Welcome to Anbu Huang’s HomePage

About me:

A lifelong learner and practitioner, with a strong passion and interest in scientific research and product, achieving business impact by combining effective leadership with deep technical knowledge and skills, continuing to expand the boundaries of knowledge and innovation.

In recent years (2019 - present), I work on the field of AI security and privacy-preserving machine learning, with the goal of building trustworthy artificial intelligence.

Federated Learning and Privacy computing: I am engaged in theoretical and practical aspects of trustworthy machine learning, I participated in the design of the FATE framework, developed a federated vision system, and published several important research papers on federated learning (Publications).

Anti-spoofing: The development of AIGC has greatly facilitated our creativity and brought us tremendous convenience. However, it can also lead to significant losses if exploited by malicious attackers, such as Deepfake. I participated in the design of facial verification work, including liveness detection and facial recognition.

In my past life (2014 - 2018), I also worked on the applied AI, I led a technical team at Tencent, and built the world's largest online music recommender system, serving more than 100 million users around the world. We tried to leverage different AI approaches to analyze our customers' listening history and predict their favorite songs, including but not limited to natural language processing, music information retrieval, deep neural network. This work is challenging and requires us to build statistical models for human emotions and interests.