– 'Embedding Symbolic Knowledge into Deep Networks' (NeurIPS 2019)
Background
Machine Learning Engineer at TikTok/ByteDance and an independent researcher.
Research focuses on: (1) knowledge-enhanced machine learning, integrating symbolic and formal methods with ML models; (2) safety and trustworthiness of AI models.
Aims to better understand real-world complexities and build more robust, interpretable, and trustworthy models.
Interests include sequential relation modeling, such as visual relation detection, video understanding, and natural language processing.
Also explores how powerful AI models impact society and human cognition.