2022 Summer Internship: Open to ML/AI research/system internship. Please reach out :)

My name is Yue ZHAO (赵越 in Chinese). I am a third-year Ph.D. student at Heinz College, Carnegie Mellon University (CMU)–the best interdisciplinary research institute in the world. Before joining CMU, I was a senior consultant at PwC Canada.

I have led or contributed as a core member to more than 10 ML open-source initiatives, receiving 11,000 GitHub stars (top 0.002%: ranked 900 out of 40M GitHub users) and >500,0000 total downloads. Popular ones:

  • [JMLR] PyOD: A Python Toolbox for Scalable Outlier Detection (Anomaly Detection).
  • [MLSys] SUOD: An Acceleration System for Large-scale Heterogeneous Outlier Detection.
  • [NeurIPS] MetaOD: Automatic Unsupervised Outlier Model Selection (AutoML).
  • PyG (PyTorch Geometric): Graph Neural Network Library for PyTorch. Contributed to profiler & benchmarking, and heterogeneous data transformation, as a member of the PyG team.
  • [NeurIPS] TDC: An extensive machine learning data hub for drug discovery.
  • [ICDM] COPOD: A fast and parameter-free outlier detection method.
  • [AAAI] combo: A Python Toolbox for ML Model Combination (Ensemble Learning).
  • [NeurIPS, AAAI] TODS: Time-series Outlier Detection. Contributed to core detection models.

I specialize in designing and building machine learning systems (MLSys), with realization and applications in outlier detection, healthcare, graph neural networks, and ensemble learning. My research focuses on the intersection of two fields:

  • machine learning systems that can speed/scale up and automate underlying algorithms
  • data mining algorithms like outlier detection (anomaly detection) and ensemble learning

At CMU, I work with Prof. Leman Akoglu from DATA Lab on outlier detection, Prof. Zhihao Jia from Catalyst on machine learning systems, and Prof. George H. Chen on general ML and statistics. Externally, I am also fortunate to visit and collaborate with Prof. Jure Leskovec at Stanford University.

Startup and VC: I am interested in capitalizing my expertise in machine learning systems and outlier detection. Let's connect!

Contact me by Email (zhaoy [AT] cmu.edu) or WeChat (微信) @ yzhao062.

[#1] Call for review oppt. I am looking for paper review, tutorial, workshop, and talk opportunities (in anomaly detection, scalable ML, machine learning systems, and AutoML).

[#2] 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 three hundred of researchers (e.g., Berkley, MIT, Tsinghua, etc.) and industry people (e.g., Alibaba, IBM, Facebook, etc.) for collaboration and intern/full-time opportunities. Ping me to join!

[#3] I am a dedicated writer with more than 300 articles (in Chinese) and 160,000 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).

Interests

  • Outlier & Anomaly Detection
  • Machine Learning Systems (MLSys)
  • Automated Machine Learning
  • Scalable Machine Learning
  • Parallel Computing
  • Healthcare AI & Therapeutic for ML
  • Graph Neural Networks
  • Ensemble Learning
  • Information Systems

Education

  • Ph.D. Student in Information Systems and Management, 2019-2023

    Carnegie Mellon University

  • M.S. in Applied Computing, 2015-2017

    University of Toronto

  • B.S. in Computer Engineering (Minor in Computer Science and Math), 2015

    University of Cincinnati

  • High School Diploma, 2010

    Shanxi Experimental Secondary School 山西省实验中学

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