Manuel Luciano is a Software Engineer and Systems Administrator specializing in applied AI, backend systems, and full-stack software engineering. His work focuses on translating advances in artificial intelligence into practical software that is reliable, scalable, and accessible to researchers and end users.
Manuel is one of the founding developers of iChatBio, an agentic system that translates advances in large language models and AI agents into a hosted application for the biodiversity research community. The platform enables researchers to explore biodiversity data and scientific resources through natural language while serving as a foundation for evaluating and deploying emerging agent capabilities in real-world scientific workflows. His work on iChatBio has contributed to multiple peer-reviewed publications describing the system and its applications.
At the University of Florida, Manuel has contributed to the design, deployment, and maintenance of research computing infrastructure while driving development of modern web applications, APIs, authentication systems, containerized services, and distributed software platforms. His experience spans user interface development, backend engineering, Linux administration, networking, security, and high-availability systems, enabling him to build AI applications with a full-stack and infrastructure-first perspective. His current interests include AI agent orchestration, planning and execution frameworks, retrieval-augmented systems, observability, and architectures that combine autonomous reasoning with deterministic software components to improve reliability, scalability, and trustworthiness.
Related Publications:
– iChatBio: an Extensible Agentic System for Scientific Exploration and Integration of Open Biodiversity Data (2026) – Accepted at eScience 2026, DOI forthcoming.
– AI-Assisted Exploration, Curation, and Extension of Biodiversity Data Using iChatBio (2025) – https://doi.org/10.3897/biss.9.181968
– Integrating Large Language Models and the iDigBio Portal for Conversational Data Exploration and Retrieval (2024) – https://doi.org/10.3897/biss.8.142696