Mohsen Alghasi

Passionate AI Developer and Data Scientist with strong expertise in Machine Learning, NLP, and Retrieval-Augmented Generation (RAG). Skilled in building scalable AI solutions, leveraging advanced algorithms and cloud technologies to solve complex problems. Committed to continuous learning and driving innovation in data-driven applications.

• Designed and implemented a Retrieval-Augmented Generation (RAG) pipeline to enhance information retrieval and contextual response generation.
• Integrated vector databases and transformer-based models for semantic search and dynamic knowledge injection.
• Optimised query relevance and response accuracy, enabling scalable AI-driven decision support for complex workflows.
• Leveraged frameworks such as HuggingFace Transformers and LangChain for modular, production-ready deployment.
• Managed the RAG application in Azure Hub, overseeing end-to-end development from architecture design to deployment.
• Developed predictive ML models (XGBoost, Random Forest) to optimise logistics operations, reducing delivery delays by 25% and improving throughput efficiency.
• Built time-series forecasting models (ARIMA, Prophet) to enhance inventory control, cutting overstock by 15%.
• Designed end-to-end AI systems integrating Machine Learning, NLP, and Generative AI to automate industrial workflows and enable scalable, data-driven decision-making.
• Delivered solutions bridging traditional operations with modern data science, driving transformation across energy, logistics, and manufacturing sectors.

MBA – Sheffield Hallam University (Sep 2022 – Sep 2023)

Focus: Business Strategy, Leadership, and Data-Driven Decision Making.

B.Sc. Electrical Power Engineering – Shiraz University (Sep 2003 – Sep 2007)

Focus: Electrical Systems, Power Distribution, and Engineering Fundamentals.