Hire the Best AI-Enhanced Medical Imaging Specialists

Top 1% Expert-Vetted Freelancer. I have a PhD in Computer Science (AI & Machine Learning) and I am a physician. I build custom AI systems with proprietary and public data, including creation of novel datasets and state-of-the-art models. * After a 30-minute to 1-hour initial meeting, I'll craft a clearly written report outlining a unique AI strategy for your project. * For long-term engagements, I implement AI solutions end-to-end, including data collection, data cleaning, novel model design, model implementation and training in Python, and iteration on the modeling and data strategy to achieve excellent performance. * One of my specialties is creating custom models for proprietary datasets, including images, videos, audio recordings, and domain-specific data. Book a 30-minute consultation with me to get immediate answers about your AI project: - How can you leverage AI in your organization? - What kind of AI do you need to solve a particular problem? - Should you use a model like ChatGPT/Claude or do you need a custom model? - What modeling strategy should you use? - How should you collect and annotate data? - How much data will you need? - How should you measure performance? After a consultation I’ll craft a clearly-written report outlining an AI strategy for your project. Specialties: Healthcare AI: I am an expert in healthcare AI, with a unique background that blends clinical understanding from my MD, deep technical expertise from my AI PhD, and business experience. I have completed 100+ engagements across medical specialties including radiology, dermatology, cardiology, mental health, family medicine, surgery, dentistry, physical therapy, women’s health, pediatrics, nutrition, and neurology. I have created datasets and custom models for diverse forms of biomedical data including x-rays, CTs, MRIs, clinical photographs, patient videos, medical audio, medical notes, EHR data, insurance claims, omics data, and more. Computer Vision: I create custom AI models for 2D images, 3D images, and videos on proprietary datasets. I am excited about projects from multiple industries including healthcare, manufacturing, automotive, and agriculture. I have extensive experience with classification, object detection, segmentation, and keypoint detection, to identify and localize abnormalities or features of interest. I developed the first machine learning model in the world to predict multiple abnormalities simultaneously from a CT scan. For a dermatology practice, I built the first CV model to predict Fitzpatrick skin type, pigmentation, redness, and wrinkle severity (mean accuracy 85%)—now a core model at Kesty AI. Artificial Intelligence R&D: I have led multiple AI research projects across industry and academia. I have developed novel AI methods, including HiResCAM, a convolutional neural network explanation method with mathematical guarantees. I have published original research across multiple areas of AI, including computer vision, natural language processing, explainable AI, expert systems, and applied AI. My research papers have been cited over 1,000 times. My healthcare AI blog Glass Box has over 700,000 readers from 185 countries. Natural Language Processing (NLP): I have a deep understanding of large language models (LLMs) like Claude, Gemini, ChatGPT, and Llama. I have leveraged Transformers and other NLP techniques for numerous applications, including customized chatbots, medical note generation, and structured information extraction. Advising Entrepreneurs: Before focusing on AI consulting, I spent seven years as the founder of a health AI startup. I led my previous company from concept to deployed B2B SaaS product serving medical practices. Our AI history-taking assistant and AI scribe saved clinicians 2+ hours daily. I managed engineering teams of 5-10 (60+ contributors), secured two U.S. patents, and raised competitive grant funding. I enjoy working with entrepreneurs and discussing pitch decks, fundraising, customer discovery, designing an MVP, and evaluating the ROI of an AI product. If you’d like to talk with me about your AI project, please feel free to send me a message or book a consultation using the link on my profile.

I don't just wrap APIs. I build the algorithms underneath them. I'm an AI engineer with 8+ years across quantum-simulation ML, fintech, EdTech, and clinical research — and an MS in Theoretical Chemistry. I train transformers from scratch, invent production retrieval algorithms, and ship AI inside a $660M global Clinical Research Organization where "almost right" doesn't pass. If your last contractor handed you a LangChain demo and called it a product, we should talk. 🔹 What Sets Me Apart ✅ Inventor of the Fox-Search Algorithm — a hybrid vector + graph retrieval method I built for asymmetric query/target search (short questions against 200-page clinical protocols). Pairs a trainable ~0.3B-parameter BERT-tier model with FAISS where pure embedding search collapses. ✅ I train my own models — fine-tuning a 0.3B encoder is normal work for me, not outsourced to a Hugging Face checkpoint. ✅ Scientific rigor — career started predicting atomistic energies and forces for ab-initio-quality molecular simulations. Same measurable-accuracy discipline now applied to LLM systems. ✅ Founder of edup.ai — autonomous grading of handwritten STEM work: computer vision + handwriting recognition + math reasoning + rubric generation, end-to-end. ✅ Production AI in a regulated industry — currently building document intelligence at Worldwide Clinical Trials (2,900+ employees, 52 countries). 🔹 Core Capabilities ▪ RAG done right — hybrid vector+graph retrieval, FAISS at scale, embedding fine-tuning, evaluation harnesses that actually measure quality. If your RAG hallucinates, I can usually tell you why within an hour. ▪ LLM engineering — self-optimizing prompt primitives that improve over time, constrained generation, tool calling, structured outputs. GPT-4o, Claude, Llama, Mistral. ▪ Document intelligence — production parsers for PDF, DOCX, XLSX with section-aware XML processing; semantic search that finds alternative phrasings of previously-approved language. ▪ Custom model training — BERT-tier encoders, LoRA/QLoRA fine-tuning, domain-adaptive pretraining. ▪ Computer vision — handwriting recognition, OCR, ViT/CLIP, math symbol understanding. ▪ High-performance engineering — C++ on the hot path, FastAPI services, real async Python. 🔹 Tech Stack • Languages: Python, C++, JavaScript / TypeScript • ML / DL: PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, NumPy, Pandas • LLM: OpenAI GPT-4o / o-series, Claude, Llama, Mistral, LangChain, LangGraph, LlamaIndex, LoRA / QLoRA, RAG, function calling • Retrieval: FAISS, Pinecone, Weaviate, Chroma, Qdrant, custom hybrid vector+graph search • Vision: OpenCV, PyTorch Vision, ViT, CLIP, OCR, handwriting recognition • Backend: FastAPI, Flask, Docker, REST, WebSockets, async Python • Frontend: Svelte 4, React • Enterprise: Microsoft Entra ID, SharePoint, Azure, AWS, GCP 🔹 Shipped Projects ▪ Fox-Search RAG — hybrid vector+graph retrieval running in production for clinical document Q&A, outperforming pure embedding baselines on long-form documents. ▪ Self-optimizing prompt infrastructure — reusable LLM primitives that improve over time without manual prompt-tuning. ▪ Document intelligence backend — parses Excel/DOCX/PDF with section-level XML comprehension; powers cross-document semantic search. ▪ RFI automation for clinical trials — ingests Excel-based Requests for Information and routes them through automated answer pipelines. ▪ edup.ai — 7-stage autonomous grading pipeline for handwritten math, from photo capture to gradebook. Live at edup.ai. ▪ Neural network potentials — ML approximations of quantum-mechanical energy surfaces for molecular simulation (same problem class as DeepMind's AlphaFold lineage). 🔹 How I Work ✔ I scope honestly — if your problem doesn't need AI, I'll tell you. ✔ I write the evaluation code before the model code. Anyone can demo; I deliver something you can measure. ✔ I ship in weekly increments — no six-week silence followed by a "big reveal." ✔ I write maintainable code your team can own after I'm gone. 🔹 Best Fit For Teams stuck on "our RAG kinda works but hallucinates" • Document-heavy domains (clinical, legal, scientific, financial, EdTech) • Startups needing a senior engineer who can architect, train, deploy, and operate • Anyone whose roadmap requires training models, not just prompting them. Send me your problem — not your solution. I'll reply within 24 hours with an honest read on whether I'm the right engineer for it.

I’m a Data & Medical Annotation Specialist with proven experience in: Medical imaging (X-rays, CT, MRI) NLP & clinical text annotation High-volume AI training datasets. My top priority is to deliver precise, accurate annotations with strict quality controls. Follow your guidelines precisely (or help refine them if needed) Handle large datasets with fast turnaround, ensure data confidentiality and compliance standards. A pro in image and video annotation (bounding boxes, segmentation, keypoints), medical imaging annotation (X-rays, CT scans, MRIs), text annotation (NER, classification, sentiment analysis), data labeling and quality assurance, and healthcare data tagging and clinical data structuring.

👨🏻‍⚕️ About Me - Surgeon building medical visuals and software 🧠🫀 - Winner of xAI Healthcare Hackathon 2026 🏆 - Developer of OpenHuman Atlas & Healthview OS 👨🏻‍💻 🛠️ What I can help with - Medical Illustrations 2D/3D - Biomedical Animations 2D/3D - Surgical Simulations/Trainers - Anatomical 3D Models/Prints - Healthcare AI applications - Medical VR/AR - DICOM & Medical Imaging Workflows 💻 Technical Expertise - Adobe Illustrator / Affinity - Blender - Three.js / WebGL / WebGPU - Medical Imaging DICOM - AI & Machine Learning - Typescript / React / React Native - Python / Django / FastAPI - Computer Vision & AR - Cloud Infrastructure 💡 Why Clients Choose Us? Unlike most developers and artists we are able to combine: - Clinical medical expertise - Software engineering experience - Medical visualization skills 🌎 Industries Served - Healthcare Startups - Hospitals & Clinics - Medical Device Companies - Universities & Research Groups - Surgical Training Organizations - Digital Health Platforms

I help researchers, startups, and businesses turn AI ideas into working MVPs and scalable products through machine learning development, AI model integration, AI/Backend Engineer, Workflow Automations and research-backed implementation & writing support. 🏆 Top Rated | 100% Job Success | about $10K+ Earned | 40+ Completed Upwork Jobs Whether you need to validate an AI idea, integrate an existing model, reproduce research code, or improve an ML pipeline, I can help move your project from concept to a reliable implementation. 🏆 MVPs to Scalable Products | AI Research & Development | Research Support-Asistance 🧠 Deep Learning | Machine Learning | ML Model Training & Fine-Tuning | APIs | LLMs 🌟 2D/3D Vision | Sensors and Medical Data | GitHub & Hugging Face Code Reproduction 🧠 Classification, Regression, Time Series, Forecasting, Detection & Recognition WHAT I CAN HELP YOU BUILD: ✅ AI & Machine Learning MVPs, SaaS, Startup Predictive models, prototypes, backend APIs, AI model integration, and deployment-ready workflows. ✅ Deep Learning & Computer Vision Solutions Image classification, object detection, segmentation, anomaly detection, medical imaging, and 2D/3D vision pipelines. ✅ LLM, RAG & AI Integration OpenAI API integration, LangChain workflows, ChromaDB knowledge bases, retrieval pipelines, and AI-powered applications. ✅ Model Training & Fine-Tuning Data preparation, training pipelines, experimentation, evaluation, optimization, and reproducible implementation. ✅ Research Support & Code Reproduction Research-paper implementation, GitHub and Hugging Face code reproduction, benchmarking, ablation studies, experiment support, and technical reporting. ✅ Medical & Scientific Data Solutions Research-focused machine learning workflows for structured, image, and multimodal datasets. ✅ Time-Series & Sensor Data Solutions Forecasting, anomaly detection, signal processing, predictive modelling, and machine learning workflows for sensor, IoT, and sequential datasets. CORE TOOLS: Python | PyTorch | TensorFlow/Keras | Scikit-learn | OpenCV | Vercel AI | Github | Hugging Face | Flask | FastAPI | OpenAI API | Claude Code | LangChain | ChromaDB | Next.js | SQL | Docker | R/Rstudio | Matlab PyTorch | TensorFlow | Deep Learning | Neural Networks | Machine Learning | Machine Learning Model | Large Language Model | RAG | AI Model Development | AI Model Integration | Data Engineering | biostatistics | Statistical Analysis | Data Engineering | Image processing | Signal Processing WHAT YOU CAN EXPECT ✓ Clear communication and realistic scoping ✓ Clean, reproducible code and documentation ✓ Research-backed implementation decisions ✓ Flexible collaboration across USA, Europe, UK, and Australia time zones I also support Python/R Data Science Data Analysis, NLP, LLMs, OpenAI API, RAG chatbots, Clinical Data, Data Engineering, scraping tasks projects and build ETL pipelines as well as setup databases. Share your idea, dataset, existing codebase, or research paper, and I will help define the most practical path from prototype to implementation.

Transforming complex data and novel research concepts into production-ready AI solutions. With over 8 years of experience at the intersection of AI research and enterprise-level engineering, I specialize in tackling challenges that require more than off-the-shelf solutions. I architect and build robust, scalable systems that turn raw data—from satellite feeds to real-time video—into actionable intelligence. Here's What I Build: 🛰️ Advanced Geospatial & Vision Systems: I develop end-to-end computer vision pipelines for complex environments. My experience includes: • Smart City Solutions: Building traffic monitoring and management systems using real-time object detection and tracking (as demonstrated in the Urban Guard project). • 3D Mapping & LiDAR Processing: Creating high-precision 3D models from LiDAR data for vehicle and drone tracking (showcased in the LiDARView system). • Automated Sports Analytics: Designing systems to track player and ball movements for real-time statistical analysis (like the Trackzella project). 💡 Custom Data & Annotation Platforms: I understand that great AI starts with great data. I build the foundational tools necessary for high-performance models: • Synthetic Data Generation: Engineering platforms to create diverse, realistic datasets for robust model training (proven with the Imagate platform). • Multi-Format Annotation: Developing collaborative tools for labeling images, video, and text to power specialized AI models (like the Anna annotation platform). ☁️ Scalable MLOps & Deployment: A model is only valuable when it's in production. I ensure your AI solutions are reliable and efficient using modern DevOps practices, including containerization (Docker, Kubernetes) and deployment across major cloud platforms (AWS, Azure, GCP). Key Technology Stack: • Languages & Frameworks: Python, PyTorch, TensorFlow, OpenCV • MLOps & Cloud: Docker, Kubernetes, AWS (SageMaker, S3), GCP (Vertex AI), Azure • Data & CV: LiDAR, Satellite Imagery Processing, Pandas, NumPy, Scikit-learn Are you looking to solve a complex R&D problem or build a first-of-its-kind AI application? Let's connect for a brief consultation to discuss your vision.