Daniel Preoțiuc-Pietro is a senior research scientist and team lead in the AI Group at Bloomberg, New York City, where he works on analytics and information extraction from news, social media and financial documents.
His research interests are in the areas of Natural Language Processing and Computational Social Science and are focused on understanding the social and temporal aspects of text, especially from social media, with applications in domains such as Psychology, Law, Political Science and Journalism. This research was featured extensively in popular press. He is a co-organizer of the Natural Legal Langauge Processing (NLLP) workshop series.
Previously, he was a postdoctoral research fellow at the University of Pennsylvania and worked on the World Well-Being Project in the Positive Psychology Center.
Daniel completed his PhD studies on temporal models for social media as part of the Natural Language Processing Research Group at the University of Sheffield. During his time in Sheffield, he was also a part-time research associate for the TrendMiner EU FP7 project where he worked on predicting real world outcomes such as political voting intention and uncovering spatio-temporal patterns in large user-generated content.