Ye Htet 🍄
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Ye Htet

Ph.D. Candidate

Washington University in St. Louis

htet.ye (at) wustl.edu

    CV

About Me

Hello! I am a 5th year PhD student in Computer Science in Washington University in St. Louis. I am a part of the Stream-Based Supercomputing Lab advised by Dr. Jeremy Buhler.

I am currently working on the streaming computational pipeline for the Advanced Particle Astrophysics Telescope (APT) and the Antarctic Demonstrator for the Advanced Particle Astrophysics Telescope ( ADAPT ) for Gamma-Ray Burst (GRB) localization.

Broadly, I am interested in working with algorithms and deep learning applications.

Research Interests

Generative AI, Large Language Models, Machine Learning Acceleration, Artificial Intelligence, Model Optimization, Pruning, Quantization, Simulation, High Performance Computing, Real-time Computing, Low-Power Design, Parallel Computing

Recent research

See all research
  • Paper Teaser
    Modeling and Optimizing Real-Time Telescope Interaction for Multi-wavelength Observation of Gamma-ray Bursts
    Ye Htet, Marion Sudvarg, Honghao Yang, Jeremy Buhler, Roger Chamberlain, and James Buckley
    Paper
    In
    WIUHPC (SC 2025)

    The 6th Combined Workshop on Interactive and Urgent High-Performance Computing (WIUHPC), November 2025. Held in conjunction with SC.

  • Paper Teaser
    Performance Modeling and Improvements on the GRB Source Localization Streaming Pipeline Aboard the Antarctic Demonstrator for the Advanced Particle-Astrophysics Telescope (ADAPT)
    Ye Htet, Marion Sudvarg, Honghao Yang, Jeremy Buhler, Roger D. Chamberlain, Wenlei Chen, James H. Buckley for the APT collaboration
    Paper
    In
    ICRC 2025

    In Proc. of 39th International Cosmic Ray Conference — PoS(ICRC2025), volume 501, pages 679:1--679:9, July 2025.

  • Paper Teaser
    Machine Learning Aboard the ADAPT Gamma-Ray Telescope
    Ye Htet, Marion Sudvarg, Andrew Butzel, Jeremy Buhler, Roger Chamberlain, and James Buckley
    Paper
    In
    AI4S (SC 2024)

    The 5th Workshop on Artificial Intelligence and Machine Learning for Scientific Applications (AI4S), November 2024. Held in conjunction with SC.

  • Paper Teaser: APT
    Localization of Gamma-ray Bursts in a Balloon-Borne Telescope
    Ye Htet, Marion Sudvarg, Jeremy Buhler, Roger Chamberlain, and James Buckley
    Paper
    In
    EPSOUQ (SC 2023)

    The First Workshop on Enabling Predictive Science with Optimization and Uncertainty Quantification in HPC (EPSOUQ), November 2023. Held in conjunction with SC.

  • Paper Teaser
    Prompt and Accurate GRB Source Localization Aboard the Advanced Particle Astrophysics Telescope (APT) and its Antarctic Demonstrator (ADAPT)
    Ye Htet, Marion Sudvarg, Jeremy Buhler, Roger D. Chamberlain, Wenlei Chen, James H. Buckley for the APT collaboration
    Paper
    In
    ICRC 2023

    In Proc. of 38th International Cosmic Ray Conference – PoS(ICRC2023), volume 444, pages 764:1–764:9, July 2023.

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