I am currently pursuing a Joint Ph.D. degree in Machine Learning & Public Policy (TBC) at Carnegie Mellon University (CMU). I am advised by Prof. Leman Akoglu and Prof. Amelia Haviland. My interest span data mining algorithms, systems, applications, and real-world implications. After I joined the Heinz College, Information systems, especially how machine learning impacts on our daily life, arises as my new interest.
Specifically, I focus on proposing ensemble learning, outlier detection, and clustering algorithms. Additionally, I design and implement scalable machine learning systems and libraries for accessibility and efficiency. Last but not least, I am excited about apply learning algorithms to to real-world problems (such as healthcare, security, and finance), i.e., building applications and understanding their implications.
To sum up, my interests lie on the applied side of the learning algorithms. I especially care why, when, and how to use learning models to change our (both yours and mine) daily life. Although algorithms are beautiful, they could be prettier if tailored to solve real-world problems.
If you would like to meet for a coffee (it is on me), just drop me a line. I know several excellent coffee shops in Pittsburgh that you would not want to miss :)
Ph.D. in Information System & Management (Primary); Joint Ph.D. in Machine Learning & Public Policy (Expected), 2019-2024
Carnegie Mellon University
M.S. in Applied Computing, 2016
University of Toronto
B.S. in Computer Engineering, 2015
University of Cincinnati
High School Diploma, 2010
Shanxi Experimental Secondary School (山西省实验中学)
July 2019: I initialized a new Python toolbox, combo, for the easy use of combination methods in machine learning.
I am an active software developer with more than 4,200 GitHub stars in total (top 1,400 among 37,000,000 GitHub developers ranked by Gitstar Ranking). I led multiple popular open-source machine learning initiatives, including PyOD (total downloads > 120,000 times), combo, anomaly-detection-resources, and awesome-ensemble-learning. Before coming to CMU, I have more than 5-year industry experience as a software engineer and management consultant. See my professional experience for more information.
I am a dedicated technical writer with more than 200 articles (in Chinese) and 80,000 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). See my Zhihu page.
If needed, high-resolution profile pictures can be downloaded here:
I am open to peer review chances in the field of outlier & anomaly detection, ensemble Learning, clustering, and ML systems. Please send me an email (firstname.lastname@example.org) or a request in the corresponding reviewing system.
[w18a] DivBoost: Constructing Effective Outlier Ensembles by Base Learner Diversity Maximization
[w19a] HD-Cluster: Synthesized Cluster Analysis and Outlier Detection on High-dimensional Data
[w19c] Colin Wan, Zheng Li, Alicia Guo, Yue Zhao. [A new statistical model. *Name masked due to double blind review policy]. AAAI Conference on Artificial Intelligence (AAAI), 2020. Submitted, under review.
[w19d] Yue Zhao, Xuejian Wang*, Cheng Cheng*, Xueying Ding* [Combining Machine Learning Models and Scores using combo library] AAAI Conference on Artificial Intelligence (AAAI), demo track, 2020. Submitted, under review. (*equal contribution).
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!
Applied research in people analytics: build machine learning models for various people analytic projects.
Supervised by Prof. Anthony Bonner and the project is partly supported by Mitacs-Accelerate Research and Development Funding (IT07884).