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milad1378yz/README.md

Milad Yazdani

I am a PhD student in Electrical and Computer Engineering at the University of British Columbia (UBC). My research focuses on generative modeling, reinforcement learning, and AI-driven search and optimization, with applications in medical imaging, multi-agent systems, mathematical optimization, and computational design.

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  1. MOTFM MOTFM Public

    Flow Matching for Medical Image Synthesis: Bridging the Gap Between Speed and Quality

    Python 86 14

  2. EvoCut EvoCut Public

    EvoCut: Automatic generation of acceleration cuts for integer programs via evolutionary search and LLMs.

    Python 11 2

  3. MASPRM MASPRM Public

    Multi-Agent System Process Reward Model (MASPRM): a lightweight process reward model guiding multi-agent systems at search time.

    Python 3 2

  4. rrt rrt Public

    Reference implementation of Rubric Response Theory (RRT): IRT-based rubric rewards for RL, with learned criterion difficulty/discrimination, online calibration, and adaptive criterion selection.

    Python 3

  5. RL-Kirigami RL-Kirigami Public

    Inverse design and RL fine-tuning for reconfigurable kirigami shape generation and fabrication export.

    Python 1

  6. sage sage Public

    SAGE: Automatic discovery of symbolic acceleration inequality families for MILP via evolutionary search and LLMs.

    Python 1