Team Lead and Senior Research Engineer specializing in Neuro-Symbolic AI. I build robust, enterprise-grade generative AI solutions that integrate symbolic reasoning and knowledge representation to enhance factual accuracy and overcome key LLM limitations.

At Fraunhofer, I refined a research-driven approach to innovation, ensuring each AI system design is guided by a clear research question and results in market-oriented solutions. My work includes: (1) developing enterprise knowledge graphs as a semantic layer for LLMs and agentic AI; (2) advancing deep learning on graphs, with a focus on scalable and time-aware Graph Foundation Models to enhance predictive AI for enterprise data; (3) employing knowledge graphs as agentic memory for continuous learning in LLM-based agents; (4) improving knowledge-enhanced generation with GraphRAG methods to reduce hallucinations; (5) establishing best practices and fine-tuning methods for open-weight LLMs; and (6) applying mechanistic interpretability to identify steering vectors for real-time monitoring and detection of harmful internal states in LLMs.

I lead the conceptualization, design, and development of AI conversational assistants and agentic automation systems. I hold a Master’s degree in Software Engineering and a Ph.D., which provide a strong foundation in project management, software architecture, and complex AI problem-solving. I believe inclusive, purpose-driven leadership is essential for fostering innovation. I mentor four PhD students and coach young AI talent in Bolivia, which helped me receive the Google AI Scholar Award in 2020.

Leading Roles

• Head of Knowledge-Enhanced Foundational Models for Data Analytics, at Fraunhofer FIT. (Current)
• Director of the Institute for Computational Intelligence, at Universidad Privada Boliviana. (Part-Time)
• Leader and Competency Area Expert Knowledge Graphs for Conversational AI at Fraunhofer IAIS, Dresden Lab. (Finished)
• Leader of the Semantic Data Management group at the Smart Data Analytics Group. (Finished)

Research Interests

• Neuro-Symbolic AI
• Enterprise Knowledge Graphs
• Graph Foundation Models
• Graph-based Retrieval-Augmented Generation
• Fine-Tuning LLMs
• Neuro-Symbolic Agentic AI
• Conversational AI
• Mechanic Interpretability for Foundation Models

CV in PDF: Two-Pager