Kelvin Wong

University of Toronto, Cornell University, Houston Methodist

Papers

Total Citations

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About

Kelvin Wong is a versatile researcher whose work spans biomedical imaging, medical robotics, and autonomous perception systems. His contributions reflect a rare breadth across engineering disciplines, bridging advanced optical technologies with cutting-edge artificial intelligence. In the domain of intraoperative imaging, Wong developed a portable multimodal nonlinear endo-microscopy probe capable of high-resolution, label-free tissue visualization during oncological surgery. By incorporating a four-wave mixing noise suppression scheme with dual wavelength wave plates, his design significantly improved tissue signal collection efficiency — a meaningful step toward real-time, dye-free surgical guidance, earning 25 citations. Wong has also made notable strides in medical robotics, producing topology-aware geometric deep learning methods for automated catheter segmentation and tip detection in cerebral angiography. This work directly addresses a critical gap in endovascular robot perception, enabling potential AI augmentation in neurointervention procedures, accumulating 19 citations since 2023. Beyond medicine, Wong contributed to autonomous driving perception by tackling the challenge of identifying unknown object instances — a fundamental limitation in real-world deployment of deep learning systems — cited 16 times. Together, his work demonstrates a consistent commitment to solving high-stakes, real-world perception challenges across diverse fields.