About me

Xiang Xu is a Senior Applied Scientist at AWS AI Labs, specializing in digital identity and AI security. His current research interests include digital identity, digital trust, and AI Security by exploring multi-modality foundational models, generative models, and security of foundational models. He and his team are committed to developing robust systems that counter presentation, deepfake, and adversarial attacks to protect the digital identity and maintain trust.

Before joining Amazon, he obtained his Ph.D. degree from the University of Houston under the mentorship of Professor Ioannis A. Kakadiaris in 2019. With over a decade of experience in biometric research, He has contributed to advancements in detection, alignment, 3D face reconstruction, liveness detection, and recognition. His expertise extends to multi-modal computer vision, encompassing image and text retrieval, and domain adaptation. Additionally, he has been a reviewer for several computer vision conferences and journals, such as CVPR, ECCV, ICCV, and IJCV.

Prospective interns: If you are interested in internship position in my team (Ph.D. student preferred), please email me your CV and a short research statement.

Recent News

  • [2024/04] I am honered to serve as the keynote speaker for 5th Chalearn Face Anti-Spoofing Workshop and Challenge @ CVPR2024 [Link]

  • [2024/04] One of our paper "Sharpness-Aware Optimization for Real-World Adversarial Attacks for Diverse Compute Platforms with Enhanced Transferability" is accepted in AdvML@CVPR2024 [Link]

Selected Publications

For most updated and comprehensive publication list, please check Google Scholar.


 

Sharpness-aware optimization for real-world adversarial attacks for diverse compute platforms with enhanced transferability
Muchao Ye, Xiang Xu, Qin Zhang, Jon Wu
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2024
Paper

 

Learning self-consistency for deepfake detection
Tianchen Zhao, Xiang Xu, Mingze Xu, Hui Ding, Yuanjun Xiong, Wei Xia
Proceedings of the IEEE/CVF international conference on computer vision, 2021 (Oral presentation)
Paper

 

On Improving Temporal Consistency for Online Face Liveness Detection System
Xiang Xu, Yuanjun Xiong, Wei Xia
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021 (Best Paper Award)
Paper

 

On Improving the Generalization of Face Recognition in the Presence of Occlusions
Xiang Xu, Nikolaos Sarafianos, Ioannis Kakadiaris
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2020
Paper

 

d-SNE: Domain Adaptation using Stochastic Neighborhood Embedding
Xiang Xu, Xiong Zhou, Ragav Venkatesan, Gurumurthy Swaminathan, Orchid Majumder
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019 (Oral presentation)
Paper

 

Adversarial Representation Learning for Text-to-Image Matching
Nikolaos Sarafianos, Xiang Xu, Ioannis A. Kakadiaris
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019
Paper

 

Deep Imbalanced Attribute Classification using Visual Attention Aggregation
Nikolaos Sarafianos, Xiang Xu, Ioannis A. Kakadiaris
Proceedings of European Conference on Computer Vision, 2018
Paper

Resume

Experience

  1. Senior Applied Scientist

    2019 — Present

    AWS AI Labs

Education

  1. University of Houston

    2014 — 2019

    PH.D. in Computer Science

  2. Beijing University of Posts and Telecommunications

    2009 — 2013

    B.S. IN Telecommunication Engineering

Portfolio