people

members of the lab or group


prof_pic.jpg

555 your office number

123 your address street

Your City, State 12345


layout: about title: About permalink: / subtitle:

profile: align: right image: bio.jpg image_circular: false # crops the image to make it circular more_info:

news: true # includes a list of news items selected_papers: true # includes a list of papers marked as “selected={true}” social: true # includes social icons at the bottom of the page —

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

If you are interested in collaborating or discussing research ideas, feel free to reach out via email.

I also co-organize the AI4Science community on alphaXiv. If you are interested in building the future of automated research, feel free to join us!


prof_pic.jpg

555 your office number

123 your address street

Your City, State 12345


layout: about title: About permalink: / subtitle:

profile: align: right image: bio.jpg image_circular: false # crops the image to make it circular more_info:

news: true # includes a list of news items selected_papers: true # includes a list of papers marked as “selected={true}” social: true # includes social icons at the bottom of the page —

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

If you are interested in collaborating or discussing research ideas, feel free to reach out via email.

I also co-organize the AI4Science community on alphaXiv. If you are interested in building the future of automated research, feel free to join us!