Hire the Best Stanford CoreNLP Specialists

Top 1% Expert-Vetted Freelancer. I have a PhD in Computer Science (AI & Machine Learning) and I am a physician. Prior to becoming a consultant I spent 7 years as the Founder and CEO of an AI startup. Today, 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 AI engagements across radiology, dermatology, cardiology, mental health, family medicine, surgery, dentistry, physical therapy, women’s health, pediatrics, nutrition, neurology, and more. 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, and omics data. I understand clinical workflows and the unique stakeholder landscape of healthcare, which informs my technical work and business advising in this space. Computer Vision: I create custom AI models for 2D images, 3D images, and videos on proprietary datasets, when you need to exceed the performance of off-the-shelf AI. 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. 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) and have completed AI projects leveraging Claude, Gemini, ChatGPT, and Llama. I’ve built customized chatbots, medical note generation, and structured information extraction. I can customize LLMs to your company’s needs through prompt engineering, RAG, or fine-tuning. 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 help organizations turn complex data into accurate forecasts, predictive models, and actionable insights using machine learning, statistics, and applied mathematics. I currently work as a Research Scientist at the University of Michigan and hold a dual PhD in Mechanical Engineering and Computational Mathematics. My expertise includes time-series forecasting, statistical modeling, machine learning, predictive analytics, signal processing, uncertainty quantification, and decision-support systems. I specialize in challenging datasets where noise, missing information, uncertainty, or complex system behavior make standard approaches unreliable. What I can help you with: • Time-series forecasting and predictive analytics • Machine learning model development and evaluation • Statistical analysis and uncertainty quantification • Predictive modeling for business, research, and engineering decisions • Classification on difficult or noisy datasets • Feature engineering, data preprocessing, and model validation • Model debugging and performance improvement • End-to-end ML pipelines in Python • Signal processing and biomedical data analysis • Simulation, surrogate modeling, and optimization workflows • Decision-support models for real-world systems Experience Highlights: • Developed machine-learning models for biomedical signal classification that improved accuracy by 15% over conventional feature-engineering approaches. • Developed custom statistical and machine-learning algorithms for identifying patterns, data drift, and behavioral changes in noisy, uncertain, and stochastic datasets. • Built predictive models and surrogate modeling systems that replaced computationally expensive simulations, enabling rapid design evaluation and optimization. • Conducted research in forecasting, stochastic systems, machine learning, and scientific computing, resulting in peer-reviewed publications, open-source software contributions, and conference presentations. Tools & Technologies: Python, Pandas, NumPy, SciPy, scikit-learn, XGBoost, TensorFlow, PyTorch, SQL, Jupyter, Matplotlib, Statistical Modeling, Machine Learning, Time-Series Forecasting, Predictive Modeling, Signal Processing, Data Analysis, Feature Engineering, Model Validation, Optimization, Scientific Computing. My Approach: Most machine-learning problems do not fail because of the model itself - they fail because the data is noisy, incomplete, poorly structured, or difficult to interpret. My focus is on building reliable models, validating assumptions, reducing overfitting, and delivering results that are useful for real-world decisions. If you're working on forecasting, predictive modeling, machine learning, statistical analysis, model validation, or complex data challenges, I’d be happy to discuss how I can help.

I design and build production-grade security systems for companies that need to secure cloud infrastructure, pass audits, and operate in regulated environments. Most teams don’t have a security tool problem. They have an architecture, integration, and execution problem. That’s where I come in. What I Do I help startups and enterprise teams move from: ❌ fragmented tools and partial controls ❌ audit delays and failing security reviews ❌ reactive fixes and security debt → to ✅ engineered, scalable security architecture ✅ audit-ready, continuously compliant environments ✅ automated, integrated security operations Core Expertise Cloud Security & Cryptography • Multi-cloud security architecture (AWS, Azure, GCP) • TLS PKI systems with automated certificate lifecycle (IaC + CI/CD) • Encryption architecture (CMEK, KMS, data masking, data protection) • Cryptographic hardening aligned with FIPS and modern standards • DNS security, network isolation, and zero-trust patterns Identity & Access Management • SSO (SAML, OIDC), enterprise identity federation • RBAC and least-privilege system design at scale • SCIM provisioning and identity lifecycle automation • Integration with enterprise IdPs (PingFederate, Azure AD, Okta) • Cross-account and multi-environment access control Compliance & Audit Readiness • SOC 2, ISO 27001, PCI DSS, HIPAA, FedRAMP-aligned environments • End-to-end delivery: gap assessment → implementation → audit support • Control design, remediation, and evidence automation (Vanta, Drata, custom pipelines) • Continuous compliance monitoring vs point-in-time audits • Closing audit findings fast (not just identifying them) Security Engineering & Incident Response • CI/CD security (SAST, DAST, IaC scanning, secret management) • Vulnerability management with automated remediation workflows • Cloud misconfiguration detection (CIS benchmarks, runtime analysis) • Secure system design across infrastructure and application layers • Incident response, forensics support, and system hardening AI-Driven Security I don’t just integrate tools — I design security platforms. I have built and architected multi-agent AI-driven cybersecurity systems combining: • Cloud security analysis (AWS integrations, IAM analysis, misconfiguration detection) • Offensive security (recon, exploitation, privilege escalation simulation) • Vulnerability management (SAST, DAST, fuzzing, CI/CD integration) • SOC automation (SIEM/SOAR integrations, alert enrichment, playbooks) • Forensics and incident investigation workflows • Compliance reporting mapped to frameworks (SOC 2, ISO 27001, PCI, HIPAA) Key capabilities: • Multi-agent orchestration and communication • Automated remediation workflows • MITRE ATT&CK mapping and executive reporting • API-driven integrations across security tooling ecosystem • Role-based access for security, DevOps, and compliance teams This enables: → Continuous security instead of periodic assessments → 80% reduction in manual security effort → Faster audit readiness and real-time visibility How I Work • Engineering-first — I build and implement, not just advise • Work directly in production systems (cloud, identity, pipelines) • Design for real audit constraints, not theoretical compliance • Fast execution, clear communication, and ownership Typical Clients • SaaS companies preparing for SOC 2 / ISO 27001 / HIPAA • Cloud-native platforms handling sensitive or regulated data • Startups entering enterprise sales with security blockers • Organizations with fragmented security tools that don’t work together Important I’m not a fit for checklist-based security or surface-level audits. If you need: • real security architecture • working implementations • systems that pass audits and hold up in production - we’ll work well together.

I help businesses, healthcare teams, researchers, and startups turn complex AI ideas into reliable software products. I am a research-driven AI Solutions Engineer and Python backend developer with a Master’s in Neuroscience and 6 years of experience building AI-powered applications, machine learning workflows, and research-focused software systems. My work sits at the intersection of artificial intelligence, backend engineering, data processing, and scientific problem-solving. My strongest value is not just writing code. I help define the right technical approach, design the system architecture, build the backend, integrate AI models, and deliver software that is practical, maintainable, and ready for real users. My core expertise includes: - Python backend development - Generative AI application development - Machine learning and data workflows - Scikit-learn, TensorFlow, Keras, NumPy, Pandas, SciPy - Speech-to-text systems using Whisper AI - SQL and SQLite database design - GPU-accelerated AI inference - Research automation and scientific computing - Healthcare AI and clinical workflow tools - Desktop AI applications and internal business tools One of my key projects is VoxChart, a clinical speech-to-text dictation application built with Whisper AI, Python, PyAudio, SQLite, tkinter, and PyInstaller. It supports offline AI transcription, medical terminology correction, autosave, Epic EHR export support, crash reporting, and a Windows installer pipeline. This project reflects the kind of work I do best: turning advanced AI capability into a clean, usable tool that solves a real workflow problem. I also have hands-on experience in computational neuroscience, reinforcement learning, and scientific modeling, including a spinal cord arm control model using Python, TensorFlow/Keras, OpenSim, and DDPG. This gives me a stronger analytical foundation than a typical software developer and allows me to work confidently on complex, data-heavy, research-driven, or AI-first projects. I can help you with: - Building AI-powered SaaS tools, MVPs, and internal platforms - Developing Python backends for AI applications - Creating custom ML models and data pipelines - Integrating OpenAI, Whisper, or other AI systems into your workflow - Automating manual business or research processes - Designing databases, APIs, and AI-assisted backend logic - Building healthcare, clinical, or research technology solutions Clients should work with me when they need someone who can think deeply, communicate clearly, and build carefully. I care about clean architecture, accurate implementation, strong documentation, and software that remains useful after delivery. If you need an AI solution that is more than a prototype, I can help you design it, build it, and make it dependable.

I specialize in securing AI and Model Context Protocol products, leveraging 25 years of experience in IT and security. My work focuses on identifying vulnerabilities that often disrupt deployment, ensuring that AI systems function as intended without compromising safety. I have developed commercial security solutions, such as the MCP Scanner, which detects prompt-injection risks and unsafe configurations. Additionally, I offer consulting services through Vectorbreak, utilizing my unique Five Surfaces methodology to audit and enhance AI deployments. If you need a reliable partner to navigate the complexities of AI security and ensure robust performance, let’s connect and discuss how I can help your team achieve secure, effective solutions.