Cognition, Narrative, and Culture Laboratory (Cognac Lab)

How does culture shape our understanding of the world? What makes stories so powerful? How can computation shed light on these questions? Culture surrounds us and affects our behavior and thoughts in ways large and small.  Narratives are everywhere, and we know of no culture or society that does not use it as a fundamental form of communication for activities as diverse as explanation, education, and entertainment. The Cognac lab investigates these and related questions from a computational and cognitive point of view, and the unifying interest of researchers in the lab is the computational modeling of culture, narrative, language, and their interaction with cognition. For the purpose of scope we construe culture in a broad sense, as any set of shared knowledge structures that mold the behavior of a group of people. Researchers in the lab conduct inter-disciplinary research spanning artificial intelligence, computational linguistics, cognitive science, and the digital humanities, and use techniques drawn from machine learning, natural language processing, linguistic annotation, knowledge representation, computational inference to tackle key questions in this space, including: How is shared knowledge—commonsense and cultural—represented in language and narrative?  How do people and how can machines extract this shared knowledge from data? And how do we apply these insights to achieve advances in machine intelligence, educational practice, health and medicine, social science theory, and the humanities?  For recent work, current and former students, and more details generally, visit the lab homepage at https://cognac.cs.fiu.edu.

 

LATEST NEWS

The Cognac Lab is now an internal partner with CREST CACHE at FIU. Deya Banisakher and Joshua Eisenberg (Ph.D. candidates at Cognac) are working on building a system to enhance literature search in the environmental sciences and hydrology domains. This project is an interdisciplinary collaboration with the Distributed Multimedia Information Systems Laboratory, represented by its director, Dr. Shu-Ching Chen, and Maria Presa – a CS Ph.D. Student – and the Department of Earth and Environment represented by the Hydrology department chair, Rene Price, and Kalli Unthank – a Hydrology Ph.D. student.

W. Victor H. Yarlott completed Summer Internship at IBM’s Thomas J. Watson Research Center. International Business Machines Corporation (commonly referred to as IBM) is an American multinational technology company headquartered in Armonk, New York, United States, with operations in over 170 countries. During his internship, he developed software that used capabilities from IBM’s Watson, natural language processing techniques, and machine learning to better match candidates and job descriptions.

Victor H. Yarlott visited the HLF as one of the young researchers who were invited from a pool of applicants. The Heidelberg Laureate Forum is an annual event created for the purpose of bringing young researchers from the fields of Mathematics and Computer Science together with some of the most distinguished researchers in those fields: Abel, Fields, and Turing laureates. The forum is by invite only — students submit an application and from this pool, only 200 young researchers are selected by the Scientific Committee of the Heidelberg Laureate Forum.

Deya Banisakher has been selected to visit the renowned Oak Ridge National Laboratory (ORNL) in Oak Ridge, Tennessee as a summer research intern. He is working under the mentorship of Supriya Chinthavali in the Computational Data Analytics Research group which falls within the Computer Science and Mathematics Division. At ORNL, Deya is working on cutting-edge national-scale technologies and projects including the URBAN NET and Eagle-I projects which target the identification and detection of vulnerable nodes in the nation’s critical infrastructure networks. He will be applying his knowledge in NLP and ML towards his work at ORNL as well as learn and develop new technical skills including visualization and graph analytics.