Abstract: At Bloomberg, our data scientists and engineers work on a diverse set of data science problems -- ranging from machine learning, natural language processing, dialog systems, information extraction, knowledge graphs, question answering, and table understanding. Due to the unique confluence of challenges we face at scale in terms of the data, precision, recall, and latency requirements of the global capital markets, we must build innovative solutions to rapidly deliver information to our clients across finance, business, government and philanthropy. These innovations take the shape of numerous publications in peer-reviewed conferences and journals, collaborations with academics and students, as well as partnerships with fellow researchers in other companies.
In this talk, Dr. Anju Kambadur, Head of AI Engineering at Bloomberg, will provide an overview of his group's research activities over the past year across 5 key problem sets. He will then dive deeper into a recent paper he and his colleagues published at SIGIR ‘18 entitled “Weakly-Supervised Contextualization Of Knowledge Graph Facts,” which details a new neural fact contextualization method (NFCM) that can be used in knowledge graph fact contextualization tasks.
Bio: Dr. Prabhanjan (Anju) Kambadur heads the AI Engineering group at Bloomberg. Anju leads a group of 100+ researchers and engineers who build solutions for Bloomberg clients in the areas of machine learning, natural language processing (NLP) and natural language understanding, information extraction, knowledge graphs, question answering, and table understanding. Previously, Anju was a research staff member in the Business Analytics and Mathematical Sciences Department at IBM Research’s Thomas J. Watson Research Center, where he worked on problems in machine learning, such as matrix sketching, genome-wide association studies, temporal causal modeling, and high performance computing. He received his Ph.D from Indiana University. Anju has published peer-reviewed articles in the fields of high performance computing, machine learning, and natural language processing.