Publications

Journal Publications

Published/In-press/Accepted

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]

Under Review

Rahman, A., Marufuzzaman, M., Street, JT., Wooten, J., Gude, VG., & Wang, H. “Boosting Discriminability of Transferable Features in Unsupervised Domain Adaptation.”
Rahman, A., Ma, J., & Wang, H. “A Proximal Policy Optimization-based Reinforcement Learning Model for Multivariate Time Series Anomaly Detection.”

Conference Publications

Published in Proceedings (* Student Co-mentored)

Eskorouchi, A.*, Rahman, A., Street, J., Marufuzzaman, M., & Wang, H. Enhanced DETR-Based Framework for Automated Wood Chip Size Distribution Estimation in High Volume Biomass Manufacturing, In The 34th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM 2025), Binghamton University, New York City, USA, June 21-24, 2025.
Eskorouchi, A.*, Rahman, A., Street, J., Marufuzzaman, M., & Wang, H. Automated Wood Chip Size Estimation with YOLO-Based Object Detection, In IISE Annual Conference and Expo, Atlanta, Georgia, May 31-June 3, 2025.
Dehghan-Bonari, M., Rahman, A., Wang, H., Carruth, D., & Marufuzzaman, M. Deep Bayesian Inverse Reinforcement Learning Technique to Assess Building Safety under an Active Shooter Violence Situation, In IISE Annual Conference and Expo, Atlanta, Georgia, May 31-June 3, 2025.
Rahman, A., Dehghan-Bonari, M., Wang, H., Carruth, D., & Marufuzzaman, M. Multi-Object Tracking in Video-based Trajectory Mapping during Simulated Active Shooting Scenario, In IISE Annual Conference and Expo, Atlanta, Georgia, May 31-June 3, 2025.
Rahman, A., Eskorouchi, A.*, Street, J., Wooten, J., Marufuzzaman, M., & Wang, H. Wood Chip Moisture Content Assessment Using Infrared Image-Based Machine Learning, in Proceedings of the ASABE International Meeting (AIM 2024), Anaheim, CA, July 28-31, 2024. [Poster]
Rahman, A., Kolla, M.*, Marufuzzaman, M., Wang, H., & Peng, Z. Image-based Genotype Encoding for Phenotype Prediction and Exploration for Result Explainability, In IISE Annual Conference and Expo, Montreal, Canada, May 18-22, 2024. [Paper]
Rahman, A., Chen, M.*, Lu, Y., & Wang, H. Weed Detection in Cotton Fields Using YOLOv5: Prototype Development and Deployment, In IISE Annual Conference and Expo, Montreal, Canada, May 18-22, 2024. [Paper]
Rahman, A., Marufuzzaman, M., & Wang, H. An Interpretable Optimal Pricing Strategy for E-Commerce Platforms, In IISE Annual Conference and Expo, Montreal, Canada, May 18-22, 2024. [Paper]
Rahman, A., Marufuzzaman, M., Street, J. T., Wooten, J., Gude, V. G., & Wang, H. An Interpretable Deep Learning Model for Wood Chip Moisture Content Prediction, In IISE Annual Conference and Expo, New Orleans, Louisiana, May 21-24, 2023. [Paper]
Rahman, A., Lu, Y., & Wang, H. (2022). Deep Neural Networks for Weed Detections Towards Precision Weeding, In 2022 ASABE Annual International Meeting, Houston, Texas, July 17-22, 2022. (p. 1). [Paper]
Rahman, A., Sarker, S., & Islam, M. T. (2018, December). Simulating Cutting Line of a Furniture Industry, In 2018 International Conference on Production and Operations Management Society (POMS), Kandy, Sri Lanka, Dec 14-16, 2018. (pp. 1-7). [Paper]

Peer Reviewed Abstract (underlining denotes the presenter)

Neupane, T., Street, J., Rahman, A., Marufuzzaman, M., & Wang, H. “Wood Chip Moisture Content Prediction Through Transfer Learning-based Regression Analysis”, International Society of Wood Science and Technology and Forest Product Society Joint Conference, Fort Collins, Colorado, 2025.
Neupane, T., Street, J., Rahman, A., Marufuzzaman, M., & Wang, H. “Image-based Moisture Prediction of Wood Chips Through Transfer Learning”, 2025 AI in Agriculture and Natural Resources Conference, Starkville, Mississippi, 2025.
Rahman, A., Kolla, M.*, Peng, J., & Wang, H. “Decoding Significant Genomic Loci for Traits from Image Encoded DNA”, IISE Annual Conference and Expo 2025, Atlanta, Georgia, 2025.
Rahman, A., Dehghan Bonari, M., Marufuzzaman, M., Carruth, D., and Wang, H., “Person Re-Identification in Video-based Trajectory Mapping during Simulated Active Shooting Scenario”, IISE Annual Conference and Expo 2025, Atlanta, Georgia, 2025.
Marulanda, D., Rahman, A., Street, J., Wooten, J., Marufuzzaman, M., & Wang, H. “Generating High-Resolution Wood Chip Images with Diffusion Transformers for Enhanced Moisture Content Prediction”, IISE Annual Conference and Expo 2025, Atlanta, Georgia, 2025.
Eskorouchi, A.*, Rahman, A., Street, J., Wooten, J., Marufuzzaman, M., & Wang, H. “Automated Wood Chip Size Estimation with Deep Learning-Based Object Detection”, IISE Annual Conference and Expo 2025, Atlanta, Georgia, 2025.
Rahman, A., Marufuzzaman, M., & Wang, H. “Boosting Discriminability of Transferable Features in Unsupervised Domain Adaptation”, IISE Annual Conference and Expo 2024, Montreal, Canada, 2024.
Chen, M.*, Nunn, D., Rahman, A., and Wang, H., “Developing a Prototype of Artificial Intelligence System for Real-time Cotton Weed Detection,” IISE Annual Conference and Expo, 2023.
Rahman, A., Chen, M.*, Nunn, D., Lu, Y., and Wang, H., “Developing a Prototype of Cost-effective Artificial Intelligence System for Real-time Cotton Weed Detection,” Beltwide Cotton Conference, 2023.
Wang, Y., Rahman, A., Duggar, W. N., Thomas, T. V., Roberts, P. R., Vijayakumar, S., Jiao, Z., Bian, L., and Wang, H. “An Explainable Deep Neural Network for Extracapsular Extension Identification in 3D Head and Neck Cancer Computed Tomography Images,” INFORMS Annual Meeting, 2023.
Rahman, A., Wang, Y., & Wang, H. “Exponential Error Linear Unit (EELU): Optimization-boosted Activation Function for Image Classification”, IISE Annual Conference and Expo, 2022.
Rahman, A., Ma, J., & Wang, H. “Multivariate Time Series Anomaly Detection through Reinforcement Learning”, ICCMAE 2022: The Second International Conference on Computational Methods and Applications in Engineering. Mississippi State, Mississippi, 2022.
Wang, Y., Rahman, A., Duggar, W. N., Thomas, T. V., Roberts, P. R., Vijayakumar, S., Jiao, Z., Bian, L., and Wang, H. “High-risk Head and Neck Cancer Evaluation with Artificial Intelligence,” 39th Annual Southern Biomedical Engineering Conference, 2022.

Poster Presentations

Budhathoki, P., Street, JT., Neupane, T., Rahman, A., Marufuzzaman, M., & Wang, H. “Wood Chip Moisture Content Recognition using Convolutional Neural Networks and Transfer Learning”, 2025 AI in Agriculture and Natural Resources Conference, Starkville, Mississippi.
Gupta, N., Neupane, T., Street, JT., Rahman, A., Marufuzzaman, M., & Wang, H. “Deep Learning-Based Moisture Prediction: A Comparison of Cropped and Original Wood Chip Images”, 2025 AI in Agriculture and Natural Resources Conference, Starkville, Mississippi.
Rahman, A., Eskorouchi, A.*, Street, J., Wooten, J., Marufuzzaman, M., & Wang, H. “Wood Chip Moisture Content Assessment Using Infrared Image-Based Machine Learning”, ASABE International Meeting, 2024. [Poster]
Rahman, A., Marufuzzaman, M., Street, J., Wooten, J., &Wang, H. “An Interpretable Deep Learning Model for Wood Chip Moisture Content Prediction”, 2024 IISE Southeastern Regional Conference, hosted by Mississippi State University, 2024. (1st prize winner in poster presentation) [Poster]

Symposium Presentations

Integrating Texture Features and Domain Adaptation for Robust Moisture Content Prediction in Wood Chips, Graduate Research Symposium Fall 2024, Mississippi State University, Mississippi State, Oct 5, 2024. (1st prize in Oral Presentation)
“Boosting Discrimanility of Transferable Features in Unsupervised Domain Adaptation”, Graduate Research Symposium – Spring 2024, Mississippi State University, Mississippi State, Feb 26, 2024.
“MoistNet: Neural Architecture Search and Bayesian Optimization-driven Model for Moisture Content Prediction in Wood Chips”, Graduate Research Symposium – Fall 2023, Mississippi State University, Mississippi State, Oct 21, 2023.
“Prediction of Genotype and Phenotype Association Using Deep Learning”, Graduate Research Symposium – Fall 2023, Mississippi State University, Mississippi State, Oct 21, 2023. (3rd prize in Oral Presentation)
“An Interpretable Deep Learning Model for Wood Chip Moisture Content Prediction”, Graduate Research Symposium – Spring 2023, Mississippi State University, Mississippi State, Feb 25, 2023. (3rd prize in Oral Presentation) [News]
“Multivariate Time Series Anomaly Detection through Reinforcement Learning”, Graduate Research Symposium – Fall 2022, Mississippi State University, Mississippi State, Oct 22, 2022.
“Activation Function Optimization Scheme for Image Classification”, Graduate Research Symposium – Spring 2022, Mississippi State University, Mississippi State, Feb 26, 2022. (1st prize in Oral Presentation) [News]

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