My PhD thesis at Leibniz University Hannover focuses on hybrid methods for Information Extraction (IE), combining Semantic Web technologies with Neural Network (NN) approaches. The goal is to bridge the gap between neural representations and semantic entities, enhancing the accuracy and interpretability of IE systems in NLP. As an MSCA fellow, I contributed to the CLEOPATRA ITN project, focusing on Event-centric Cross-lingual Information Processing, which involved developing methods to process and analyze digital information across languages.
Additionally, my involvement in the d-E-mand project, a German national initiative aimed at predicting energy supply needs for electric vehicle users amidst rising charging demands, has allowed me to apply AI in predictive analytics and sustainable energy solutions. These experiences underscore my commitment to leveraging AI to tackle real-world challenges and drive societal progress.