My name is Yue ZHAO (赵越 in Chinese). I am a Ph.D. student at Carnegie Mellon University (CMU), a machine learning (ML) evangelist, and an ex management consultant at PwC Canada. As a seasoned ML software/system architect, I have led/participated > 10 ML libraries initiatives, 8,500 GitHub stars (top 0.002%: ranked 830 out of 40M GitHub users), and >300,0000 total downloads. Popular ones:

  • [JMLR] PyOD: A Python Toolbox for Scalable Outlier Detection (Anomaly Detection).
  • TDC: An extensive machine learning data hub for therapeutic tasks (ML for Therapeutic).
  • MetaOD: Automating Outlier Detection via Meta-Learning (Anomaly Detection).
  • PyHealth: A Python Library for Healthcare AI (ML for Healthcare).
  • [AAAI] combo: A Python Toolbox for ML Model Combination (Ensemble Learning).
  • [AAAI] TODS: Time-series Outlier Detection System. Contributed to core detection model.
  • SUOD: An Acceleration System for Large-scale Outlier Detection (Anomaly Detection).
  • meta-blocks: A modular toolbox for meta-learning research (Meta-Learning).

My research focuses on two streams:

  • data mining topics related to scalability, reliability, and automation and
  • information systems problems related to interaction, trade-off, and cooperation between human and “AI”

Good news: I am looking for 2021 Summer ML/DM Internship in Canada, United States, or China. Not necessarily pure research; system or AutoML related stuff would be great. Just reach out and let's figure something out :)

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

[#1] I am open to collaboration opportunities (anytime & anywhere) and research internships (open for Summer 2021). I could legally work in United States (CPT), Canada (permanent residency), and China (permanent residency). I have been working with the professionals from both industry and academia (U Toronto, Havard, UIUC, Texas A&M University, Tsinghua, Purdue University, National Chiao Tung University, Northeastern U, University of Virginia, PolyU, IQVIA, Adobe, PwC, Arima, etc.).

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

[#3] I host a WeChat group on anomaly detection (异常检测微信讨论组), 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!

Word Cloud from Paper Titles

Interests

  • Outlier & Anomaly Detection
  • Automated Machine Learning
  • Scalable Machine Learning
  • Machine Learning Systems
  • Healthcare AI & Therapeutic for ML
  • Ensemble Learning
  • Clustering
  • Active Learning
  • Information Systems

Education

  • Ph.D. in Data Mining and Information Systems (expected), 2019-2024

    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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