Biography
Short Bio: My name is Yue ZHAO (赵越 in Chinese). I am a third-year Ph.D. student at Heinz College, Carnegie Mellon University (CMU). Before joining CMU, I earned my Master degree from University of Toronto, and worked as a senior consultant at PwC Canada. I have coauthored more than 20 papers (in JMLR, TKDE, NeurIPS, etc.) on anomaly detection and its applications in security and healthcare. Service-wide, I am on the conference program committee of KDD, AAAI, and IJCAI, and reviewing for JMLR, TPAMI, and TKDE. I am one of the two recipients of the 2022 Norton Labs Graduate Fellowship.
Outlier detection systems and applications: I build automated, scalable, and accelerated machine learning systems (MLSys) to support large-scale real-world outlier detection applications in security, finance, and healthcare with millions of downloads. I designed CPU-based (PyOD), GPU-based (TOD), distributed detection systems (SUOD) for tabular (PyOD), time-series (TODS), and graph data (PyGOD).
Research outcomes (related to outlier detection if not specified):
| Primary field | Secondary | Method | Year | Venue | Lead author |
|---|---|---|---|---|---|
| machine learning systems | PyOD | 2019 | JMLR | Y | |
| machine learning systems | time series | TODS | 2020 | AAAI | |
| machine learning systems | benchmark | TODS | 2021 | NeurIPS | |
| machine learning systems | SUOD | 2021 | MLSys | Y | |
| machine learning systems | distributed systems | TOD | 2022 | Preprint | Y |
| machine learning systems | graph neural networks | PyGOD | 2022 | Preprint | Y |
| ensemble learning | semi-supervised | XGBOD | 2018 | IJCNN | Y |
| ensemble learning | LSCP | 2019 | SDM | Y | |
| ensemble learning | machine learning systems | combo | 2020 | AAAI | Y |
| ensemble learning | interpretable ML | COPOD | 2020 | ICDM | Y |
| ensemble learning | interpretable ML | ECOD | 2022 | TKDE | Y |
| automated machine learning | graph mining | AutoAudit | 2022 | BigData | |
| automated machine learning | MetaOD | 2021 | NeurIPS | Y | |
| graph neural networks | contrastive learning | CONAD | 2022 | PAKDD | |
| AI x Science | benchmark | HR manage. | 2018 | Intellisys | Y |
| AI x Science | CIBS | 2020 | BIBM | ||
| AI x Science | PyHealth | 2020 | Preprint | Y | |
| AI x Science | benchmark | TDC | 2021 | NeurIPS |
At CMU, I work with Prof. Leman Akoglu (DATA Lab), Prof. Zhihao Jia (Catalyst), and Prof. George H. Chen. Externally, I collaborate with Prof. Jure Leskovec at Stanford University and Prof. Xia “Ben” Hu at Rice University.
Open-source Contribution: I have led or contributed as a core member to more than 10 ML open-source initiatives, receiving 13,000 GitHub stars (top 0.002%: ranked 800 out of 40M GitHub users) and >8,000,000 total downloads. Popular ones:
- PyOD: A Python Toolbox for Scalable Outlier Detection (Anomaly Detection).
- TOD: Tensor-based outlier detection–First large-scale GPU-based system for acceleration!
- SUOD: An Acceleration System for Large-scale Heterogeneous Outlier Detection.
- anomaly-detection-resources: The most starred resources (books, courses, etc.)!
- PyTorch Geometric (PyG): Graph Neural Network Library for PyTorch. Contributed to profiler & benchmarking, and heterogeneous data transformation, as a member of the PyG team.
- Python Graph Outlier Detection (PyGOD): A Python Library for Graph Outlier Detection.
- Therapeutics Data Commons (TDC): Machine learning for drug discovery.
- combo: A Python Toolbox for ML Model Combination (Ensemble Learning).
- TODS: Time-series Outlier Detection. Contributed to core detection models.
- MetaOD: Automatic Unsupervised Outlier Model Selection (AutoML).
[#1] I host a WeChat group on anomaly detection (异常检测微信讨论组) & machine learning systems (MLSys讨论组), along with more than four hundred of researchers (e.g., Berkley, MIT, Tsinghua, etc.) and industry people (e.g., Alibaba, IBM, Meta, etc.) for collaboration and intern/full-time opportunities. Join it by scan 微信 @ 加群小助手!
[#2] I host a WeChat group for ML Ph.D. (北美ML博士求职分享群) where we share postdoc, intern, and full-time jobs for ML Ph.D. (students). Join it by scan 微信 @ 加群小助手!
[#3] I am a dedicated writer with more than 300 articles (in Chinese) and 170,000 followers on Zhihu (知乎) — Chinese Quora (200 million+ registered users). I have been officially recognized as a “Top Writer” (优秀回答者) in four fields (AI, ML, DM, and STAT). My articles have been read by more than 20,000,000 times. See my Zhihu page (微调).
Contact me by Email (zhaoy [AT] cmu.edu) or WeChat (微信) @ yzhao062.Interests
- Outlier Detection Systems (ODSys)
- Outlier & Anomaly Detection
- AI + Security
- Machine Learning Systems (MLSys)
- Automated Machine Learning
- Graph Neural Networks
- Ensemble Learning
- Scalable Machine Learning
- Healthcare AI & Therapeutic for ML
- Information Systems
Education
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Ph.D. Student in Information Systems, 2019-2023
Carnegie Mellon University
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M.S. in Applied Computing, 2015-2017
University of Toronto
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B.S. in Computer Engineering (Minor in Computer Science and Math), 2015
University of Cincinnati
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High School Diploma, 2010
Shanxi Experimental Secondary School 山西省实验中学
