About

Didier Devaurs is a leading researcher at the intersection of robotics and structural biology, renowned for developing sampling-based motion planning algorithms that bridge these two fields. His most significant contribution is the Transition-based RRT (T-RRT), a groundbreaking algorithm for navigating complex cost spaces that has accumulated over 83 citations. Devaurs has extended this work through multi-tree approaches and low-dimensional projection techniques, enabling efficient exploration of high-dimensional conformational spaces in both robotic manipulation and biomolecular systems. His research has yielded practical tools like MoMA-LigPath, a web server for simulating protein-ligand unbinding (46 citations), and has advanced the characterization of peptide energy landscapes using stochastic algorithms. With over 290 total citations across his most-cited papers, Devaurs has demonstrated remarkable impact in applying robotics-inspired methods to molecular caging prediction, protein conformational sampling, and aerial manipulation with towed-cable systems. His work continues to influence both autonomous robotics and computational structural biology, making him a pivotal figure in the growing field of robotics-inspired computational biology.

Research Focus

Key Achievements

7
H-Index
11
Papers
294
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
Enhancing the transition-based RRT to deal with complex cost spaces
83 citations · 2013
📈 Most Prolific Year: 2013 (4 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: Laboratoire d'Analyse et d'Architecture des Systèmes, Centre National de la Recherche Scientifique, Rice University, Institut polytechnique de Grenoble

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago