Daniel Preoțiuc-Pietro is the engineering manager of NLP Platforms in the AI Group at Bloomberg, based in New York City, that develops centralized libraries, tools and models that power NLP products and applications developed by Bloomberg. His group's work spans topics in NLP, LLMs and Information Retrieval, including LLM post-training, custom retrieval models, reinforcement learning, automatic evaluation using LLMs, model distillation, frameworks for RAG applications, information extraction or semantic parsing.

His research interests are in the wider areas of Natural Language Processing, Large Language Models and Computational Social Science where he has authored over 50 top-tier publications. His recent research theme is introducing and developing new task setups, applications and resources for NLP tasks inspired by industry use cases. His personal research interests are on understanding the pragmatic, social and temporal aspects of text, especially from social media, with applications to domains such as Psychology, Law, Political Science and Journalism. His past original research was featured extensively in popular press including the Washington Post, BBC or New Scientist.

He is the co-founder and co-organizer of the Natural Legal Language Processing (NLLP) workshop series at *ACL conferences, was the Industry Track Chair at EMNLP 2024 and regularly serves in the senior program committee at major NLP conferences.

Prior to joining Bloomberg nine years ago, he was a postdoctoral research fellow at the University of Pennsylvania working on the World Well-Being Project in the Positive Psychology Center. Daniel completed his PhD in the Natural Language Processing Group at the University of Sheffield and was a research associate for the TrendMiner EU project.