Skip to content
View yzhao062's full-sized avatar
💜
Very Busy Since Joined USC
💜
Very Busy Since Joined USC

Highlights

  • Pro

Organizations

@pygod-team @Open-Source-ML

Block or report yzhao062

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
yzhao062/README.md

😄 I am an Assistant Professor at USC Computer Science; see the latest information at my homepage.

Prospective Students. We are seeking to recruit 2 Ph.D. students for Fall 2025. Applicants are required to have at least one paper published in a top ML, System, or LLM conference. We also have openings for undergraduate and graduate interns, both from USC and other institutions. For all positions, please complete this Google Form: Application Form. Additionally, Ph.D. candidates are required to email me directly after submitting the form. See details at my homepage.

🌱 Research Interests. My research is centered on the development of robust, efficient, and automated machine learning (ML) algorithms, systems, and applications. My key areas of focus include:

  1. Robust and Trustworthy AI: Enhancing AI systems with capabilities in out-of-distribution (OOD) detection, outlier detection (OD), and anomaly detection to improve reliability and trust.

  2. Efficient and Automated AI: Developing ML systems that operate with minimal human supervision, optimizing for performance and automation.

  3. AI for Applications and Science: Applying AI technologies to solve complex problems in fields such as drug discovery, security, finance, healthcare, and political science.

  4. Foundation Models and Generative AI for OD/OOD: Investigating the interplay between OD/OOD and advanced models like large language models (LLMs), enhancing both fields.

Open-source Contribution: I created PyOD (used by NASA, Tesla, Morgan Stanley, and more) - the most popular library for anomaly detection in 2017. Also, I have led more than 10 ML open-source initiatives, receiving 20,000 GitHub stars (top 0.002%) and >22M downloads. Popular ones: PyOD, PyGOD, TDC, ADBench

📫 Contact me by:


Pinned Loading

  1. pyod pyod Public

    A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

    Python 8.6k 1.4k

  2. anomaly-detection-resources anomaly-detection-resources Public

    Anomaly detection related books, papers, videos, and toolboxes

    Python 8.4k 1.8k

  3. WSAD WSAD Public

    A Collection of Resources for Weakly-supervised Anomaly Detection (WSAD)

    Python 160 11

  4. Minqi824/ADBench Minqi824/ADBench Public

    Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.

    Python 876 136

  5. pytod pytod Public

    TOD: GPU-accelerated Outlier Detection via Tensor Operations

    Python 177 24

  6. pygod-team/pygod pygod-team/pygod Public

    A Python Library for Graph Outlier Detection (Anomaly Detection)

    Python 1.3k 128