About Me

Welcome to my homepage! My name is Bojian Hou (also Bo-Jian Hou), an AI Research Scientist at Meta, with a focus on large-scale machine learning and artificial intelligence systems. My current work centers on ranking, recommendation, and retrieval, as well as large language models (LLMs) and multimodal generative AI.

Before joining Meta, I was a postdoctoral researcher in the Department of Biostatistics, Epidemiology and Informatics at the University of Pennsylvania, where I had the privilege of being advised by Prof. Li Shen.

I received my B.Sc. and Ph.D. degrees in the Department of Computer Science at Nanjing University in 2014 and 2020, respectively. I was fortunate to be supervised by Prof. Zhi-Hua Zhou in the LAMDA Group.

Recent Highlights

Research Interests

As a machine learning researcher, I am interested in both the theoretical foundations and real-world applications of AI. My research spans:

• Interpretability: studying and improving transparency of black-box machine learning models
• Fairness Learning: developing fair and unbiased machine learning algorithms
• Feature Evolvable Learning: learning with dynamic and shifting feature spaces
• Large Language Models: calibration, uncertainty estimation, and response control
• Multimodal Learning: vision-language modeling and cross-modal retrieval
• Recommendation Systems: multi-stage ranking, retrieval, and user modeling
• Semi-Supervised Learning: learning models from both labeled and unlabeled data
• Online Learning: learning models continuously from streaming data
• Biomedical Data Mining: developing machine learning methods for Alzheimer’s disease, dementia, and mental health

I am passionate about bridging fundamental ML research with real-world deployment, and designing AI systems that are not only technically rigorous, but also trustworthy and socially responsible.