Acerca de Muhammad Adnan
Machine Learning Engineer and Data Professional with a Ph.D. in Computational Mathematics, specializing in data pipelines, applied machine learning, and AI-driven solutions.
I help companies transform raw and unstructured data into actionable insights and scalable systems. My experience includes building end-to-end data workflows, from data ingestion and cleaning to analysis and deployment. I have developed Retrieval-Augmented Generation (RAG) pipelines for document processing and semantic search, enabling efficient information retrieval from complex datasets.
My core expertise includes Python (Pandas, NumPy, Scikit-learn), SQL, ETL pipeline development, and data transformation. I also work with data visualization tools such as Power BI and Excel to deliver clear, decision-ready outputs.
I focus on delivering practical, business-oriented solutions, including:
- Data cleaning and structuring for reliable analytics
- Dashboard development and reporting
- Machine learning models for pattern detection and prediction
- AI-powered document and knowledge systems (RAG)
- Automated data pipelines and workflows
I am comfortable working with both structured and unstructured data and collaborating with cross-functional teams. I prioritize clarity, reliability, and scalability in every project.
Available for freelance projects in data analysis, machine learning, and AI system development.
Inglés
Bilingüe o nativo
Solo teletrabajo
Lleva a cabo sus proyectos principalmente en remoto
Experiencia
- AIcloudersMachine Learning Engineerabril de 2024 - Hoy (2 años y 4 meses)• • Designed and implemented a Retrieval-Augmented Generation (RAG) system for document-based question answering• • Built full pipeline: document ingestion → preprocessing → chunking → embedding generation → retrieval → response generation• • Implemented FAISS-based vector search for semantic retrieval over unstructured documents• • Developed REST-style interaction layer using FastAPI concepts and modular architecture• • Built interactive UI using Streamlit for real-time querying• • Optimized retrieval quality using embedding tuning and prompt engineering Document Retrieval & QA System• • Developed AI system for querying domain-specific documents using embeddings and vector search• • Implemented preprocessing pipelines for structured and unstructured data (PDF/JSON)• • Built automated workflows for data ingestion and retrieval• • Focused on improving grounding and reducing hallucinations in LLM responses Vector• • Built machine learning models to predict customer behavior and improve engagement• • Developed ETL pipelines for data cleaning, feature engineering, and model training• • Integrated models into a reproducible workflow for analysis and deployment• • Collaborated within a team to deliver a complete AI-driven solution• • Developed ML models using PyTorch for high-dimensional scientific datasets• • Processed large-scale structured data and extracted meaningful patterns• • Combined domain knowledge with machine learning for predictive modeling Built real-time object detection and tracking system OpenCV Implemented video stream processing pipeline for live inference Developed interactive Python-based interface for visualization and control
- Personal TutorData Science Instructorenero de 2022 - diciembre de 2023 (1 año y 11 meses)• • Delivered training on Python, ML, and AI concepts• • Designed hands-on projects involving real-world datasets• • Mentored students on ML workflows and best practices
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Formación
- Ph.D. in Computational MathematicsLahore University of Management Sciences (LUMS)2022Ph.D. in Computational Mathematics
- M.Phil. inUniversity of Engineering and Technology2018M.Phil. in
Certificados
- PythonData Science with Python2022