About Me

I am a Ph.D. candidate in the Data Science and Analytics Thrust at Hong Kong University of Science and Technology (Guangzhou), specializing in neural solvers for partial differential equations. I am supervised by Prof. Wei WANG and co-supervised by Prof. Zhilu LAI.

My current research interests include:

I am actively seeking research collaborations and industry internship opportunities. Please feel free to contact me at [email protected].

Education

2023 ~ Present: Ph.D. Student in Data Science and Analytics

2019 ~ 2023: B.Eng. in Mechatronics

(2026 - Now) We are building an open repository for parameterizing functionals in scientific machine learning within function spaces. If you are interested in participating, please contact me.
(2026 - Now) Recently, we have uploaded our work on epistemic uncertainty quantification for neural operators to arXiv, introducing a novel scheme that reframes weight-space epistemic uncertainty as noise perturbations confined to the lifting-weight subspace.

(2025 - 26) We have submitted our paper: Redefining Neural Operators in $d+1$ Dimensions for Embedding Evolution, which provides the first functional view on embedding-space evolution in neural operators.

(2024 - 25) We have published our paper: Harnessing scale and physics: A multi-graph neural operator framework for pdes on arbitrary geometries, which adaptively constructs multi-scale graphs to support information aggregation in a graph-former architecture.

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