Intelligent search engine in the nuclear field

Within the intricate domain of decommissioning nuclear power plants, engineers face the daunting task of sifting through vast repositories of data to extract critical information. Recognizing the need for an intelligent solution, I embarked on a project to develop a specialized search engine tailored to this unique challenge.

The project’s inception involved close collaboration with engineering teams. To ensure the search engine’s efficacy, I played a pivotal role in validating the ontology, a crucial component governing the system’s semantic structure. This required a deep understanding of both the nuclear domain and data science principles.

A significant aspect of this initiative was managing a dedicated team tasked with annotating data. This annotated data served as the foundation for training a sophisticated Natural Language Processing (NLP) model, specifically BERT (Bidirectional Encoder Representations from Transformers). This model was meticulously fine-tuned to comprehend the intricate language and context of nuclear data.

In addition to these responsibilities, I took on the role of mentoring and training newcomers who joined the project. This encompassed imparting knowledge about the project’s intricacies, best practices in data annotation, and the nuances of working within the nuclear semantic domain.

The project’s impact has been profound. Engineers now have a powerful tool at their disposal, streamlining the process of information retrieval amid the complexities of nuclear decommissioning. This endeavor epitomizes my ability to bridge the gap between technical domains, from engineering to data science, and underscores my adeptness at managing teams and fostering knowledge transfer.

By spearheading this project, I have not only demonstrated my technical acumen but also showcased my commitment to enhancing operational efficiency through innovative solutions and collaborative teamwork.