Applied Scientist & AI Researcher — LLMs, RAG, NLP, interpretability, multimodal AI.
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I work at the intersection of research and production AI, building systems that are both effective and measurable.
My focus is on LLM evaluation, Retrieval-Augmented Generation, model interpretability, and multimodal pipelines — with a particular interest in making AI systems understandable, not just functional.
Currently at Leonardo Labs as an AI Researcher & Applied Scientist. Previously at IBM and Google Summer of Code 2024 (HumanAI).
Leonardo Labs — AI Researcher & AI Applied Scientist
Agentic AI safety, RAG evaluation, and interpretability workflows for assessing model transparency and robustness.
IBM — Data Scientist & Applied Scientist
Multimodal retrieval, anomaly detection, summarization, geospatial intelligence, and production NLP systems.
Google Summer of Code 2024 — HumanAI — Open Source Contributor
Open-source NLP research on large-scale Dark Web analysis, including topic extraction, clustering validation, and multimodal labeling workflows.