Miscellaneous

News & Travel

Dec 2019: Our paper “SynC: A Unified Framework for Generating Synthetic Population with Gaussian Copula” is accepted at AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI). See you in New York!

Dec 2019: Have a preliminary paper on accelerating the training & prediction with a large number of unsupervised anomaly detectors: “SUOD: Toward Scalable Unsupervised Outlier Detection”. More in-depth theoretical justification and an accompanied scalable python toolkit SUOD will be released for KDD 2020 (ADS track).

Dec 2019: PyOD has been downloaded by more than 350,000 times!

Nov 2019: Received more than 5,000 ⭐ on GitHub.

Oct 2019: Our demo paper “Combining Machine Learning Models and Scores Using combo library” on ML library combo is accepted at AAAI 2020. See you in New York! Check out our Demo Video!

Fun Facts

[#1] I am an active software developer with more than 5,000 GitHub stars in total (top 1,200 among 37,000,000 GitHub developers ranked by Gitstar Ranking). I led multiple popular open-source ML initiatives, including PyOD (total downloads > 350,000 times), combo, anomaly-detection-resources, and awesome-ensemble-learning.

[#2] I am a dedicated technical writer with more than 200 articles (in Chinese) and 90,000 followers on Zhihu (知乎) — Chinese Quora (200 million+ registered users). Since 2018, I have been officially recognized as a “Top Zhihu Writer” (优秀回答者) in four fields (AI, ML, DM, and STAT). My articles have been read by more than 8,000,000 times with 95,000 upvotes (statistics provided by Zhihu). See my Zhihu page.

Profile Pictures

High-resolution profile pictures can be downloaded here: Professional, Casual.

Publications

I am open to peer review and organizing chances (all types of venues) in the field of outlier & anomaly detection, ensemble Learning, clustering, ML libraries & systems, and information systems. Please send me an email (zhaoy@cmu.edu) or a request in the corresponding reviewing/organizing system.

Journal Reviewer

Working Papers

[w20a] DNA: Differentiating Noise from Anomaly

[w20b] Outlier Detection via Semi-supervised Generative Models

Under Review

[w19e] Yue Zhao, Xueying Ding, Jianing Yang, and Haoping Bai. SUOD: Toward Scalable Unsupervised Outlier Detection. AAAI Conference on Artificial Intelligence Workshop, 2020. Submitted, under review. Under R&R for KDD 2020 ADS track. [PDF] [Code] [Slides]

[w19c] Yiqun Mei (UIUC), Yue Zhao. A New Image Super-Resolution Method (Name masked due to the double-blind policy). Submitted to a major CV conference, under review.

Quickly discover relevant content by filtering publications.

Peer-reviewed Papers

(2019). SynC: A Unified Framework for Generating Synthetic Population with Gaussian Copula. AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI), Accepted, to appear.

PDF Code PPAI Arxiv

(2019). Combining Machine Learning Models Using combo Library. AAAI Conference on Artificial Intelligence (AAAI), demo track. Accepted, to appear.

PDF Code Video

(2019). PyOD: A Python Toolbox for Scalable Outlier Detection. Journal of Machine Learning Research (JMLR).

PDF Code Project JMLR abs Arxiv

(2019). Music Artist Classification with Convolutional Recurrent Neural Networks. International Joint Conference on Neural Networks (IJCNN).

PDF Code IEEE Xplore

(2019). Locally Selective Combination in Parallel Outlier Ensembles. SIAM International Conference on Data Mining (SDM).

PDF Code Slides DOI SIAM epubs

(2018). XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning. International Joint Conference on Neural Networks (IJCNN).

PDF Code DOI IEEE Xplore

(2018). DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Workshop on Outlier Detection De-constructed (ODD).

PDF Poster Slides

(2018). Employee Turnover Prediction with Machine Learning: A Reliable Approach. SAI Intelligent Systems Conference (Intellisys).

PDF DOI SpringerLink

(2017). An empirical study of touch-based authentication methods on smartwatches. Proceedings of the 2017 ACM International Symposium on Wearable Computers (Equal contribution).

PDF DOI ACM DL

Software

I will be happy to give talks on the series of tools I built, e.g., PyOD and combo. I am also happy to discuss the experience as a ML developer and researcher and how to build ML tools from design. Please drop me a line for invite :)

I am an enthusiastic open-source developer: I build machine learning libraries and systems. Specifically, I initialized Python Outlier Detection library (PyOD) in 2018, which has become the most popular Python outlier detection toolkit. I also initialized combo: A Python Toolbox for Machine Learning Model Combination in July 2019–it is currently under active development. Watch/Star/Follow welcome!

A Python Toolbox for Machine Learning Model Combination.
Code Doc Examples

PyOD–A Python Toolbox for Scalable Outlier Detection (Anomaly Detection).
PDF Code Doc

Experience

Professional Positions

 
 
 
 
 

Senior Consultant

PwC Canada, Consulting & Deals

Feb 2017 – Jun 2019 Toronto, ON, Canada
I was a senior consultant with the following duties:

  • Designed fraud analytic solutions for major Canadian banks and insurance firms.
  • Led applied data analytics projects, e.g., client segmentation and churn analysis.
  • Developed multiple pricing optimization models with statistical methods.
 
 
 
 
 

Research Associate (Intern)

PwC Canada, Consulting & Deals

May 2016 – Dec 2016 Toronto, ON, Canada

Applied research in people analytics with machine learning.

Supervised by Prof. Anthony Bonner and the project is partly supported by Mitacs-Accelerate Research and Development Funding (IT07884).

 
 
 
 
 

Software Engineer (Intern & Contract)

Siemens PLM Software USA

Mar 2012 – Dec 2014 Cincinnati, Ohio, USA
As a co-op student and contractor, my works include:

  • Managed a Java project to transition the LabManager system to vCloud Director.
  • Refactored outdated automation code and added new modules and JUnit test cases.
  • Led a C++ Code Coverage project on Teamcenter platform to strengthen its stability.

Experience

Teaching Positions

 
 
 
 
 

Teaching Assistant

University of Toronto, Department of Computer Science

Sep 2015 – Dec 2015 Toronto, ON, Canada
I was a teaching assistant for Embedded Systems taught by Prof. Philip Anderson.
 
 
 
 
 

Teaching Assistant

University of Cincinnati, Department of Electrical Engineering & Computer Science

Sep 2014 – Dec 2014 Cincinnati, OH, USA
I was a teaching assistant for Introduction to Programming taught by Prof. George Purdy.

Funds and Awards

CMU GSA/Provost Conference Funding

Carnegie Mellon University Nov 2019
Part of the travel grant for attending AAAI 2020.

Mitacs-Accelerate Research and Development Funding

Mitacs & University of Toronto May 2016 – Dec 2016
Project IT07884 ($30,000): machine learning in HR analytics.

Mantei/Mae Award & Scholar

University of Cincinnati Sep 2012 – May 2015
Awarded to highest-performing students in Electrical Engineering, Computer Engineering, and Computer Science ($40,000 in four years).

University Global Award and Scholarship

University of Cincinnati Sep 2010 – May 2015
Awarded to top performing international students ($32,000 in four years).

Contact

  • zhaoy@cmu.edu
  • Hamburgh Hall 2005, 4800 Forbes Ave, Pittsburgh, PA, USA, 15213
  • Thursday 15:00 to 18:00
    Friday 15:00 to 18:00
    or by appointment