Richard Cornelius Suwandi

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I am a PhD student at The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen). Prior to my PhD, I obtained my BSc degree in Statistics from CUHK-Shenzhen.

I am fortunate to be advised by Prof. Feng Yin and Prof. Tsung-Hui Chang. My current research focuses on:

  • Sequential decision-making with active learning and Bayesian optimization
  • Probabilistic machine learning, especially Gaussian processes
  • AI4Science, including experimental design and scientific discovery

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

News

Sep 10, 2024 My blog post on “Optimize Your Signal Processing with Bayesian Optimization” has been published on IEEE SPS
Sep 09, 2024 Invited to serve as a Reviewer for International Conference on Learning Representations (ICLR) 2025
Jul 17, 2024 Selected as the recipient of the 2024 Shenzhen Universiade International Scholarship Foundation (SUISF)
Aug 14, 2023 Joined Bayesian Learning for Signal Processing (BLSP) Group of CUHK-Shenzhen as a PhD student
May 04, 2022 Our paper titled “Gaussian Process Regression with Grid Spectral Mixture Kernel: Distributed Learning for Multidimensional Data” has been accepted to FUSION 2022

Selected Works

(* indicates equal contributions)

  1. fedmf.png
    Demystifying model averaging for communication-efficient federated matrix factorization
    Shuai Wang, Richard Cornelius Suwandi, and Tsung-Hui Chang
    In 46th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , 2021
  2. gsm.png
    Gaussian process regression with grid spectral mixture kernel: Distributed learning for multidimensional data
    Richard Cornelius Suwandi*, Zhidi Lin*, Yiyong Sun, and 3 more authors
    In 25th International Conference on Information Fusion (FUSION) , 2022