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🚀 I help companies turn engineering and sensor data into practical AI solutions — from idea to working MVP. I’m Dr. Muhammad Zohaib Sarwar, a PhD engineer from NTNU, Norway, with hands-on experience in machine learning, signal processing, predictive maintenance, smart sensing, and industrial analytics. My work combines strong research depth with practical implementation, so clients get solutions that are not only technically sound, but also usable in real projects. I have worked on real-world engineering problems involving condition monitoring, railway systems, sensor integration, time-series analysis, and data-driven diagnostics. My background spans AI, embedded sensing, cloud-based analytics, and engineering workflows, allowing me to bridge raw data, algorithms, and deployable solutions. 💡 What I Can Help You With * Build AI/ML MVPs in as little as 30 days for well-defined use cases * Predictive maintenance and anomaly detection systems * Signal processing and time-series analytics * Vibration and condition monitoring solutions * Sensor fusion, IoT, and edge-data workflows * Deep learning models for engineering applications * Dashboards, reporting tools, and cloud-based analytics * Research consulting, algorithm development, and technical documentation 🧠 My Expertise * Machine learning and deep learning * Predictive modeling and fault diagnostics * Signal processing and feature engineering * Time-series analysis * Smart sensing and embedded systems * IoT and sensor data pipelines * Technical data visualization and reporting * Engineering-focused AI workflows ⚙️ Tools & Technologies * Programming: Python, MATLAB, C/C++ * AI/ML: TensorFlow, PyTorch, Scikit-learn * Cloud & DevOps: Azure, AWS, Docker, Git, Power BI * Engineering Tools: COMSOL, ABAQUS, LabVIEW * Hardware: Arduino, Raspberry Pi, FPGA, smart sensors ✅ Why Clients Hire Me I do more than build models. I help clients define the problem clearly, structure the data, choose the right technical approach, and develop a solution that creates real value. If you need someone who can: * Understand complex technical systems * Work with noisy real-world data * Build reliable AI workflows * Deliver a useful prototype or MVP fast then I can help. 🤝 Let’s build an intelligent solution that is practical, reliable, and ready for real use.

I’m a Computer Science Engineer with a strong foundation in software, data, and automation. What I do best: * Build AI-powered data extraction pipelines that turn messy, unstructured data such as PDFs, websites, and scanned documents into clean, structured datasets * Develop custom web scraping and automation systems for reliable, ongoing data collection * Build full-stack web applications and internal tools for testing, logging, automation, and production workflows My experience spans software development, automation, data engineering, and AI. I enjoy taking real-world problems and turning them into clean, reliable, and maintainable software solutions. I care about building systems that work reliably — whether that means a scraper that keeps running, a data pipeline that handles information accurately, or software that remains easy to maintain as it grows. I’m always interested in solving real-world problems with software, automation, AI, and data.

I'm a certified Microsoft Data Analyst with a solid foundation in data science, machine learning, and software development. Holding a Master's in Data Science from NMBU, Norway, I bring hands-on experience in analyzing complex datasets, building predictive models, and optimizing data processes to enhance operational efficiency. Key Projects and Achievements: Developed advanced machine learning models and data pipelines for environmental monitoring at NMBU. Created dynamic dashboards for aquaculture and sales analysis, providing actionable insights for decision-makers. Enhanced a Property Management System with the Zoho Business Suite, automating workflows and improving data management. Designed and delivered custom WordPress websites, achieving 100% client satisfaction. My expertise spans Python, MATLAB, SQL, Power BI, and advanced data visualization tools such as Plotly and PLS Toolbox. As a Microsoft Certified Data Analyst, I am skilled in turning data into actionable insights, driving better decision-making for your business. Let’s collaborate to transform your data into growth opportunities!

🏆 𝐓𝐨𝐩 𝐑𝐚𝐭𝐞𝐝 𝐀𝐈/𝐌𝐋 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 | 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈, 𝐋𝐋𝐌 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 & 𝐀𝐈 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 🤖 𝐏𝐡𝐃 𝐢𝐧 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 | 𝐀𝐈/𝐌𝐋 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 | 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈, 𝐋𝐋𝐌𝐬 & 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 📱 𝐅𝐮𝐥𝐥-𝐒𝐭𝐚𝐜𝐤 𝐀𝐈 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 | 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐖𝐞𝐛 & 𝐌𝐨𝐛𝐢𝐥𝐞 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 | 𝐂𝐥𝐨𝐮𝐝 & 𝐒𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 I build production-ready AI systems, intelligent web and mobile applications, and scalable digital products combining 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈, 𝐋𝐋𝐌𝐬, 𝐦𝐚𝐜𝐡𝐢𝐧𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠, 𝐝𝐚𝐭𝐚 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠, 𝐛𝐚𝐜𝐤𝐞𝐧𝐝 𝐬𝐲𝐬𝐭𝐞𝐦𝐬, 𝐚𝐧𝐝 𝐜𝐥𝐨𝐮𝐝 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬. With a PhD in Machine Learning and hands-on experience building real-world products, I help startups and enterprises transform complex ideas, workflows, and data into reliable AI-powered solutions. My experience includes AI SaaS platforms, RAG systems, AI agents, intelligent 𝐰𝐞𝐛 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬, 𝐦𝐨𝐛𝐢𝐥𝐞 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬, 𝐝𝐨𝐜𝐮𝐦𝐞𝐧𝐭 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞, 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐌𝐋 𝐦𝐨𝐝𝐞𝐥𝐬, 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬, 𝐚𝐧𝐝 𝐝𝐚𝐭𝐚 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬 from architecture and development to integrations, deployment, and production optimization. 🤖 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 & 𝐋𝐋𝐌 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 ➜ AI agents using 𝐋𝐚𝐧𝐠𝐆𝐫𝐚𝐩𝐡, 𝐋𝐚𝐧𝐠𝐂𝐡𝐚𝐢𝐧, 𝐎𝐩𝐞𝐧𝐀𝐈, 𝐂𝐥𝐚𝐮𝐝𝐞, 𝐆𝐞𝐦𝐢𝐧𝐢, 𝐋𝐋𝐚𝐌𝐀, 𝐚𝐧𝐝 𝐜𝐮𝐬𝐭𝐨𝐦 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬 ➜ Agentic AI workflows with tools, memory, reasoning, planning, and automated execution ➜ AI copilots, assistants, and business workflow automation systems ➜ Multi-agent systems integrated with APIs, databases, and enterprise platforms ➜ LLM applications with structured outputs, function calling, MCP workflows, evaluation, and validation 📚 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈, 𝐑𝐀𝐆 & 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 ➜ Production RAG systems using embeddings, vector databases, semantic search, and retrieval optimization ➜ Enterprise knowledge assistants built over private documents and business data ➜ Document intelligence platforms for extraction, summarization, classification, and analysis ➜ Hybrid retrieval, reranking, context optimization, and hallucination reduction techniques ➜ LLM evaluation, prompt engineering, and response quality improvement 📊 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 & 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 ➜ Predictive modelling, classification, regression, clustering, anomaly detection, and recommendation systems ➜ Forecasting, ranking models, personalization, and business intelligence solutions ➜ NLP solutions including information extraction, text classification, sentiment analysis, and topic modelling ➜ Deep learning applications using PyTorch, TensorFlow, and Scikit-learn ➜ Data analysis, feature engineering, experimentation, statistical modelling, and model evaluation 📱 𝐌𝐨𝐛𝐢𝐥𝐞 & 𝐅𝐮𝐥𝐥-𝐒𝐭𝐚𝐜𝐤 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 ➜ Native iOS and Android applications using Swift, SwiftUI, and Kotlin ➜ Cross-platform applications using Flutter and React Native ➜ AI-powered mobile apps with chat, voice, payments, authentication, maps, notifications, and real-time features ➜ Full-stack development from frontend architecture to backend APIs and cloud deployment ☁️ 𝐁𝐚𝐜𝐤𝐞𝐧𝐝, 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠, 𝐂𝐥𝐨𝐮𝐝 & 𝐌𝐋𝐎𝐩𝐬 ➜ Backend systems using Python, FastAPI, Django, Flask, and Node.js ➜ REST APIs, WebSockets, asynchronous processing, Celery, Redis, and scalable workflows ➜ ETL pipelines, data processing, normalization, analytics systems, and data platforms ➜ Database design using 𝐏𝐨𝐬𝐭𝐠𝐫𝐞𝐒𝐐𝐋, 𝐌𝐲𝐒𝐐𝐋, 𝐌𝐨𝐧𝐠𝐨𝐃𝐁, 𝐅𝐢𝐫𝐞𝐛𝐚𝐬𝐞, 𝐚𝐧𝐝 𝐯𝐞𝐜𝐭𝐨𝐫 𝐝𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬 ➜ Cloud infrastructure using AWS, Azure, GCP, Docker, Kubernetes, CI/CD, monitoring, and security practices ➜ MLOps workflows including model deployment, versioning, experiment tracking, and production monitoring 🔬 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 & 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 ➜ PhD-level expertise in 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, 𝐍𝐋𝐏, 𝐚𝐧𝐝 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 ➜ Supervised and unsupervised learning approaches ➜ Recommendation systems, forecasting, intelligent ranking, and model validation ➜ Statistical analysis, experimental design, causal analysis, and advanced analytics ➜ Technical documentation, research reporting, and data-driven insights I combine machine learning research, AI engineering, software architecture, and product development to build reliable AI solutions that move beyond prototypes into real-world production. Whether you need an AI application, RAG system, AI agent, automation workflow, predictive ML solution, data platform, or intelligent mobile product, I can help take your idea from concept and experimentation to a scalable, production-ready solution.

PhD in Machine Learning and Computational Immunology. 3 years biotech industry experience with generative models of biological sequences. Freelance projects in RAG, conversational AI applications, data analysis.

Bioinformatics Specialist & Data Scientist with Full-stack Developer and Platform Engineering Expertise PhD in Bioinformatics with a robust foundation in designing and optimizing data pipelines, ETL processes, and integrating large-scale biological datasets. Over 6 years of professional experience in developing end-to-end data processing workflows, building and deploying scalable machine learning models, and implementing statistical models. Proficient in architecting and automating data platforms, ensuring efficient data flow and real-time processing for high-throughput genomics, proteomics, and other omics data. Expertise in creating full-stack solutions that transform complex biological research into actionable insights, leveraging advanced data transformation, analysis, and visualization techniques. Skilled in bridging the gap between bioinformatics and software development, delivering scalable, reliable, and maintainable data solutions. Technical Skills: • Programming Languages: Python (7+ years) • Data Processing: Pandas, Numpy, and other Python-based data manipulation tools • Databases: SQL (PostgreSQL, MySQL), NoSQL (MongoDB), Vector (Milvus) • Data Pipelines: ETL processes, Snakemake • Machine Learning: PyTorch, Scikit-learn, model deployment • Data Visualization: Matplotlib, Seaborn, Plotly, interactive dashboards Bioinformatics Tools: • Programming Libraries: BioPython • Genetic and Variant Analysis: PLINK, GATK (Genome Analysis Toolkit), variant calling • Sequence Alignment: MUSCLE • Genomic Studies: GWAS tools Molecular Modeling Tools: • Molecular Dynamics: AMBER, GROMACS • Structural Visualization: PyMOL • Docking: AutoDock, VINA, DiffDock, etc. • Protein Structure Prediction: AlphaFold • Applications: Molecular dynamics simulations, structural bioinformatics Extensive experience integrating a wide range of bioinformatics databases across various domains into pipelines and custom software: Genomic Databases, e.g, NCBI (GenBank, RefSeq), Ensembl, ClinVar • Protein and Structural Databases, e.g. UniProt, PDB, InterPro, Pfam • Pathway and Functional Databases, e.g. KEGG • Chemical and Drug Databases, e.g., ZINC, PubChem, ChemDB, DrugBank