Mr. Siyu Wang | Multimodal Detection | Best Researcher Award
Innovative Researcher, Wuhan University of Science and Technology, China
Mr. Siyu Wang is an innovative researcher in control science, artificial intelligence and automation whose academic path and project experience demonstrate a rare combination of theoretical insight and applied problem-solving. Mr. Siyu Wang is currently pursuing a Master’s degree in Control Science and Engineering at Wuhan University of Science and Technology, focusing on machine vision, multimodal data fusion, deep learning, and 3D perception systems, after completing a rigorous undergraduate training that gave him a strong engineering foundation across software, hardware and algorithm domains. Professionally, Mr. Siyu Wang has led and contributed to projects such as a 3D Semantic Segmentation System Integrating Image and LiDAR Information, designing a novel fusion strategy to match image pixels with point cloud data for superior segmentation accuracy, as well as implementing end-to-end training pipelines and custom CUDA operators to accelerate model performance. His research interests encompass multimodal fusion, millimeter-wave radar, accelerated depth estimation and 3D object detection, and he has already demonstrated skill in predicting and diagnosing one-dimensional data, classifying and segmenting two-dimensional image data, and processing three-dimensional point cloud information to build robust intelligent models. Mr. Siyu Wang has earned recognition for his strong engineering background, covering the full cycle of model development, design, deployment and optimization, and for his contributions to the growing field of AI-driven control systems. His achievements indicate a promising trajectory toward leadership in artificial intelligence, intelligent automation and advanced perception research.
Profile: SCOPUS | ORCID
Featured Publications
Wang, S. (2024). MDFusion: A multistage dynamic fusion framework for multimodal 3D object detection with leveraging cross-modal feature complementarity. Expert Systems with Applications. 5 citations.
Wang, S. (2024). Multi-sensor data fusion strategies for improved 3D semantic segmentation in intelligent transportation systems. IEEE Transactions on Intelligent Transportation Systems. 3 citations.
Wang, S. (2025). Accelerated depth estimation using multimodal LiDAR-camera fusion for autonomous navigation. International Journal of Automation and Computing. 2 citations.
Wang, S. (2025). Transformer-based multimodal fusion for millimeter-wave radar and vision data in 3D object detection. Neural Computing and Applications. 1 citation.