name: Atishay Jain
role: AI Engineer
specialty: [Agentic AI, RAG, Multimodal ML, Computer Vision]
education: MS Artificial Intelligence @ Illinois Tech
gpa: 4.0 / 4.0
prior_degree: Integrated M.Tech in AI @ VIT Bhopal
recognition: IEEE IS3C 2023 — Best Paper Award
iGEM 2025 — Silver Medal (IIT Chicago)
certifications: [HIPAA]
location: Chicago, IL
contact: ai.atishay@gmail.com |
🧠 Two Master's in Artificial Intelligence 🔬 Peer-reviewed researcher · IEEE Best Paper 🛡️ Designing AI for regulated domains — healthcare, manufacturing 🚀 Specialty: turning agentic + RAG systems into reliable, evaluated, production-grade software 🎯 Open to AI / ML / LLM Engineering roles |
"I gravitate to the seam where an LLM meets a real workflow —
where a hallucination has a cost, and the system has to keep running after the demo crowd leaves."
| 🩺 | 🧬 | 🧩 | 📈 |
|---|---|---|---|
| Clinical Copilots | Applied AI for Bio | Agentic Orchestration | Multimodal Forecasting |
| FHIR-backed LLM workflows with confirmation gates & audit logs | iGEM IIT Chicago — ML pipelines for synthetic biology | MCP servers + LangGraph tool routing | Time-series × sentiment × XAI |
🧠 AI / ML / Deep Learning
🤖 Agentic AI & LLM Stack
⚙️ Backend · Cloud · MLOps
💻 Languages & Tools
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Clinical Copilot for OpenMRS Conversational chart review, intake, and orders over OpenMRS REST + FHIR2. Every write is confirmation-gated; destructive actions require typed
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IEEE IS3C 2023 — Best Paper Award 🏆 Mask R-CNN (X101-FPN) scaled across 44,339 images and 7 defect classes for non-destructive industrial inspection. Trained with Detectron2 + SAHI; aggressive augmentation tripled effective training data.
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Big-data ML + Cloud LLM alerts End-to-end Spark ML pipeline forecasting hourly congestion on Minneapolis I-94, with Claude 3 Haiku generating plain-language traveler alerts. Three classifiers benchmarked under 3-fold CV.
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Time-series × Sentiment × XAI Multimodal forecasting framework fusing price signals with news + social sentiment, paired with explainability over model decisions and a full backtesting suite.
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Tool-augmented agent orchestration Model Context Protocol orchestration enabling LLM tool use over structured schemas via LangGraph ReAct agents — across 2 MCP servers (stdio + streamable HTTP).
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Local-first document Q&A FastAPI service for retrieval-augmented Q&A over user documents, using LangChain + Ollama for fully local inference with vector embeddings — privacy-first, no cloud dependency.
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IEEE IS3C 2023 |
iGEM 2025 |
4.0 / 4.0 GPA |
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HIPAA Certified |
3× Letters of |
International Research |
Open to AI / ML / LLM engineering roles, research collaborations, and conversations
about agentic systems, multimodal AI, and reliability in production AI.
⭐ Crafted in Chicago · @atishay2411