My research interests include Multimodal Sensor Fusion, Unmanned Surface Vehicles and Intelligent Transportation Systems.

🔥 News

  • 2025.06:  🎉🎉 A USV-based object tracking dataset in inland waterways is accepted by IROS.
  • 2025.03:  🎉 A survey for Radar Data Representations is accepted by TITS.
  • 2024.06:  🌟 A 4D Radar-Camera Fusion Dataset is accepted by TITS.
  • 2024.09:   Radar-Camera Fusion is a Highly Cited Paper 🏆 by WOS.
  • 2023.08:   A survey for Radar-Camera Fusion is accepted by TIV.

📝 Publications

IEEE TITS

WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmarks for Autonomous Driving on Water Surfaces

Shanliang Yao, Runwei Guan, Zhaodong Wu, Yi Ni, Ryan Wen Liu, Yong Yue, Xiaohui Zhu, Yutao Yue, etc.

[Website]

  • The first multi-task 4D radar-camera fusion dataset on water surfaces, which offers data from multiple sensors, including a 4D radar, monocular camera, GPS, and IMU.
  • It can be applied in multiple tasks, such as object detection, instance segmentation, semantic segmentation, free-space segmentation, and waterline segmentation.
IROS

USVTrack: USV-Based 4D Radar-Camera Tracking Dataset for Autonomous Driving in Inland Waterways

Shanliang Yao, Runwei Guan, Yi Ni, Yong Yue, Xiaohui Zhu, Ryan Wen Liu.

[Website]

  • The first USV-based 4D radar-camera tracking dataset for autonomous driving in waterborne transportation systems, providing comprehensive data from four sensors: a 4D radar, a monocular optical camera, a GPS and an IMU.
  • USVTrack contains a rich diversity of data samples, including various waterways (wide and narrow rivers, lakes, canals, moats and docks), diverse time conditions (daytime, nightfall, night), weather conditions (sunny, overcast, rainy, snowy), and lighting conditions (normal, dim, strong).
IEEE TITS

Exploring Radar Data Representations in Autonomous Driving: A Comprehensive Review

Shanliang Yao, Runwei Guan, Yong Yue, Xiaohui Zhu, Yutao Yue, etc.

[Website] Github

  • We offer an up-to-date (2019-2024) overview of radar-based datasets and algorithms, providing in-depth research on their advantages and limitations.
  • We analyze the significant challenges and open questions related to these data representations, and propose potential research directions for further investigation.
IEEE TIV

Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review

Shanliang Yao, Runwei Guan, Yong Yue, Xiaohui Zhu, Yutao Yue, etc.

[website] Github

  • We present an up-to-date (2019–2023) overview of radar-camera fusion datasets and algorithms, and conduct in-depth research on “why to fuse”, “what to fuse”, “where to fuse”, “when to fuse”, and “how to fuse”.
  • We analyze the critical challenges and open questions in radar-camera fusion, and put forward potential research directions.

🎖 Honors and Awards

  • Project Management Professional (PMI-PMP), International Project Management Institute
  • Information System Project Manager, Ministry of Industry and Information Technology

  • 2022 The 8th ‘Internet+’ Student Innovation and Entrepreneurship Competition, Bronze Award in National Finals
  • 2022 The 12th ‘Challenge Cup’ National College Student Business Plan Competition, Bronze Award in Jiangsu Provincial Competition
  • 2020 The 6th ‘Internet+’ Student Innovation and Entrepreneurship Competition, Second Prize in Jiangsu Provincial Competition

📖 Educations

  • 2021.09 - 2024.11, Ph.D. in Computer Science and Software Engineering, University of Liverpool.
  • 2019.09 - 2021.04, M.S. in Applied Informatics, University of Liverpool.
  • 2012.08 - 2016.06, B.E. in Software Engineering, Soochow University.

💻 Services

  • Reviewer of TITS, TIV, TCSVT, TMC, RAL, ICRA, IROS, PR, etc.