Undergraduate Student
Xingjian College (Mechanical Engineering)
Tsinghua University
My research interests center on AI for inverse problems and sparse reconstruction, numerical simulation, and multiphysics. I am also interested in embodied intelligence and robotics.
I continue to collaborate with the CAB Lab at Princeton University following my exchange there in spring 2026.
I welcome research opportunities for summer 2027 and plan to apply to PhD programs for Fall 2028. Let's connect.
Preprint Submitted to NeurIPS 2026
NeTMY combines neural fields with differentiable physics for sparse reconstruction, revealing how forward-model fidelity and neural parameterization shape inverse optimization.
Technical Presentation Extended abstract
ASME IDETC-CIE 2026
Houston, TX, USA –
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Advisor: Prof. Christine Allen-Blanchette Mentor: Tao Zhong
I led NeTMY's physical modeling and neural-field design (Feb–Jul 2026), investigating how forward-model fidelity changes reconstruction behavior and why neural parameterization mitigates center collapse. Our ongoing collaboration explores equivariant models for learning physical structure in acoustics and weather modeling.
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Advisor: Prof. Xianghua Xu (徐向华)
I developed a CNN surrogate to infer cell-wise correction coefficients from temperatures on two opposing surfaces, addressing non-orthogonal mesh errors in finite-volume heat-transfer simulations. I led the implementation, including ANSYS mesh parsing, and benchmarked the model against least-squares-based methods on simple 3D geometries.
Xingjian College (Mechanical Engineering)
Undergraduate Student
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Department of Mechanical and Aerospace Engineering (MAE)
Exchange Student
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