Taikyeong Jeong

Hallym University, Myongji University, Seoul Women's University

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About

Taikyeong Jeong is a researcher at the forefront of medical robotics and intelligent sensing systems. His work primarily focuses on enhancing robotic-assisted surgery through computer vision, particularly addressing the critical challenge of smoke removal during laparoscopic procedures. Jeong’s most impactful contribution is the "DeSmoke-LAP" framework (2022, 36 citations), an innovative unpaired image-to-image translation method that significantly improves surgical visibility by removing smoke from laparoscopic videos without requiring paired training data. Beyond surgical applications, Jeong has made notable contributions to robotic perception and sensor networks. He developed methods for simultaneous calibration of hand-mounted laser-vision sensors (2011), enabling precise 3D measurement for robotic systems. His work on energy-efficient sensing algorithms for ubiquitous networks (2010) introduced novel circuit designs that reduce power consumption by intelligently managing sensor activity. Additionally, Jeong has explored intelligent algorithms for multi-mobile robot coordination (2015), focusing on autonomous navigation in dynamic, post-disaster environments. His research bridges the gap between theoretical sensing algorithms and practical robotic applications, with particular emphasis on improving safety and precision in medical robotics.