Skip To Main Content
Dongxiao Yin on Muck Rack

Dongxiao Yin

As seen in: Nature, Wiley Online Library, Eyes on Earth, MDPI, Royal Society of Chemistry
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Dongxiao

Contact Dongxiao, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

An interactive enhanced driving dataset for autonomous driving

|
By Haojie Feng, Xinrui Zhang, Mengjie Tian, Peizhi Zhang, Zhuoren Li, Junpeng Huang, Xiurong Wang, Junfan Zhu, Jianzhou Wang, Dongxiao Yin, Lu Xiong
| Nature Verified
Abstract Driving interaction data are important for training and evaluating autonomous driving Vision-Language-Action (VLA) models, but existing datasets contain limited dense interaction samples and weak alignment between trajectories, visual inputs, and language annotations. This work presents the Interactive Enhanced Driving Dataset (IEDD), a large-scale interaction-oriented dataset constructed from five naturalistic trajectory datasets: Lyft Level 5, Waymo, nuPlan, INTERACTION, and SIND.
Open in Who Shared Issue with article?

Spatial heterogeneity of salt marsh vulnerability to sea-level rise: Dual controls of hydrological setting and salinity regime

|
By Dongxiao Yin
| Eyes on Earth
Links More information: Publisher Index Page (via DOI) Download citation as: RIS | Dublin Core Suggested Citation Yin, D., Defne, Z., Ganju, N., Warner, J., Ralston, D.K., Harris, C.K., and Li, B., 2026, Spatial heterogeneity of salt marsh vulnerability to sea-level rise: Dual controls of hydrological setting and salinity regime: Geophysical Research Letters, v. 53, no. 8, e2025GL119461, 12 p., https://doi.org/10.1029/2025GL119461.
Open in Who Shared View Duplicates (4) Issue with article?

5G communication delay dataset for cloud-based vehicle planning and control

|
By Xinrui Zhang, Lu Xiong, Peizhi Zhang, Haojie Feng, Junpeng Huang, Xiurong Wang, Mengjie Tian, Zhuoren Li, Dongxiao Yin
| Nature Verified
Abstract Cloud-based intelligent connected vehicles (CICVs) rely on vehicle-to-network-to-vehicle (V2N2V) communication for cooperative planning and control (PnC), where communication delay directly influences control performance and safety. To support research on delay modeling and delay-aware control, we present CICV5G, a publicly available dataset of 5G communication delay for cloud-based CICV applications.
Open in Who Shared Issue with article?
See all 8 articles