Lecturer Riyadh Nazar Ali Algburi
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Degree

PH.D

General & Specialist

Mechatronics Engineering - هندسة ميكاترونكس

E-mail

[email protected]

University granting the Degree

Southwest Jiaotong University

Academic Title

Lecturer

Colleges

College of Modern Technologies

 

1. Academic Teaching

  •  Al-Farahidi University, Baghdad, Iraq: 

    Period: (2023 – 2025). 

    Position: Instructor.

    • Courses Taught: Program II Matlab (2nd stage) and Aircraft Electronic and Electric Systems (3rd stage) in the Department of Aeronautical Technical Engineering. 

  •  Al-Hussein University College, Karbala, Iraq:

    •  Period: (September 2013 – June 2016).

    •  Position: Instructor.

    •  Courses Taught: Power Electronics and Digital System Design (Medical Engineering Department), and Control Systems (Computer Science Engineering and Communications Engineering). 

2. Research Experience

  •  Engineering Research Center of Advanced Driving Energy-Saving Technology, Chengdu, China:

    •  Period: (September 2016 – 2022).

    •  Position: Member of Research Team. 

    •  Focus Areas: Sparse representation, Deep learning, and their applications in fault detection, diagnosis, and condition monitoring for industrial robots. 

3. Additional Academic Activity

  •  Scientific Reviewer: Serves as a reviewer for several prestigious international scientific journals, including: 

    • IEEE Transactions on Industrial Electronics. 

    • Expert Systems with Applications. 

    • Applied Intelligence. 

    • Sensors.

  • A hybrid deep learning pavement crack semantic segmentation.

  • Health assessment and fault detection system for an industrial robot using the rotary encoder signal.

  • Asymmetric dual-decoder-U-Net for pavement crack semantic segmentation.

  • Weakly supervised pavement crack semantic segmentation based on multi-scale object localization and incremental annotation refinement.

  • Improvement of an industrial robotic flaw detection system.

  • A new synergy of singular spectrum analysis with a conscious algorithm to detect faults in industrial robotics.

  • Weakly supervised semantic segmentation by iteratively refining optimal segmentation with deep cues guidance.

  • Object scale selection of hierarchical image segmentation with deep seeds.

  • Optimal scale of hierarchical image segmentation with scribbles guidance for weakly supervised semantic segmentation.

  • Detecting feeble position oscillations from rotary encoder signal in an industrial robot via singular spectrum analysis.

  • Implementation of singular spectrum analysis in industrial robot to detect weak position fluctuations.

  • Advanced fault diagnosis in industrial robots through hierarchical hyper-laplacian priors and singular spectrum analysis.

  • Mdau-net: A multi-scale u-net with dual attention module for pavement crack segmentation.

  • Design and implementation fuzzy-PLC temperature controller for the cooling tower to reduce dust emission in cement plant.

  • HHLP-SSA: enhanced fault diagnosis in industrial robots using hierarchical hyper-Laplacian prior and singular spectrum analysis.

  • SSA-sparse MHD: singular spectrum analysis paired with sparse maximum harmonics deconvolution for detecting feeble defect signals in industrial robots.

  • Detection of weak position oscillations in the industrial robot by singular spectrum analysis.

  • Triplet Attention-Enhanced UNet Architectures for Advanced Skin Lesion Segmentation.

  • Physics-Informed Optimization of Dross Formation in Fiber-Laser Cutting: From Multi-Variable Design to a Single Decision Rule.

  • Design of a Non-Ideal Buck Converter.

 

  • Member, Iraqi Engineers Union (IEU).

 

  • Member, Iraqi Academics Union (IAU).
  •  Member of Research Team, Engineering Research Center of Advanced Driving Energy-Saving Technology, Chengdu, China (2016–2022). 
  •  Certified Peer Reviewer, Elsevier Researcher Academy.

  1. Control Systems

  2. Digital Systems Design

  3. Power Electronics

  4. Electrical Networks I

  5. Electrical and Electronic Engineering II

  6. Introduction to Robotics

  7. Matlab

 

First: Training Courses and Professional Certifications (Coursera & Google) The Doctor has received intensive training in the fields of Artificial Intelligence and Data Analytics through global platforms:

  •  Deep Learning Specialization: Supervised by Professor Andrew Ng. 

  •  Python for Everybody Specialization: From the University of Michigan.

  •  Machine Learning Specialization: Supervised by Professor Andrew Ng. 

  •  Google Data Analytics Professional Certificate.

  •  SQL for Data Science: From the University of California, Davis. 

Second: Workshops and Researcher Academy (Elsevier) The Doctor completed specialized courses in developing scientific research and evaluation skills:

  •  Fundamentals of Peer Review: From Elsevier Researcher Academy.

  •  Certified Peer Reviewer Course. 

Third: Participation in Conferences and Scientific Symposia (Conference Proceedings) The Doctor participated in presenting his research at several international scientific gatherings, which serve as intensive technical symposia and workshops:

  •  2024 8th International Artificial Intelligence and Data Processing Symposium (IDAP): Participated with several research papers related to fault diagnosis in robots and medical image segmentation.

  •  2023 18th International Conference on Intelligent Systems and Knowledge Engineering (ISKE): Regarding pavement crack segmentation using Artificial Intelligence.