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@cuhkshenzhen

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richardcsuwandi/README.md

I am a PhD student at CUHK-Shenzhen, advised by Prof. Feng Yin and Prof. Tsung-Hui Chang. Prior to my PhD, I obtained my BSc degree in Statistics from CUHK-Shenzhen.

I am interested in building open-ended intelligent systems capable of continuous learning, efficient knowledge acquisition from limited data, and generalization across an evolving range of tasks. To this end, my research explores:

  • Bayesian optimization for sample-efficient, adaptive exploration in open-ended search spaces
  • Gaussian processes to enable principled decision-making and uncertainty quantification
  • Foundation models for open-ended algorithm discovery, creative problem solving, and generative design in science and engineering

During my free time, I also enjoy writing about the latest advancements in AI. If you are interested in collaborating or discussing research ideas, feel free to reach out via email.

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  1. awesome-bo awesome-bo Public

    A curated repository of awesome Bayesian optimization resources.

    7 2

  2. jennyzzt/awesome-open-ended jennyzzt/awesome-open-ended Public

    Awesome Open-ended AI

    323 33

  3. blsp-group/blsp-group.github.io blsp-group/blsp-group.github.io Public

    HTML

  4. linkedin-network-analysis linkedin-network-analysis Public

    Exploratory analysis and visualizations on my own LinkedIn data.

    Jupyter Notebook 11 1