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Gave a talk at the Qwen3.8 Show and Tell event about Sift, a private local AI copilot for searching, understanding, and organizing your files.

Invited to serve as a reviewer for ICLR 2027

Joined Qwen as a dev ambassador

Co-organized AIDDA 2026, a two-day virtual technical conference focusing on AI-driven algorithm discovery. Recordings of the talks are available on our YouTube channel

Our paper titled “MIMOMamba: From Scalar Duality to Matrix-Valued Attention” has been accepted to ICML 2026

Successfully passed my PhD candidate exam

Joined ByteDance’s Creation & Music Recommendation Team as a Research Intern to work on generative recommendation, LLM4Rec, and AIGC-powered content discovery

Invited to serve as a reviewer for NeurIPS 2026

Our paper titled “Breaking the Curse of Dimensionality in Gaussian Process Training With Zeroth-Order Adaptive Perturbation” has been accepted to ICASSP 2026 as oral

Transferred to the School of Artificial Intelligence, CUHK-Shenzhen with a fully-funded PhD scholarship

Selected as the recipient of the Guangdong Government Outstanding International Student Scholarship

Gave a talk on “Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMs” at the 2025 Greater Bay Area Graduate Research Forum in Shenzhen, China

Invited to serve as a reviewer for ICASSP 2026

Invited to serve as a reviewer for ICLR 2026

Our paper titled “Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMs” has been accepted to NeurIPS 2025

Joined Dria as a Research Intern to work on evolutionary coding agents

Won the 2nd prize award at the 2025 Doctoral Research and AI Innovation Conference held by CUHK-Shenzhen

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

Joined Huawei as a Research Intern to work on 5G network optimization

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

Received research funding from the Shenzhen Universiade International Scholarship Foundation

Joined Bayesian Learning for Signal Processing Group as a 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