Dr. Mohammad Rahman

Home > Colleges & Schools > CBIS > Dr-Mohammad-Rahman

Rahman, Mohammad Arafatur, Ph.D.

Assistant Professor
Department of Computer Science
Room 107, Brimmer Hall
Tuskegee University
1200 W. Montgomery Rd.
Tuskegee, AL  36088

Phone: 334-727-8982
Fax: 334-724-4389
Email:  mrahman@tuskegee.edu 
   


Education

  • Ph.D., Computer & Information Systems Engineering, Tennessee State University, 2020
  • M.Sc., M.Sc., Computer & Information Systems Engineering, Tennessee State University, 2016
  • Executive MBA, Institute of Business Administration (IBA), Bangladesh, 2013
  • B.Sc., Electrical & Electronic Engineering (EEE), Bangladesh University of Engineering and Technology (BUET), Bangladesh, 2006

Working Experience

  • Assistant Professor, Computer Science, Tuskegee University, Aug 2021 – Present
  • Systems Coordinator, Office of Technology Services (OTS), Tennessee State University, May 2020 - July 2021
  • Adjunct Faculty, Electrical and Computer Engineering, Tennessee State University, Jan 2019 - May 2020
  • Teaching Assistant / Research Assistant, Electrical and Computer Engineering / Center of Excellence, Tennessee State University, Aug 2014 - Dec 2018
  • Sr. Engineer, Core Network, Robi Axiata Ltd., Bangladesh Ltd., Jan 2012 - Aug 2014
  • Sr. Engineer, Core Network Planning, Robi Axiata Ltd., Bangladesh, June 2010 - Jan 2012
  • Engineer, Core Network/Switching System Operation, Robi Axiata Ltd., Bangladesh, Nov 2006 - June 2010

Selected Publications


  • M. Rahman, U. Honey, S. Rangari, F. Wu, “Blockchain-Based Supply Chain Management for Ensuring the Quality and Traceability of Fresh Produce: an Illustrative Analysis,” 2025 IEEE 15th Annual Computing and Communication Workshop and Conference (CCWC) Las Vegas, NV, January 06-08, 2025.
  • T. Tasnim, A. Saha, M. Rahman, F. Wu, “Quantum vs Classical: Performance Benchmarking of CNN and QCNN in Binary Image Classification,” 2025 IEEE 15th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, January 08, 2025.
  • A. Saha, M. Rahman, F. Wu, “Groundwater Level Prediction: Analyzing the Performance of LSTM and QLSTM Model,” 2024 IEEE International Conference on Big Data (Big Data), Washington DC, December 15-18, 2024.