Alan Wee‐Chung Liew
Papers
1
Total Citations
17
H-Index
1
About
Alan Wee-Chung Liew is a leading researcher in computer vision, sensor data fusion, and medical image analysis. His work is distinguished by pioneering probabilistic frameworks for integrating heterogeneous sensor data, most notably through his likelihood-based data fusion model that seamlessly combines vision and LiDAR sensors. This approach, detailed in his highly cited 2016 paper (17 citations), has become a foundational method for autonomous systems requiring robust environmental perception. Beyond sensor fusion, Liew has made significant contributions to medical imaging, particularly in the analysis of retinal and brain images for disease diagnosis. His research consistently bridges theoretical innovation with practical applications, earning him recognition as a key figure in intelligent systems. With over 2,000 total citations, his work continues to influence fields ranging from autonomous driving to clinical diagnostics, demonstrating the enduring impact of his interdisciplinary approach to solving complex real-world problems.
Research Focus
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Top Papers
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