Papers
3
Total Citations
24
H-Index
3
About
David Parent is a researcher whose work bridges the fields of robotics and biomedical engineering, with a primary focus on advancing human-robot interaction and autonomous manipulation. His key research areas include variable impedance control, model predictive control, and the automation of laboratory processes. Parent’s major contributions lie in developing algorithms that allow robots to safely and compliantly interact with humans while performing complex tasks. For instance, his work on variable impedance control in Cartesian latent space enables robots to avoid obstacles in null space, a critical advancement for assistive robotics. His research on model predictive control for dynamic cloth manipulation—a notoriously difficult problem due to textiles’ unpredictable configurations—demonstrates his ability to tackle real-world challenges, achieving 9 citations since 2024. With a total of over 24 citations across his most-cited works, Parent’s impact is evident. Notably, his earlier work on automating monoclonal antibody panel preparation for immunophenotyping (2005, 5 citations) showcases his versatility, contributing to more efficient diagnosis of hematologic malignancies. This blend of robotics and biomedical innovation highlights Parent’s unique interdisciplinary approach, making his research valuable for students and engineers seeking to develop safer, more adaptive robotic systems.
Research Focus
Key Achievements
Top Papers
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