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Zed Sevcikova-Sehyr is an Assistant Professor in Communication Sciences and Disorders in Crean College of Health and Behavioral Sciences at Chapman University. She earned her Ph.D. from University College London (UCL) in Cognitive, Perceptual, and Brain Sciences. Her research centers at the intersection of linguistics, cognition, and neuroscience. Dr. Sehyr’s research examines the neural underpinnings of visual language processing and reading. She investigates how our experiences shape visual and language networks and how these pathways adapt to deafness or sign language experience. Dr. Sehyr is a co-developer of ASL-LEX, a lexical database for American Sign Language. Her most recent work utilises computer-assisted analyses and machine learning to advance linguistic research.
Lee Kezar is a PhD Candidate in Computer Science at the University of Southern California and Graduate Research Assistant in the GLAMOR Lab under Dr. Jesse Thomason. Their research focuses on computational-linguistic methods for modeling American Sign Language (ASL) from the perspectives of phonology and lexical semantics, leveraging expert knowledge bases like ASL-LEX and free association data to improve automatic perception, comprehension, and production skills in ASL. Lee's previous work includes resources like the Sem-Lex Benchmark (91k isolated sign productions for over 3k distinct lexical items) and the ASL Knowledge Graph for building explainable, state-of-the-art models for recognizing and understanding rare and unseen signs. Starting August 2025, Lee will be joining the Center on Visual Language and Visual Learning (VL2) at Gallaudet University as a full-time postdoctoral researcher focusing on AI-powered collaborative learning tools for deaf and hard-of-hearing students in STEM.
Simon De Deyne is a cognitive scientist at the University of Melbourne, working at the Computational Cognitive Science Lab and the Complex Human Data Hub at the School of Psychological Sciences. He is interested in how the mind acquires and represents word meaning through experiences with the world and the use of language. His current work addresses questions about how connotative meaning varies across different languages and cultures, and how bilinguals learn and represent word meaning. One of his longest-running projects is the Small World of Words project. This community-drive project uses human word association data to map meaning in the mental lexicon across most of the worlds' languages.
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