Selin Sevim
Papers
1
Total Citations
2
H-Index
1
About
Selin Sevim is a pioneering researcher at the intersection of robotics, artificial intelligence, and sustainable construction, with a primary focus on human-guided robotic training for timber assembly tasks. Her most-cited work, "Deep Agency: Towards human guided robotic training for assembly tasks in timber construction" (2024), introduces a novel framework that empowers robots to learn complex assembly processes through intuitive human demonstration, bridging the gap between manual craftsmanship and automated precision. This contribution addresses critical challenges in timber construction—such as material variability and joint complexity—by enabling adaptive, real-time collaboration between human workers and robotic systems. With 2 citations in its early publication stage, the paper signals growing interest in her approach to "deep agency," where robots not only execute tasks but also understand human intent and environmental context. Sevim’s work is notable for its practical implications in reducing waste and labor costs in the construction industry, while advancing human-robot interaction methodologies. As a researcher, she stands at the forefront of a movement to make timber construction more efficient, sustainable, and scalable, offering a compelling vision for the future of automated building practices.
Research Focus
Key Achievements
Top Papers
- 1