Bashir Alsaidi

M.E. Candidate & Research Assistant


Tennessee State University
Department of Mechanical and Manufacturing Engineering
Tel: 615-963-5081


Research Interest:

  • Design, analysis, modeling, optimizing, and Simulation of static and dynamic systems.
  • Image Processing, Surface defect detection and Classification, Artificial Intelligence, Machine Learning, Data Mining.


  • M.E., Mechanical Engineering, Tennessee State University, USA, 2013.
  • B.Sc., Mechanical Engineering, Mosul University, Iraq, 2002.

Professional Experience:

  • Research Assistant, Intelligent Tactical Mobility Robotics Lab, Tennessee State University.
  • Maintenance Engineer, Asiacell Telecommunications Company, Iraq.

Project Scope:
Visual Inspection (VI) usually is the final step in manufacturing process and the quality of the product is a major factor that which highly effects a company’s reputation in the market and it might lead to a disaster when the product gets a human life involves into it. VI is a tedious work for inspector engineers when the products numbers are in thousands daily, in this case, this inspection work will lead to a misjudgments easily, therefore the need for developing an automated systems arise in manufacturing process applications. An automatic Visual inspection system (AVIS) is one of image processing techniques that researchers effort themselves to develop some of its applications in the last few decays and the challenges is how to improve like these systems to have them detect that abnormalities from the surfaces efficiently as well as how to have an AVIS to be smart enough to classify that different types of defect as the human does. Where improving like these systems lead to several benefits in the manufacturing, like avoiding an inspection’s misjudgments, decreasing a detection time of products which leads to increasing the production lines, decreasing a labor cost by automating a systems, and so on.

The Goal of this project is to develop an AVIS that can detect surface abnormalities and to classify these defects in different classes which will be classified according to its own features.

Academic Activities:

  • Lone Star Competition-2012: Involved in Design and Fabrication of Battery Powered Rope Ascender, Organized by Wright-Patterson Air Force Base, Dayton, Ohio.
  • CAD Design-2011: Unique mini industrial stamp, Tennessee State University.

Research Applications:

Detecting a Surface abnormalities and classify it can be considered an open field of research in image processing for developing an automatics visual inspection systems (AVIS) for manufacturing processes Technologies.

Publications and Presentations:

  • Vinayak Elangovan, Bashir Alsaidi, and Amir Shirkhodaie,” A Multi-attribute Based Methodology for Vehicle Detection & Identification,” SPIE Defense, Security and Sensing Conference, Baltimore, MD, April 2013.
  • Bashir F. Alsaidi, “Defect Detection and Classification on Metallic Parts using Image Processing Techniques,” 35th Annual Research Symposium, Tennessee State University, March 2013.  
  • Bashir Alsaidi, “Defect Classification of Metallic Surface for Automatic Inspection Systems,” M.S. Thesis, Tennessee State University, August 2013.

Research Advisor:
Dr. Amir Shirkhodaie
Director, Center of Excellence for Battlefield Sensor Fusion
Tennessee State University
Dept. of Mechanical and Manufacturing Engineering
3500 John A. Merritt Blvd., Nashville, TN 37209
Tel: 615-963-5396

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