I am pursuing a Joint Ph.D. degree in Machine Learning & Public Policy at Carnegie Mellon University, advised by Prof. Leman Akoglu. Before coming to CMU, I have more than 5-year industry experience in software engineering and management consulting. See my professional experience.
Research Keywords: Outlier & Anomaly Detection; Ensemble Learning; Scalable Machine Learning
Longer version: my interests lie on the applied side of the learning algorithms. I especially care why, when, and how to use learning models to bring social impact. In addition to propose new ensemble learning, outlier detection, and clustering algorithms, I design and implement accessible and scalable machine learning systems and libraries as well. More importantly, I enjoy applying learning algorithms to solve real-world problems (e.g., healthcare, education, security, and finance), i.e., build applications and understand their implications.
I am always open to collaboration opportunities (anywhere on the earth) and applied research internships (United Stats (CPT), Canada (Residency), and China (Residency); I need visa sponsorship for other countries). I have been working with the researchers from both industry and academia (U of Toronto, UIUC, PwC etc.). Feel free to reach out by Email (zhaoy [AT] cmu.edu) or WeChat (微信).
If you want to meet in person for a coffee in Pittsburgh (it is on me), drop me a line ☕
Joint Ph.D. in Machine Learning & Public Policy (Expected); Ph.D. in Information System & Management (Primary), 2019-2024
Carnegie Mellon University
M.S. in Applied Computing, 2016
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