Peiyuan Liao
廖培元

Boogiepop

Researcher, Programmer, Ponderer


When in doubt, Unsafe.Coerce

I help organize an academic conference/retreat in Beijing.

I also write code for a Pittsburgh-Chicago-based startup on real-time capture solutions for virtual personalities and youtubers/livers/“UP主” (uploaders).

While at school, I focused/am focusing on topics that live in the intersection of machine learning, systems engineering and programming language theory. 2 I've had the honor of working with Han Zhao and Keyulu Xu on graph neural networks in the past.

2. For a complete list of published works and preprints, please refer to papers.bib.

Research Interests

  • Graph Neural Networks: performance, application and interpretability
  • Representation Learning
  • Machine Learning/Deep Learning Systems: Training and Inference DSLs, Compilers and Optimizers
  • Federated Learning
  • Distributed Systems
  • Object Detection and Segmentation under performance-sensitive settings (low-power, low-memory, etc.)
  • Disentangled Machine Learning/Meta Learning/Interpretable Machine Learning
  • Formal Verification of Machine Learning Algorithms
  • Automated Abstraction and Reasoning of Programs
  • Currently

    I'm mainly participating in Recurse Center's Summer I batch (2020), where I will work several open source projects, including mmdetection, TVM, Taichi and PyTorch Geometric.

    I am also working at Cambricon Technologies as an intern, where I seek to enhance core features of their MLU enviornment and the BANG programming language.

    Coursework (Expected)

  • 15-295 Competitive Programming
  • 10-315 Introduction to Machine Learning
  • 15-459 Quantum Computation
  • 15-418 Parallel Architecture and Programming
  • 15-819 Foundation of Quantitative Program Analysis (graduate)
  • Portfolio

    I'm involved in several online, computer science-related communities, including Kaggle and Codewars (real-time ranking below). My resume can be found here.

    Codewars Profile


    Research
    graph neural networks, lossy compression

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    graph neural networks, lossy compression
    Projects
    functional programming, deep learning DSL, data science

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    functional programming, deep learning DSL, data science
    Academics
    classes, majors, courses

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    classes, majors, courses
    Professional
    LunTan, Recurse Center, Cambricon Technologies

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    LunTan, Recurse Center, Cambricon Technologies
    Skills
    programming languages, natural languages, technologies

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    programming languages, natural languages, technologies
    Honors
    prizes and recognitions

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    prizes and recognitions

    Miscellaneous

    Personal Interests

  • (hate to say it, but) towards General Artificial Intelligence
  • Automated Theorem Proving
  • Coldplay
  • Analytic Philosophy & its application in computer science
  • Automata Theory
  • Gen Hoshino
  • Sakanaction
  • French/Japanese
  • Film Photography

  • Prague
  • Virtual YouTubers *
  • Squash
  • *. 小孩子干什么不好非得看管人

    Contact

    Regarding my researches, academic collaboration, Kaggle team-up, or questions related to TVM/zeta/ml-arsenal:

    peiyuanl [at] andrew [dot] cmu [dot] edu

    For LunTan-related subjects, such as application, collaboration, sponsorship, etc:

    peiyuanl [at] luntan [dot] io

    Finally, anything else, like just making friends or talk about programming languages, machine learning (for fun), or what's it's like to be at recurse center:

    alexander [underscore] liao [at] outlook [dot] com

    Most of the code I've written can be found under my GitHub account: @liaopeiyuan.

    Institutional Address

    Peiyuan Liao
    5032 Forbes Avenue
    SMC 4401
    Pittsburgh, PA 15289

    ORCID iD iconhttps://orcid.org/0000-0002-4387-7940

    tr5 Homepage

    Want to become a better programmer? Join the Recurse Center!