معرفی
Xia Hu is an Associate Professor in the Department of Computer Science at Rice University. His research focuses on data science, interpretable machine learning, automated machine learning, and network analytics. He leads projects such as AutoKeras, an open-source automated deep learning system widely adopted in industry. His work integrates machine learning with real-world applications in healthcare and production systems like TensorFlow and Bing. Dr. Hu holds a PhD from Arizona State University (2015), and has received prestigious awards including the NSF CAREER Award and ACM SIGKDD Rising Star Award.
Education:
- PhD, Computer Science, Arizona State University (2015)
- Master's Degree, Computer Science, Beihang University (2009)
- Bachelor's Degree, Computer Science, Beihang University (2006)
Research Interests: Dr. Hu explores automated machine learning (AutoML) techniques, interpretable AI systems, and ethical considerations in algorithmic fairness. His work bridges theory and practice, addressing challenges in model efficiency, bias mitigation, and healthcare applications. Recent projects include improving LLM compression, fairness in graph neural networks, and leveraging AI for medical diagnosis prediction.
Publications Trends: His recent articles emphasize large language model optimization (e.g., quantization, compression), fairness in AI systems, and healthcare applications like risk assessment in heart transplants. He also contributes to foundational research in explainable AI and data-centric methodologies.
Awards:
- ACM SIGKDD Rising Star Award (2021)
- NSF CAREER Award (2018)
- Multiple Best Paper nominations (ICDM 2019, WWW 2019)
Labs & Collaborations: His group develops open-source tools like AutoKeras and collaborates with industry leaders (e.g., Apple, Bing). Research spans interdisciplinary projects combining AI with healthcare, cybersecurity, and network analysis.
