Thesis/Dissertation Defenses
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CIE Dept. invites all faculty, researchers, and students to MS Thesis Defense on "Multi-Objective Plant-Wide Optimization and Control of the Tennessee Eastman Process: From Mechanistic EMPC to Surrogate-Assisted Data-Driven Real-Time Optimization" by Mr. Fawaz Babajide Aremu, a Graduate Student of CIE Dept
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CIE Dept invites all faculty, researchers, and students to MS Thesis Defense on "Robust Attitude Control of a 3-DOF Quadcopter: Theory and Experiments" by Mr. Ahmed AbdulRazeq, a Full-time Graduate Student of CIE Dept.
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CIE Dept. invites all faculty, researchers, and students to MS Thesis Defense on "Intelligent Dispatch and Control Strategies for Microgrids: Integrating Model Predictive Control, Metaheuristic Optimization, and Machine Learning" by Mr. Emmanuel Agber, a Fulltime Graduate Student of CIE Dept.
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CIE Dept. invites all faculty, researchers, and students to MS Thesis Defense on "Supervisory Energy Management and Control of Grid-Connected Net Zero Energy Buildings Using Co-Simulation" by Mr. Mohammed Abaker Ahmed Slman, a Fulltime Graduate Student of CIE Dept.
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CIE Dept. invites all faculty, researchers, and students to PhD Dissertation on "Decentralized Self-Organization Controller Implementation for a Fully Autonomous Swarm of Robots" by Mr. Mohammed Abdelnasser Ahmed Mohammed, a Fulltime Graduate Student of CIE Dept.
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CIE Dept. invites all faculty, researchers, and students to MS Thesis Defense on "Detection of False-Data Injection and Replay Attacks on Controllable Crypto-Mining Loads in High-Penetration Renewable Microgrids" by Mr. Khidir Mohamed, a Fulltime Graduate Student of CIE Dept.
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CIE Dept. invites all faculty, researchers, and students to MS Thesis Defense on "System-Level Design, Experimental Validation, and Optimization of a Four-Layer PCB Embedded Autopilot System" by Ms Rawan Mohammad Al-Nawasrah, a Fulltime Graduate Student of CIE Dept.
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CIE Dept. invites all faculty, researchers, and students to MS Thesis Defense on "Safe and Agile UAV Navigation in Confined and Tight Spaces via Deep Reinforcement Learning" by Mr. Ziad Shoeib, a Fulltime Graduate Student of CIE Dept.