news

📚 Our latest work on grid spectral mixture product (GSMP) kernel has been featured in the “Machine Learning: From the Classics to Deep Networks, Transformers and Diffusion Models” book!

🎉 Our paper titled “Sparsity-Aware Distributed Learning for Gaussian Processes with Linear Multiple Kernel” has been accepted to IEEE TNNLS!

🏆 Selected as the recipient of the IEEE Signal Processing Society Scholarship!

📝 My blog post on “Optimize Your Signal Processing with Bayesian Optimization” has been published on IEEE SPS!

✨ Invited to serve as a reviewer for ICLR 2025!

🏆 Selected as the recipient of the Shenzhen Universiade International Scholarship Foundation Program!

🎓 Joined Bayesian Learning for Signal Processing Group as PhD student!

🎉 Our paper titled “Gaussian Process Regression with Grid Spectral Mixture Kernel: Distributed Learning for Multidimensional Data” has been accepted to FUSION 2022!

🎉 Our paper titled “Demystifying Model Averaging for Communication-Efficient Federated Matrix Factorization” has been accepted to ICASSP 2021!