Hello! I’m Tiankai Yang, a first-year PhD student of Computer Science at the University of Southern California (USC), supervised by Prof. Yue Zhao. Prior, I earned a Master’s degree in Machine Learning and Data Science from USC and a Bachelor’s degree in Software Engineering from Nankai University, China.

My research focuses on anomaly detection, out-of-distribution detection, and enhancing the robustness and trustworthiness of machine learning models, particularly in the realm of large language models (LLMs).

News

• [01/2025] We have a new paper, PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection, accepted to The Web Conference 2025 Demo Track; see our Preprint.
• [12/2024] We have a new paper evaluating how LLMs can help with anomaly detection (AD-LLM); see our Preprint!
  
• [12/2024] We have a new paper introducing a comprehensive benchmark for NLP anomaly detection (NLP-ADBench); see our Preprint!
• [11/2024] We have a new paper on dynamic prototype updating for multimodal out-of-distribution detection (DPU); see our Preprint!