Alwyn Mathew

Papers

Total Citations

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About

Alwyn Mathew is a researcher at the forefront of computer vision and robotics, with a primary focus on advancing medical imaging and autonomous systems. His work centers on monocular depth estimation—a critical technology that enables machines to perceive 3D structure from a single image, which is essential for navigation and scene understanding in robotics. Mathew’s most notable contributions lie in applying this technique to high-stakes medical contexts, particularly colonoscopy. His 2023 paper on self-supervised monocular depth estimation for high field-of-view colonoscopy cameras tackles the challenge of missed polyps during colorectal cancer screening—a procedure where up to 28% of polyps can go undetected. By enabling vision-based autonomous soft endorobots, his work aims to dramatically improve diagnostic accuracy and patient outcomes. Beyond medical applications, Mathew has also investigated the security of depth estimation systems, as shown in his 2020 study on vulnerabilities and attacks against monocular depth estimators. With each of his most-cited papers garnering 7 citations, Mathew’s research is gaining traction for its dual focus on robustness and real-world impact, positioning him as a rising voice in safe, deployable AI for critical healthcare and robotic tasks.