Assistant Professor of Computer Science
Education
- 2023, Doctoral Degree, Information Systems, Carnegie-Mellon University
- 2016, Master's Degree, Computer Science, University of Toronto
- 2015, Bachelor's Degree, Computer Engineering, University of Cincinnati
Biography
Dr. Yue Zhao is an Assistant Professor of Computer Science at the University of Southern California. His research primarily focuses on advancing machine learning (ML) and data mining in areas such as anomaly detection, graph neural networks, ML systems, and healthcare AI, contributing over 40 papers to leading venues. Dr. Zhao is recognized for his work in open-source ML systems, having created more than 10 projects with over 20,000 GitHub stars and 20 million downloads. His notable projects, including PyOD, PyGOD, TDC, and ADBench, are used in organizations like NASA and Morgan Stanley for high-stakes applications. He has received awards such as the AAAI New Faculty Highlights Awards, Norton Fellowship, Meta AI4AI Research Award, and the CMU Presidential Fellowship. In his professional capacity, he serves as an associate editor of IEEE Transactions on Neural Networks and Learning Systems (TNNLS), an action editor of the Journal of Data-centric Machine Learning Research (DMLR), a workflow co-chair for KDD 2023, and a program committee member for numerous ML conferences.
Research Summary
I build reproducible, automated, and scalable machine learning (ML) and data mining (DM) benchmarks, algorithms, and systems, with a focus on but not limited to anomaly detection, graph neural networks, and healthcare for AI.
1. Benchmark various learning algorithms for fair evaluation and new insights.
2. Automate ML by model selection and hyperparameter optimization.
3. Design large-scale ML systems for real-world applications.
4. Develop open-source ML tools to support applications in healthcare, finance, and more.
Research Keywords: (1) Data mining: Anomaly/Outlier/Out-of-Distribution (OOD) Detection, Unsupervised ML, Graph Neural Networks (2) Open Systems: ML Systems, Automated ML, (3) Applications: AI for Science, e.g., healthcare, biology, and finance.
