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Dr.Yasser Ismail

  • Dr. Yasser Ismail
  • Associate Professor
  • Electrical Engineering Department
  • Email: yasser_ismail@subr.edu
  • Phone: (225) 771-4672
  • Office: Pinchback, Room 424

Dr. Yasser Ismail is an Associate Professor in the Electrical Engineering Department at Southern University and A&M College (SU). Dr. Yasser Ismail has over twenty (20) years of professional experience in teaching and research. Prior to joining SU, he was a faculty at five (5) international universities (Mansoura University, University of Louisiana at Lafayette, Umm Al-Qura University, University of Bahrain, and Zewail City of Science and Technology University). With a focus on Electronics and Electrical Communication, he holds a bachelor’s and a master’s degrees from Mansoura University in Egypt. He also got a master’s and a doctorate degrees in Computer Engineering from University of Louisiana at Lafayette.

Dr. Ismail has a broad background in machine learning applications, modeling and design techniques for reliable, low-power, and high-performance VLSI and FPGA systems, Cloud Computing, Cybersecurity, Internet of Video Things (IoVT), digital video processing algorithms/architectures levels, and wireless and digital communication systems.

Dr. Ismail has over 66 publications including books, book chapters, and articles in high-ranked journals and conferences. He served as an NSF panel reviewer from 2019 – present. He served as a PI and Co-PI of over twelve (17) funded grants from NSF, State, and international fund agencies. He was awarded the Partnering, Research, Innovation, Development, and Entrepreneurship award (P. R. I. D. E) by Southern University. Dr. Ismail served as a reviewer for several peer-reviewed conferences and journals. He served as a session chair and as a member of the organizing committee of several international conferences. Dr. Ismail served as a member of several Editorial Boards from 2018 – present. He also served as an associate editor for an indexed journal, International Journal of Computing and Digital Systems (IJCDS).

Dr. Ismail participated in organizing several STEM programs and activities for undergraduate and K-12 students at the College of Sciences and Engineering and high schools. He successfully supervised over 13 master and Ph.D. students. Dr. Ismail taught over 17 courses related to Electrical and Computer Engineering at different Universities. He developed the curriculum of three (3) new courses at the College of Sciences and Engineering, SU. He worked as an external moderator for some courses at University of Bahrain (UoB).

 

Fall 2022 Classes:

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Office Hours:

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Syllabi:

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Research Interests:
  • Machine-Learning Models for Corrosion Classification Levels: Developed machine learning-based algorithms to inspect and determine undesirable alloy phases distributed along grain boundaries for the Al-5XXX series. These machine-learning algorithms can detect different levels of corrosion for such alloy series.
  • Agriculture–Based Image Processing and Machine Learning: Develop a system that can monitor and determine the effect of adding chemical materials to plants and soils. This work can be extended to characterize various materials’ degradations.
  • Machine Vision–based Detection and Measurement of Welding Scene Features: Developed machine vision-based algorithms to detect geometric measurements of arc welding scene features using Carderock’s patented attenuated-long wave infrared radiation imaging technique.
  • Smart traffic-Based Artificial Intelligence (AI) and Machine Learning: Develop smart systems-based Deep Learning algorithms that can automatically count different objects. Such systems and algorithms are very helpful in designing new smart cities.
  • Internet of Video Things (IoVT): Design video surveillance systems, for homeland security applications that match the allowed hardware complexity of the Internet of Video Things (IoVT) infrastructure.
  • Digital Video Processing Algorithms/Architectures levels: Develop video processing algorithms and architectures. My research involves Video Compression algorithms and architectures, specifically Motion Estimation and Compensation, DCT transform, and Vector Quantization.
  • VLSI and FPGA Design (Low-Power and High-Speed Performance Embedded Systems): Design video systems taking into consideration optimizing the encoding speed and studying the effect on both the area and power consumption of the designed systems. Systems are tested and implemented in either FPGA or ASIC flow design.
  • Wireless and Digital Communication Systems: Design several techniques and systems that help in compressing the transmitted bit-rate of a speech signal over wireless communication channels.
 
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