Monika Chavan
I’m Monika Chavan, an AI and data professional based in Erlangen, where I’ve spent the last 8+ years building practical solutions across AI/ML, data engineering, and software development.
About
I’m Monika Chavan, an AI and data professional based in Erlangen, where I’ve spent the last 8+ years building practical solutions across AI/ML, data engineering, and software development. I enjoy turning complex problems into reliable pipelines—especially when it comes to LLM-powered applications like RAG, embeddings, and agentic workflows—and I’m motivated by research challenges that demand both rigor and real-world impact.
Right now, I’m working at Siemens Healthineers, focusing on enterprise-grade GenAI systems that reduce information discovery and analysis effort while scaling to large knowledge sources. Alongside my industry work, I’ve been pursuing an M.Sc. in Artificial Intelligence and continue to deepen my expertise through research in secure and trustworthy AI, as well as hands-on projects spanning computer vision, multimodal learning, and self-supervised representation learning.
- 7 years' experience
- Joined September 2026
Industry experience
- Healthcare
- Software & Internet
- Professional Services
- Computers & Electronics
Work experience· 8 roles
Conducted research in IT and computer security, contributing to secure and trustworthy AI research through a research seminar. Supported academic research through technical analysis, experimentation, and evaluation of security-related challenges.
Designed and developed enterprise AI solutions leveraging LLMs, RAG, embeddings, and agentic workflows, reducing information discovery and analysis effort by up to 87%. Built production-oriented AI pipelines integrating cloud AI services, enterprise data, search systems, and external knowledge sources, supporting 100K+ knowledge sources and reducing search effort by 72%. Focused on end-to-end pipeline design with practical evaluation and deployment considerations.
Engineered real-time data flows and ETL pipelines for a healthcare SaaS platform serving 2,000+ hospitals using NiFi, Airflow, Spark, Python, and SQL. Designed data models and integration workflows for drug diversion analytics, optimizing pipelines and automating processing across healthcare data workflows.
Education
Certifications and awards· 15
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