Shaohan Huang

Shaohan Huang is a researcher at Beihang University, China, actively contributing to top software engineering conferences including ASE and SANER with innovative work in log analysis and anomaly detection.

His research focuses on the integration of artificial intelligence with software engineering, particularly in log analysis and anomaly detection. Key interests include:

• Lightweight expert mixture models for cross-system log anomaly detection (LogMoE)
• Guiding large language models to interpret system logs for question answering (GLOSS)
• Applications in software reliability and maintenance

His work demonstrates a strong emphasis on practical solutions for log-based software analysis, combining machine learning and natural language processing techniques to enhance DevOps workflows and system reliability.

No scientific awards were mentioned in the available sources.

Information regarding student advising, research grants, and laboratory affiliations is not provided in the current data.