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How has Marjan Yaghoubi's publication output changed over time?
ScholarIQpublication output · 2021–2025
Output grew0% over the shown period — from 1 works in 2021 to 1 in 2025.
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2021202220232025
What are the most-cited papers on Marjan Yaghoubi?
ScholarIQmost cited works
Intelligent manufacturing execution systems: A systematic review
Ardeshir Shojaeinasab, Todd Charter, Masoud Jalayer, Maziyar Khadivi, Oluwaseyi Ogunfowora, Nirav Raiyani, Marjan Yaghoubi, Homayoun Najjaran
Journal of Manufacturing Systems. 2022160 Citations
A review of recent trend in motion planning of industrial robots
Mehran Ghafarian Tamizi, Marjan Yaghoubi, Homayoun Najjaran
S4210177954. 202381 Citations
Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions
Maziyar Khadivi, Todd Charter, Marjan Yaghoubi, Masoud Jalayer, Maryam Ahang, Ardeshir Shojaeinasab, Homayoun Najjaran
Computers & Industrial Engineering. 202541 Citations
A High-Fidelity Simulation Platform for Industrial Manufacturing by Incorporating Robotic Dynamics Into an Industrial Simulation Tool
Zengjie Zhang, Ram Dershan, Amir M. Soufi Enayati, Marjan Yaghoubi, Dean Richert, Homayoun Najjaran
IEEE Robotics and Automation Letters. 202221 Citations
Deep Reinforcement Learning for Machine Scheduling: Methodology, the State-of-The-Art, and Future Directions
Maziyar Khadivi, Todd Charter, Marjan Yaghoubi, Masoud Jalayer, Maryam Ahang, Ardeshir Shojaeinasab, Homayoun Najjaran
SSRN Electronic Journal. 202315 CitationsOPEN ACCESS
Related on ScholarIQ
University of Victoria
Institution
Intelligent manufacturing execution systems: A systematic review
Paper
A review of recent trend in motion planning of industrial robots
Paper
Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions
Paper
A High-Fidelity Simulation Platform for Industrial Manufacturing by Incorporating Robotic Dynamics Into an Industrial Simulation Tool
Paper
Deep Reinforcement Learning for Machine Scheduling: Methodology, the State-of-The-Art, and Future Directions
Paper