Miad Moarref

Sharif University of Technology, Concordia University

Papers

Total Citations

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About

Miad Moarref is a researcher whose work lies at the intersection of multi-agent robotic systems, distributed control, and optimization. His key contributions focus on developing scalable, asynchronous algorithms for coordinating networks of mobile agents. In his most cited work, "A Distributed Algorithm for Proportional Task Allocation in Networks of Mobile Agents" (56 citations), Moarref addressed the challenge of ensuring equal duty-to-capability ratios among robotic agents by fusing deployment and consensus problems—a foundational approach for fair task distribution in dynamic environments. He further advanced the field with "Facility Location Optimization via Multi-Agent Robotic Systems" (13 citations), where he introduced distributed algorithms for optimal facility placement, minimizing locational costs across demand points. Moarref also made notable strides in control theory with "Sensor allocation with guaranteed exponential stability for linear multi-rate sampled-data systems" (12 citations), tackling the complex problem of sensor assignment under incommensurate sampling rates while preserving system stability. His work bridges theoretical rigor with practical multi-agent coordination, offering tools that are both mathematically grounded and implementable. Moarref’s research continues to influence the design of autonomous systems, from robotic swarms to networked sensing, making him a valuable contributor to the fields of distributed robotics and control.