Muhammad Ali

• Built educational chatbots for students using RAG pipelines, Agentic AI, and advanced prompt engineering. • Created LLM-powered assistants to support interactive learning and personalized responses. • Designed and deployed machine-learning solutions to optimize smart buildings and reduce energy consumption. • Developed cloud-native AWS workflows to operate end-to-end ML services efficiently. • Applied MLOps practices, including model monitoring, automated retraining, and performance tracking.

• Analyzed network performance and outage reports to identify root causes and improve reliability. • Tracked operational costs and visualized metrics using dashboards and reports. • Delivered actionable, data-driven insights to technical teams to reduce downtime and optimize operations.

1. Designed and implemented an ETL pipeline for high-frequency PV and transformer data. 2. Managed and optimized data warehouses, enabling real-time analytics and reporting. 3. Built and deployed forecasting models for solar energy production. 4. Automated data ingestion and transformation workflows to improve pipeline efficiency. 5. Collaborated with cross-functional team to ensure data quality, consistency, and scalability.

Thesis Title: Development of a Scalable Machine Learning Pipeline on AWS for Optimizing Building Heating Systems using Reinforcement Learning and Transfer Learning Skills Developed: Machine Learning & AI, AI Agents, RAG, AWS, Cloud Computing, MLops, Databases, ETL Pipelines