Papers
8
Total Citations
60
H-Index
6
About
Jad Bassil is a robotics and artificial intelligence researcher whose work spans modular robotics, programmable matter, and deep learning-based computer vision. His most significant contributions lie in the design of distributed algorithms that enable large-scale modular robotic systems to self-organize, reconfigure, and recognize their own shapes autonomously. His landmark paper introducing RePoSt, a distributed self-reconfiguration algorithm leveraging porous 3D structures to enable parallel module flow, has garnered 14 citations and represents a meaningful advance in scalable robotic reconfiguration. Complementing this, his work on distributed clustering algorithms — both linear and size-constrained variants — addresses the fundamental challenge of coordinating millions of independent robotic modules efficiently, with each study accumulating up to 9 citations. Bassil has further contributed fault-tolerance mechanisms for self-reconfiguring systems and shape recognition algorithms for lattice-based robots, reinforcing the robustness and intelligence of programmable matter architectures. Beyond robotics, his foray into solar energy research, applying deep learning image classification to detect dust accumulation on solar panels, demonstrates a versatile research vision. Collectively, his body of work reflects a consistent dedication to distributed intelligence, autonomous systems, and real-world applications of cutting-edge computational methods.
Research Focus
Key Achievements
Top Papers
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- 6Distributed Shape Recognition Algorithm for Lattice-Based Modular Robots6 citations · 2023
- 7Fault- Tolerance Mechanism for Self-Reconfiguration of Modular Robots4 citations · 2022
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