I study how to tell
synthetic from real.
武汉大学网络空间安全学院博士候选人,研究方向为 多模态深度伪造检测(人脸与语音)、 对抗攻防与声纹隐私保护、音视频取证。 Ph.D. candidate at Wuhan University, researching multimedia security — deepfake detection, adversarial robustness, and audio-visual forensics.
Multimedia SecuritySpeech Deepfake Detection 语音深度伪造检测
Detecting AI-generated and spoofed speech across real-world channels — real-time communication, speaker-specific fingerprints, editing localization, and generalisation gaps.
检测真实信道中的 AI 合成与伪造语音——实时通信、说话人特异性指纹、 语音编辑定位与泛化鸿沟。
Adversarial & Privacy Protection 对抗与隐私保护
Adversarial examples and defenses for speaker recognition and voice privacy — low-cost, universal, and real-time.
面向声纹识别与语音隐私的对抗攻防——低开销、通用、实时。
Multimodal Research 多模态研究
Multi-modal learning across audio and video — lip-sync for talking heads, and audio-visual speech recognition under real-world degradation.
音视频跨模态研究——口型同步数字人合成,以及真实世界退化下的音视频语音识别。
Audio-Visual Forensics 音视频取证
Cross-modal forensics for synthetic faces — wavelet-domain cues and speaking-behaviour facial landmarks expose generated content.
面向合成人脸的跨模态取证——小波域线索与说话行为面部关键点揭露伪造内容。
/01 News & Highlights 动态
News · 新闻
Honors & Awards · 荣誉
Experience · 经历
/02 Publications 论文
Grouped by research direction. Underlined name marks me as author. Each paper is tagged with an evidence index — you can look up any of them on Google Scholar.
Speech Deepfake Detection 语音深度伪造检测
7 papersAdversarial & Privacy Protection 对抗与隐私保护
4 papersMultimodal Research 多模态研究
2 papersAudio-Visual Forensics 音视频取证
2 papers/03 Education 教育经历
/04 Notes from the Lab 实验手记
A blog about deepfake detection, adversarial robustness, and the craft of working in multimedia security — written for anyone walking the same road. 这里记录研究中的思考与实验笔记。
Why deepfake detection is really a data problem
Every detector I have worked on eventually bumps into the same wall: the dataset. Notes from the lab on why we should...