The Intelligent Systems & Optimization (ISO) Lab develops advanced machine learning methodologies that are more accurate, adaptable, secure, and efficient. We drive innovations across critical engineering and science domains, such as agriculture, healthcare, manufacturing, and more, to improve our lives.
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Research Focus
Research Focus
Optimization in AI
Domain Adaptation & Robust Modeling
Human-AI Collaboration & Trust
Healthcare Data Analytics
Biomass Analytics & Forestry Systems
Timeseries Modeling
Highlights / News
Highlights / News
Great News! We have recently been funded by NSF & the Louisiana Board of Regents.
ISO Lab welcomes two new graduate researchers: (1) Fahim Faysal and (2) Rahath Ahmed.
Dr. Rahman joined the Industrial Engineering program at the Louisiana Tech University College of Engineering and Science in the Fall of 2025.
Lab Director
Lab Director
Abdur Rahman, Ph.D.
Abdur Rahman, Ph.D.
Assistant Professor of Industrial Engineering
College of Engineering and Science (COES), Louisiana Tech University
Office Address: Bogard 233, 600 Dan Reneau Dr, Ruston, LA 71270
Office Phone: +1 (318) 257-3965
Email: arahman(at)latech(dot)edu
Dr. Abdur Rahman develops optimization-driven artificial intelligence that learns and adapts under uncertainty. His research spans robust decision-making, domain adaptation, time-series analytics, and human-AI collaboration. His work has applications in healthcare staffing, biomass quality assessment, and precision agriculture. He joined Louisiana Tech University as a tenure-track Assistant Professor in Fall 2025.
Academic Background
Ph.D. in Industrial Engineering, Mississippi State University, USA (August 2025).
M.S. in Industrial and Systems Engineering, Mississippi State University, USA (August 2024).
B.S. in Industrial and Production Engineering, BUET, Bangladesh (October 2018)
Current Students
Current Students
Fahim Faysal
Fahim Faysal
PhD Student (Dec 25 - )
Rahath Ahmed
Rahath Ahmed
PhD Student (Dec 25 - )
Caden Edwards
Caden Edwards
MS Student (Sep 25 - )
Opennings
Opennings
We currently have no openings in the ISO lab. However, if you are interested in any data analytics projects, have any specific ideas, and are looking for guidance, feel free to reach out.
Selected Journal Articles
Selected Journal Articles
Marulanda, D. E., Rahman, A., Street, J., Marufuzzaman, M., Wang, H., Gude, V. G., & Buchanan, R. (2025). MoistViT: A vision transformer model for moisture content prediction of wood chips. Systems and Soft Computing, 200429. [Paper]
Douglas, Z., Rahman, A., Duggar, W. N., & Wang, H. (2025). Automatic head and neck tumor segmentation through deep learning and Bayesian optimization on three-dimensional medical images. Computers in Biology and Medicine, 192, 110309. [Paper]
Chorney, W., Rahman, A., Wang, Y., Wang, H., & Peng, Z. (2025). Federated Learning for Heterogeneous Multi-Site Crop Disease Diagnosis. Mathematics, 13(9), 1401. [Paper]
Rahman, A., Street, J., Wooten, J., Marufuzzaman, M., Wang, H., Gude, V. G., & Buchanan, R. (2024). Interpretable Wood Chip Moisture Content Prediction Through Texture Analysis, Expert Systems with Applications, 126989. [Paper] [Code]
Rahman, A., He, L., & Wang, H. (2024). Activation function optimization scheme for image classification. Knowledge-Based Systems, 112502. [Paper] [Code]
Rahman, A., Street, J., Wooten, J., Marufuzzaman, M., Gude, V. G., Buchanan, R., & Wang, H. (2024). MoistNet: Machine vision-based deep learning models for wood chip moisture content measurement. Expert Systems with Applications, 125363. [Paper]
Rahman, A., Marufuzzaman, M., Street, J., Wooten, J., Gude, V. G., Buchanan, R., & Wang, H. (2024). A comprehensive review on wood chip moisture content assessment and prediction. Renewable and Sustainable Energy Reviews, 189, 113843. [Paper]
Wang, Y., Rahman, A., Duggar, W. N., Thomas, T. V., Roberts, P. R., Vijayakumar, S., ... & Wang, H. (2023). A gradient mapping guided explainable deep neural network for extracapsular extension identification in 3D head and neck cancer computed tomography images. Medical Physics. [Paper]
Duggar, W. N., Thomas, T. V., Wang, Y., Rahman, A., Wang, H., Roberts, P. R., ... & Vijayakumar, S. (2023). Preoperative Prediction and Identification of Extracapsular Extension in Head and Neck Cancer Patients: Progress and Potential. Cureus, 15(2). [Paper]
Rahman, A., Lu, Y., & Wang, H. (2023). Performance evaluation of deep learning object detectors for weed detection for cotton. Smart Agricultural Technology, 3, 100126. [Paper] [Code] [Data]
Teaching & Learning
Teaching & Learning
At Louisiana Tech
Spring 2026 - EMGT 4143/ INEN 5143: Statistical Analysis for Six Sigma (Upcoming)
Winter 2026 - INEN 4103/ INEN 5053: Manufacturing Systems Management (Ongoing)
Class type - Undergraduate & Graduate, in-person & online (hybrid)
Class size - 13
Fall 2025 - EMGT 4143/ INEN 5143: Statistical Analysis for Six Sigma
Class type - Undergraduate & Graduate, in-person & online (hybrid)
Class size - 53
At Mississippi State
Summer 2024 - IE 4613/6613: Engineering Statistics I (Evaluation: 3.95/4.00)
Class type - Undergraduate & Graduate, in-person & online (hybrid)
Class size - 32
Research Support
Research Support
Lousiana Tech University's Start-up Fund for Early-career Faculty
National Science Foundation
Louisiana Board of Regents
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