Papers
7
Total Citations
32
H-Index
3
About
Siqin Dong is a robotics and biomedical engineering researcher whose work bridges autonomous systems, advanced manufacturing, and surgical robotics. Based at Old Dominion University's Collaborative Robotics and Adaptive Machines Laboratory, Dong has made notable contributions across three intersecting domains: medical image segmentation for surgical planning, human-robot collaboration in precision manufacturing, and the design of specialized surgical instruments. Dong's most-cited work (14 citations) introduced an nnU-Net-based multi-modality breast MRI segmentation architecture paired with a tissue-delineating phantom, laying critical groundwork for robotic tumor surgery planning. This research exemplifies her commitment to translating deep learning advances into clinically meaningful tools. Complementing this, her earlier work on force-controlled adaptive feedrate strategies for micro-drilling tasks (6 citations) demonstrated how human-robot collaborative frameworks can tackle the unpredictability of real-world manufacturing environments. Her innovative RoboCatch device further highlights her versatility — a hand-held robot designed to enable spillage-free specimen retrieval during laparoscopic surgery. More recently, Dong has expanded into composite materials research, examining fiber tow deformation in automated fiber placement. Collectively, her portfolio reflects a researcher dedicated to making autonomous systems smarter, safer, and more responsive across both industrial and healthcare applications.
Research Focus
Key Achievements
Top Papers
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