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About

Aran Mohammad is an emerging robotics researcher whose work centers on the intersection of human-robot collaboration (HRC) and parallel robot systems — a niche yet increasingly vital area of modern robotics. His research addresses one of the central challenges in deploying parallel robots alongside humans: ensuring physical safety without sacrificing the speed and performance advantages these systems offer over traditional serial robots. Mohammad's most cited work, "Towards Human-Robot Collaboration with Parallel Robots by Kinetostatic Analysis, Impedance Control and Contact Detection" (2023, 10 citations), laid a foundational framework for making parallel robots HRC-ready through kinetostatic analysis and impedance control strategies. Building on this, he has developed sophisticated methods for collision isolation and identification using proprioceptive sensing, and pioneered sensor fusion techniques combining joint and inertial measurement units to dramatically reduce contact detection delays — a critical factor in preventing injury. His consistent focus on clamping and collision reactions specific to parallel kinematic chains demonstrates a deep understanding of the unique safety risks these architectures present. With a growing body of work published primarily in 2023–2025, Mohammad is establishing himself as a focused contributor to safe robotics, with cumulative citations reflecting strong early-career impact within the specialized HRC community.