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pnxenopoulos/README.md

Hey there! πŸ‘‹

Peter Xenopoulos Website Peter Xenopoulos Twitter Peter Xenopoulos LinkedIn Peter Xenopoulos Google Scholar

I'm Peter Xenopoulos. I'm a research scientist at NVIDIA, focusing on developing machine learning and visual analytics solutions for esports & sports. Previously, I led quantitative research for a sports betting exchange, worked with a professional baseball team (Phillies), analyzed companies for a top seed-stage venture capital fund (Tuesday VC), created data and modeling pipelines for an athlete investment fund (Big League Advance), and worked on the AI data science team at Facebook. I maintain the following projects:

  • πŸ‘©β€πŸ’» awpy, a library to parse, analyze and visualize Counter-Strike demofiles. The project has spawned published papers in IEEE Big Data, ACM's WWW conference, and IJCAI.
  • πŸ’Ύ ESTA, a large esports dataset, which contains 8.6m player actions, 7.9m game frames and 417k player trajectories from 1.5k professional CSGO matches.
  • πŸ“ˆ PyCalibrate, a visual analytics tool to analyze model calibration. This work was accepted to IEEE VIS 2022.
  • πŸ’‘ GALE, a technique to measure the similarity between sets of local explanations developed in collaboration with Capital One. Accepted for a spotlight talk at the TAGML workshop at ICML 2022.

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  1. awpy awpy Public

    Python library to parse, analyze and visualize Counter-Strike 2 data

    Python 387 58

  2. implied implied Public

    implied is a Rust library to work with odds and sports betting

    Rust 1

  3. esta esta Public

    Esports Trajectories and Actions (ESTA) dataset

    25 2

  4. cav-keras cav-keras Public

    Concept activation vectors for Keras

    Python 13 6