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About

Selim Engin is a researcher whose work bridges the frontiers of robotics, computer vision, and multi-agent systems. His primary research areas include 3D scene reconstruction, multi-robot coordination, and active perception. Engin’s most notable contribution is the "RIC: Rotate-Inpaint-Complete" framework, a novel method for generalizable scene reconstruction from a single view—a critical challenge for AR/VR and autonomous navigation. This work, already garnering 4 citations shortly after its 2024 release, demonstrates his ability to tackle complex, real-world problems. In robotics, Engin has made significant strides in decentralized systems, such as his 2019 study on asynchronous network formation for mobile robots in unknown environments, which addresses fundamental challenges in information propagation for multi-robot teams. His work on active localization of multiple targets using noisy relative measurements (2020-2021) further showcases his expertise in optimal robot motion planning for uncertainty reduction. With a research portfolio that combines theoretical rigor with practical applications, Engin is establishing himself as a rising voice in autonomous systems and embodied intelligence.