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Achievements

Achievement: Pair Extraordinairex2Achievement: StarstruckAchievement: YOLOAchievement: Pull Sharkx2Achievement: Quickdraw

Achievements

Achievement: Pair Extraordinairex2Achievement: StarstruckAchievement: YOLOAchievement: Pull Sharkx2Achievement: Quickdraw

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pbonazzi/README.md

👋🏻 I’m a Ph.D researcher at ETH Zürich focused on low-latency, efficient machine learning systems—especially those deployable on constrained hardware like embedded platforms. Alongside my academic work, I consult as an AI engineer, helping organizations build practical and optimized ML pipelines based on LLMs. During my Master studies, I collaborated with Federico Tombari’s group at Google, working on differentiable rendering, graph-based transformers, and diffusion models. My broader research interests include real-time perception and efficient computing.

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  1. picosam2 picosam2 Public

    [IEEE SENSORS 2025] PicoSAM2 is a minimal, prompt-based segmentation model distilled from Meta’s SAM 2.1

    Jupyter Notebook 15 2

  2. ETH-PBL/MLonMCU ETH-PBL/MLonMCU Public

    [ETH Course] Exercise materials of the Machine Learning on Microntrollers course

    C 10 11

  3. eva eva Public

    [CVPR Workshop 2025] Event-based obstacle avoidance on FPGA AMD Xilinx DPU.

    Python 12 1

  4. ETH-PBL/TinyissimoYOLO ETH-PBL/TinyissimoYOLO Public

    Python 46 7

  5. retina retina Public

    [CVPR Workshop 2024] Retina is an eye tracking method suitable for deployment on a neuromorphic system on chip.

    Python 50 7

  6. tinytracker tinytracker Public

    [IEEE SENSORS 2023] TinyTracker is a highly efficient, fully quantized model for 2D gaze estimation.

    Python 21 2