Daniel Cotrim, master's and bachelor's degree in Computer Science from the Pontifical Catholic University of Rio Grande do Sul (PUCRS), is a graph md data science specialist with a focus on knowledge engineering and artificial intelligence (AI) applied to the development of complex digital ecosystems, through graph md schema modeling and the development of super apps for knowledge synthesis with the Neo4j enterprise integrate to a high-performance cloud platform and graphRAG with LLM ai.
He completed two years of his PhD in Computational Neuroscience at the PUCRS School of Medicine, where he worked as a researcher on R&D projects at TECNOPUC related to the development of AI technology in the healthcare area.
As a data scientist at TOTVS, he participated in the development and implementation of the Electronic Patient Record at HCor in São Paulo.
A Java developer since the age of 15 and a Graph Data Science Specialist with 27 years of experience in the market, implementing solutions in neo4j Aura DS, spring data, spring data, and web development of high-performance cloud platforms.
He has been working with GDS (Graph Data Science) applied to the development of Healthcare complex digital ecosystems for at least 13 years.
Working as an architect of complex digital ecosystems in important national and international projects, it is observed that the benefits of the sophisticated techniques used were success factors for the delivery of the proposed solutions. Specialized in modeling complex knowledge synthesis bases, having developed the 10-year monitoring database for patients in the Epilepsy Surgery Program at Hospital São Lucas da PUCRS, during his doctorate period, and later, the architecture of the complex diagnostic support ecosystem at HCor in São Paulo.
Throughout his career, he has served as technology leader for the AI and Architecture teams. It is observed that these two areas are strongly interconnected, and the final result intended with the AI Application is only possible through a modern and efficient architecture. Currently, relational databases are unable to perform some fundamental queries for AI solutions. In this sense, it is important to think of alternative and innovative solutions, such as neo4j spring data, which integrates the modeling of persistent entities provided by Java in projects with the development methodology using graph md schemes.
The project management process gains added value with agile methodologies, but it must be supported by activity and people management techniques that address Knowledge Management, Design Thinking, UX, and traceability. Contact with the universe of developing complex digital ecosystems contributed significantly to the success of his professional career.
He worked for ten years as an undergraduate and graduate professor at the university. This experience of several years with a significant number of people from different professional profiles allowed him to acquire fundamental skills in the search for encouraging people to give their best in daily challenges. Some of the technologies most recently used in Graph Data Science projects, developed in the last 3 years: development of the super app graph.md with java spring data neo4j; and the creation of complex digital ecosystems using OPM (Object Process Methodology) within spring data and graphRag LLM ai.
