Solution Architect & Automation Engineer based in Nashville, TN. Bridging the gap between intelligent document processing, AI/ML workflows, and enterprise-scale platforms.
Have fun and Interact with the particle engine. My favorite is the QUASARS engine.
A highly experienced and accomplished automation engineer, architect, and researcher, with significant experience delivering end-to-end enterprise automation, AI/ML, and data engineering solutions.
Technology professional specializing in robotic process automation, intelligent document processing, and hybrid cloud/on-premise infrastructure. Demonstrates strong expertise in Python, C#, and SQL, combined with modern engineering practices. Brings a balanced blend of deep technical capability, architectural thinking, and practical problem-solving across both strategic initiatives and hands-on execution.
Architecting enterprise-grade services, intelligent automation solutions, and scalable data pipelines. Specializing in API integration, workflow optimization, and AI-driven image classification/extraction. Leveraging Microsoft Fabric Lakehouse, Azure Synapse, and Google Cloud Platform (GCP) to design modern data architectures, with containerized deployments using Docker. Extensive experience integrating enterprise systems such as Infor CloudSuite and ION with UiPath.
Taught undergraduate courses in computer science, including Computer Organization and Architecture (COMP 2400), Introduction to Computing (COMP 1210), and Introduction to Bioinformatics (COMP 3112). Focused on building strong foundational knowledge in systems, programming, and computational biology. Mentored students and supported academic research initiatives, fostering analytical thinking and applied problem-solving skills.
Designed and delivered intelligent automation solutions focused on OCR, image extraction, and classification. Utilized Kofax TotalAgility for enterprise-grade document processing, and Automation Anywhere A360 for scalable RPA and AI/ML-driven workflows. Integrated Power Automate and Azure IaaS to build robust, distributed automation platforms, improving processing accuracy and operational efficiency.
Engineered and delivered enterprise and public-facing platforms across SharePoint, Java/JEE, and .NET technologies. Led full lifecycle delivery, including end-to-end solution integration, custom application development, and infrastructure implementation. Emphasized scalable architecture, system interoperability, and long-term maintainability, ensuring reliable, high-performance services across diverse enterprise environments.
Research spanning bioinformatics, protein structure prediction, rotamer modeling, RNA analysis, and applied machine learning.
A machine learning framework for assigning protein secondary structure from Cα backbone geometry, focused on extracting meaningful structural signals for protein modeling and structural analysis workflows.
Explores protein side-chain packing through rotamer clustering and machine learning techniques, with emphasis on improving structural prediction quality and rotamer selection strategies.
Presents a Bayesian approach for protein rotamer prediction using Dirichlet priors and spatial smoothing, advancing probabilistic modeling for side-chain conformation prediction.
Computational research on RNA structure comparison methods that combine structural matching with sequence alignment to improve biological similarity analysis.
Visualization-focused work for making RNA sequence structures easier to inspect, compare, and communicate across research workflows.
Practical technical notes, troubleshooting guides, and engineering write-ups from my blog.
An outstanding software engineer and architect with strong expertise across multiple domains. Mohamad brings creativity, problem-solving ability, and a rare capacity to deliver high-quality solutions under challenging conditions.
Mohamad consistently delivers beyond expectations, combining deep technical expertise with a strong sense of ownership. His ability to take complex deliverables to a level of precision and completeness is exceptional.
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