Main Conference Keynotes

We are delighted to announce that the esteemed speakers listed below have graciously accepted our invitation to deliver keynote speeches at the main conference of COLING 2024:

More information about the keynote speaches will be updated soon.

Katrin Erk

Bio:

Katrin Erk is a Professor of Linguistics and Computer Science at the University of Texas at Austin. She earned her Ph.D. from Saarland University in Germany in 2002, focusing on tree description languages and ellipsis. Her research expertise lies in computational linguistics, particularly in semantics. She specializes in developing distributed, flexible approaches to describing word meaning and integrating them with representations at the sentence or discourse level. Her work includes studying flexible representations of word meaning constrained by context and exploring frameworks that draw inferences based on sentence structure and word meanings. She also investigates narrative schemas and their influence on word meaning and inference. In October 2024, it was announced that she will join the University of Massachusetts Amherst in September 2025, holding a joint position in the Department of Linguistics and the Manning College of Information and Computer Sciences. Throughout her career, she has received several awards and honors, including a CSLI Fellowship at Stanford in 2017 and a Google Faculty Research Award in 2018.

Emmanuel Dupoux

Bio:

Emmanuel Dupoux is a Professor of Cognitive Psychology at the École des Hautes Études en Sciences Sociales (EHESS) in Paris. He earned his Ph.D. in Cognitive Psychology from EHESS in 1989, focusing on the mechanisms and representations that enable infants to acquire language and become cognitively functional within their culture. His research expertise lies in cognitive development, psycholinguistics, language acquisition, cognitive modeling, and machine learning. He specializes in studying early language acquisition, phonological ‘deafnesses’ in speech perception, and the development of social cognition. He also investigates how machine learning and artificial intelligence can provide quantitative models of processing and learning in infants. Throughout his career, he has received several awards and honors, including an Advanced ERC grant and the organization of the Zero Resource Speech Challenge (2015, 2017, 2019) and the Intuitive Physics Benchmark (2019).

Partha Talukdar

Bio:

Partha Talukdar is a Senior Staff Research Scientist at Google Research India and an Associate Professor (on leave) in the Department of Computational and Data Sciences at the Indian Institute of Science (IISc), Bangalore. He earned his Ph.D. in Computer and Information Science from the University of Pennsylvania in 2010, focusing on graph-based weakly supervised methods for information extraction and integration. His research expertise encompasses Natural Language Processing (NLP), Machine Learning, and Knowledge Graphs, with a particular interest in large-scale learning and inference. He has contributed significantly to the development of inclusive AI and language technologies, aiming to make information access more universal. Throughout his career, he has received several awards and honors, including an Outstanding Paper Award at ACL 2019 and the ACM India Early Career Researcher Award in 2022. He is also the founder of KENOME, an enterprise knowledge graph company dedicated to helping organizations make sense of unstructured data.