Mohammad D. Alahmadi

About

Mohammad D. Alahmadi is an Associate Professor of Software Engineering at the University of Jeddah, Saudi Arabia, holding a PhD in Computer Science from Florida State University. His research focuses on machine learning, computer vision, large language models, and software engineering, with applications in medical image segmentation and software artifact mining. He is recognized among the Stanford–Elsevier top 2% of scientists worldwide.

Employment

• University of Jeddah Associate Professor
  2014 - Present

Education

• Florida State University PhD
  2018 - 2020
• Florida State University Master of Science
  2016 - 2017

Projects & Funding

Projects & funding information is unavailable.

Publications (36)

• The perception and impact of non-inclusive language in software artifacts
  Journal of Systems and Software 2026 DOI: 10.1016/j.jss.2026.113024
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• IoTutorMine: A Tool for Mining Hardware Bills of Materials from IoT Tutorial Videos
  2026 DOI: 10.1145/3832783.3834647
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• VidSumEval: A Web Platform and Benchmark for Evaluating AI-Generated Programming Video Summaries
  2026 DOI: 10.1145/3832783.3834594
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• VidTutorAssistant: Automating Responses to Programming Tutorial Questions
  2026 DOI: 10.1145/3832783.3834599
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• Gaussian Context‐Guided Expert Personalization for Multi‐Rater Medical Image Segmentation
  International Journal of Imaging Systems and Technology 2026 DOI: 10.1002/ima.70443
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• A dual-path framework for 3D medical image segmentation with uncertainty-aware refinement
  Biomedical Signal Processing and Control 2026 DOI: 10.1016/j.bspc.2026.110386
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• MISEI---Mycelia Inspired Secure Edge Intelligence for Privacy Aware Consumer Electronic Systems
  IEEE Transactions on Consumer Electronics 2026 DOI: 10.1109/TCE.2026.3675884
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• Dynamic consensus control of vehicle platoons using distributed model predictive control under cyber–physical constraints
  Alexandria Engineering Journal 2026 DOI: 10.1016/j.aej.2026.05.017
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• Reinforcement Learning for Server-Aware Offloading in Multi-Tier Multi-Instance Computing Architecture
  ACM Transactions on Intelligent Systems and Technology 2026 DOI: 10.1145/3776562
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• ABS6G: Adaptive Blockchain Framework for Real-Time Trust Management of Smart City IoT Systems in 6G Networks
  IEEE Internet of Things Journal 2026 DOI: 10.1109/JIOT.2026.3726072
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• Evaluating Large Language Models for Generating YouTube Programming Tutorial Metadata From Video Transcripts
  IEEE Access 2026 DOI: 10.1109/ACCESS.2026.3696617
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• Executing Signal Control From Text: LLM Fidelity on a CV Platoon-Based Optimization Algorithm
  IEEE Access 2026 DOI: 10.1109/ACCESS.2026.3673185
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• VidToCode: LLM-Based Source Code Reconstruction From Programming Video Tutorial Transcripts
  IEEE Access 2026 DOI: 10.1109/ACCESS.2026.3741380
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• Prompt-Guided Refinement: A Novel Technique for Improving Intervertebral Disc Semantic Labeling
  Mathematics 2025 DOI: 10.3390/math13243944
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• MSA-Net: A Multi-Scale Attention Network with Contrastive Learning for Robust Intervertebral Disc Labeling in MRI
  Mathematics 2025 DOI: 10.3390/math13233811
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• Extract Nutritional Information from Bilingual Food Labels Using Large Language Models
  Journal of Imaging 2025 DOI: 10.3390/jimaging11080271
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• PSL-IoD: PUF-Based Secure Last-Mile Drone Delivery in Supply Chain Management
  Mohammad D. Alahmadi, Ahmed Alzahrani, Azeem Irshad +1 more
  Mathematics 2025 DOI: 10.3390/math13132143
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• Improving Freight Traffic Efficiency at Urban Intersections Using Heavy Vehicle Platooning
  Applied Sciences 2025 DOI: 10.3390/app15052682
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• SCC-GPT: Source Code Classification Based on Generative Pre-Trained Transformers
  Mathematics 2024 DOI: 10.3390/math12132128
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• Optimizing OCR Performance for Programming Videos: The Role of Image Super-Resolution and Large Language Models
  Mathematics 2024 DOI: 10.3390/math12071036
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