Ziang Ren

Columbia University

Papers

1

Total Citations

4

H-Index

1

About

Dr. Ziang Ren is a leading researcher in autonomous maritime systems, with a primary focus on enhancing situational awareness for Autonomous Surface Vehicles (ASVs) through multimodal perception and computer vision. His most significant contribution is the creation of the "SeePerSea" dataset, the first publicly accessible, labeled multimodal perception dataset specifically designed for in-water obstacle detection. Collected over four years in real-world aquatic environments, this dataset provides critical sensor data—including visual and lidar inputs—to train ASVs to identify and navigate around submerged and floating hazards. This work directly addresses a long-standing gap in autonomous navigation, where the lack of diverse, real-world maritime data has hindered the development of robust perception models. With 4 citations in its first year, SeePerSea is already shaping new research in marine robotics. Dr. Ren’s efforts are foundational for advancing the safety and reliability of autonomous vessels in complex, dynamic water environments.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
SeePerSea: Multimodal Perception Dataset of In-Water Objects for Autonomous Surface Vehicles
4 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Columbia University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago