Thomas H.

I am an AI/ML & Data Engineer with 8 years of experience and PhD-trained Bioinformatics Scientist. I specializes in developing production-quality AI systems, ETL/Data Pipeline modeling, deep learning, NLP/LLM workflows, and digitally using AI for pathology. As an experienced hands-on builder of end-to-end AI systems for pharmaceutical research and development (R&D), cancer research, and computational pathology, I have developed AI systems that integrate raw data into production ML application systems from the data pipeline through to deployment, monitoring, and statistical analysis for non-technical stakeholders. I have expertise in both cutting-edge research in the area of machine learning, as well as extensive practical engineering experience with scalable and high reliability ML application systems in production. 📌 Recent Project Experience ✨ Developed ML pipeline to process heterogeneous structured and unstructured data • Pfizer DSDR – Drug Safety AI Pipeline: Built production ML/ETL workflows integrating structured + unstructured data, with API deployment, validation, monitoring, and alerts. ✨ Trained and deployed deep learning networks that can analyze large biomedical data sets • FNLCR – Multi-Modal Pathology Toolkit: Operationalized HALO H&E/mIF whole-slide analysis and million-cell/pixel-scale metadata curation. ✨ Deployed and monitored AI algorithms in production environments with API, monitoring, validation, and cross-functional collaboration • AbbVie Precision Medicine – WSI Modality Prediction: Trained MIL deep learning models with attention heatmaps and Flask API visualization. 💡 What I Can Help You With ✅ Production ML Systems • End-to-end ML pipeline design and implementation • Model training, evaluation, deployment, and monitoring • API-based ML inference systems • Model reliability, robustness testing, and performance tracking ✅ ETL & Data Engineering for AI • Automated ETL pipelines for structured and unstructured datasets • Data validation, error handling, metadata management, and QA workflows • Integration of SQL databases, CSV files, imaging data, and distributed repositories • Scalable data curation pipelines for ML-ready datasets ✅ Deep Learning & Computer Vision • PyTorch/Keras model development • Vision transformers, foundation models, CNNs, MIL models, segmentation models • Image classification, prediction, feature extraction, and attention visualization • Large-scale image analysis for gigapixel whole-slide images ✅ Digital Pathology & Biomedical AI • Whole-slide image analysis for H&E, IHC, and multiplex immunofluorescence • Weakly supervised multi-instance learning for histopathology • Spatial omics, single-cell analysis, graph-based modeling, and image-derived biomarkers • HALO-based image analysis workflows and algorithmic scoring exports ✅ NLP/LLM & AI Workflow Integration • LLM-powered data processing and knowledge extraction workflows • Biomedical text/data integration • AI-assisted research pipelines and automation • Foundation model evaluation and applied AI system development ⚙ Technical Expertise Languages: Python(Advanced), SQL(PostgreSQL, MS SQL Server), R, Go AI/ML/DL: PyTorch, Keras, Statistical ML, Computer vision, MIL, Transformers, DNN, CNN NLP/LLM: RAG, LangChain, LangGraph LlamaIndex, OpenAI API, Anthropic Claude, Hugging Face, AutoGPT, AgentGPT Data/ETL: CSV, Structured/unstructured data integration, Metadata pipelines, Pandas, Numpy, Data validation Frontend: React, Next.js, TypeScript, HTML5, CSS3, Tailwind CSS, Material-UI Backend: Node.js, Express.js, GraphQL Databases: MongoDB, MySQL, Redis, Firebase Deployment: Flask, REST APIs, Linux/Unix, Git, Production ML workflows E-Commerce: Shopify (Liquid, Apps, Plus), WordPress, WooCommerce, Elementor DevOps: AWS, Docker, CI/CD, Nginx, PM2 Automation: n8n, Make, Zapier, Temporal, Apache Airflow CRM/Marketing: HubSpot, GoHighLevel, Salesforce, ActiveCampaign Data Visualization: Power BI, Looker Studio, Matplotlib, Plotly Domains: Digital pathology, Big Data, Statistical testing, Spatial Omics, Biomedical AI, Pharmaceutical R&D, Cancer research 🤝 Why Work With Me? ✓ PhD-level AI/ML expertise with real-world production experience ✓ Strong ability to bridge research, engineering, and domain science ✓ Experienced in working with pharmaceutical, biomedical, and cross-functional teams ✓ Clean, scalable, well-documented code and reproducible workflows ✓ Strong communication and attention to detail for complex technical projects I am particularly suited to taking on clients who require more than a typical ML developer, specifically those involved with highly complex biomedical data, multi-dimensional imaging, production ML systems and AI workflows that are built from research through to deployment. If you need assistance with creating an effective AI pipeline, deploying an ML model, developing a CV system, or analyzing digital pathology data, I would be glad to work with you on your project.