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Zeyi Ren

2 accepted papers

2026

DPNet: Doppler LiDAR Motion Planning for Highly-Dynamic Environments

RA-L 2026

Existing motion planning methods often struggle with rapid-motion obstacles due to an insufficient understanding of environmental changes. To address this, we propose integrating motion planners with Doppler LiDARs, which provide not only ranging measurements but also instantaneous point velocities.

Cited by 0SourcecodeScholar
2025

Nonparametric Teaching for Graph Property Learners

ICML 2025spotlight

Inferring properties of graph-structured data, *e.g.*, the solubility of molecules, essentially involves learning the implicit mapping from graphs to their properties. This learning process is often costly for graph property learners like Graph Convolutional Networks (GCNs). To address this, we prop…