Muskan Shivnani is a student at the University of Illinois at Urbana Champaign.

Collaborating on AI-enabled healthcare and document retrieval projects at UIUC and Carle Illinois College of Medicine. No other specific current technical projects are mentioned.

I'm an MS Computer Engineering student at NYU (GPA 4.0) with hands-on experience building production AI systems. I've architected GenAI platforms serving 200+ concurrent users, built RAG pipelines that shipped as flagship products, and contributed to open-source computer vision research. My work spans MLOps, LLM fine-tuning, and cloud-native deployment, bridging the gap between research and real-world AI products.

I'm interested in production AI systems, agentic workflows, and the infrastructure that makes LLMs reliable at scale, observability, evaluation pipelines, and runtime safety. I'm also drawn to healthcare AI, particularly responsible deployment of diagnostic models. I'm looking to connect with founders, researchers, and engineers working at the intersection of ML and real products - the teams where closing the research-to-deployment gap is the core challenge.

I'm currently building agentguard, an open-source Python library for runtime safety in agentic AI systems, budget enforcement, tool-call verification via a Bayesian engine, and circuit breakers for multi-agent workflows. I'm also working on observability infrastructure for NYU's GenAI platform, including automated quality checks via Kubernetes CronJobs with Grafana Cloud reporting.