 09 to 2017 05 | research assistant (center for health services and outcomes research).
Mo Zhou Ifds Deep neural network classifiers are vulnerable to adversarial attack, where an imperceptible perturbation could result in misclassification. however, the vulnerability of dnn based image ranking. Johns hopkins university bloomberg school of public health: baltimore, md, us 2013 09 to 2017 05 | research assistant (center for health services and outcomes research). Career & education history phd student johns hopkins university (jhu.edu) 2021 – present research assistant xi'an jiaotong university (xjtu.edu). He is also a current phd student at johns hopkins university, studying deep learning and computer vision. he published a couple of papers in top tier ai related academic conferences including cvpr, iccv, eccv, etc., as well as top tier ai related academic journals such as ieee t pami. He is a second year ph.d. student at johns hopkins university. mo has been working on deep learning, computer vision covering research topics such as object detection, adversarial attack, deep metric learning, cross modal retrieval, and age estimation. [c02] mo zhou, vishal m. patel, “enhancing adversarial robustness for deep metric learn ing,” in proc. ieee conf. on computer vision and pattern recognition (cvpr), 2022.
Mo Zhou The Glimmerglass Festival Career & education history phd student johns hopkins university (jhu.edu) 2021 – present research assistant xi'an jiaotong university (xjtu.edu). He is also a current phd student at johns hopkins university, studying deep learning and computer vision. he published a couple of papers in top tier ai related academic conferences including cvpr, iccv, eccv, etc., as well as top tier ai related academic journals such as ieee t pami. He is a second year ph.d. student at johns hopkins university. mo has been working on deep learning, computer vision covering research topics such as object detection, adversarial attack, deep metric learning, cross modal retrieval, and age estimation. [c02] mo zhou, vishal m. patel, “enhancing adversarial robustness for deep metric learn ing,” in proc. ieee conf. on computer vision and pattern recognition (cvpr), 2022.
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