My work is dedicated to advancing our foundational understanding of human language. How do we understand what we hear and read? How are we able to convert thoughts into meaningful utterances that others understand? And how do we acquire the knowledge that makes all this possible? My research program sits at the intersection of artificial intelligence, psychology, and linguistics, and tackles these questions through theory, computationally implemented models of language, psychological experimentation, analysis of large linguistic datasets, and more.
My research combines Natural Language Processing (NLP), Computational Linguistics and Cognitive Science. I currently study what eye movements during reading can reveal about the linguistic knowledge and cognitive state of the reader, and how such signal can be used to improve NLP. Other related interests include multilingualism, linguistic typology, treebanking, and grounded language acquisition.
I am interested in how people use language to share their thoughts and feelings. I am particularly fascinated by the context-sensitivity of language understanding, issues of vagueness, and how people learn from linguistic messages. In my research, I use computational models and behavioral experiments and enjoy thinking up novel data analytic methods.
My research focuses on the nature, origins, and utility of abstract linguistic knowledge in children's early development, and how such knowledge grows to support adult language processing. In my research I use a combination of computational models from NLP, corpus studies, web-based experiments, and in-lab experiments. My postdoc is split with the Bergelson Lab at Duke University, where I conduct behavioral experiments with young children (12 - 36 months).
My research consists of two mutually reinforcing goals: (1) understanding the structure and development of human linguistic knowledge by using high-performance computational language models as candidate models of human language processing and acquisition, and (2) operationalizing insights from these models and the human language processor alike to build and evaluate better language models. As such, I use tools from neuroscience and psycholinguistics to evaluate and constrain language models.
I'm interested in linguistic meaning: how it is acquired by the child, how it is structured in the mind of the speaker, and how it is worked out in the mind of the listener. I study these questions through different computational case studies, combining data and methods from linguistics, psychology, artificial intelligence, and neuroscience. You can find much more about my work on my website, where I also blog about language, cognitive science, and philosophy, among other things.
My research focuses on cognitive models of how language is perceived and acquired, with the goal of connecting these model to social and cultural processes to explain language structure. In particular, I am interested in how properties such as discreteness and compositionality arise in grounded communication systems that evolve over time. I pursue these questions by conducting behavioral experiments that mimic cultural evolutionary processes, and by building probabilistic models of the observed linguistic behavior.
My research develops computational models of how humans resolve ambiguity in language understanding, with the goal of building better systems of artificial intelligence. I am also interested in how brains and machines represent linguistic meaning and structure. I am supported by an NSF Graduate Research Fellowship and the NIH Program in Computationally-Enabled Integrative Neuroscience.
I am interested in which cognitive processes underlie human language production and understanding: How do speakers plan what to say and how do listeners predict and process upcoming utterances? Current research projects I am involved in investigate how accurately different artificial neural network models can predict language processing in the human brain, which neural resources are recruited for (non-)linguistic conceptual processing, and how well computational models can capture semantic plausibility. Furthermore, I investigate conversational restrictions that underlie human discourse with the aim of building computational models that abide by them as well.
I’m interested in the cognitive basis of human language. My current work combines behavioral experiments and computational models to investigate the relevance of linguistic knowledge in learning, reasoning, and judgment.
I am a fourth year in the Department of Linguistics at Harvard, with affiliations at the Computational Psycholinguistics Lab at MIT and the Meaning and the Modality Lab at Harvard. I employ methods from psycholinguistics to analyze Natural Language Processing systems, investigating how these techniques can be used to build more robust NLP models and how model performance bears on questions central to linguistic theory and acquisition. I employ a broad range of experimental approaches, from controlled syntactic tests, to broad statistical analysis of human behavior such as gaze duration during reading. I also work on recursive models of semantic and pragmatic reasoning, with one current project investigating how speakers and listeners coordinate on a shared common ground.
I am a senior in the Brain and Cognitive Sciences department here at MIT. I’m currently working with Veronica Boyce on an experimental psycholinguistics project that involves studying human sentence processing using A-Maze. I have broad interests in both cognitive science and neuroscience. I also enjoy reading, writing, and baking!
I’m a rising sophomore studying computer science, and I’m interested in machine learning and natural language processing. I’m currently working with Tiwa and CJ on gamifying the collection of cloze completions to provide training data for cognitively plausible AI.
I am a undergraduate freshman, planning on majoring in Computation and Cognition (6-9) due to an interest in the field of artificial intelligence. Currently, I am working on a project using eye-tracking experiments to correlate language comprehension and eye movements.
I’m an incoming undergraduate sophomore studying math with computer science, but I’m also interested in linguistics. My current project tackles some of the challenges involved with collecting cloze completions at scale.
Along with MH Tessler, I currently focus on using iterated transmission experiments to study how people use language to share their thoughts. Past research has included probing off-the-shelf word embeddings to see how they can be used to differentiate between semantic relations.
I’m a rising sophomore studying computer science. I also have an interest in linguistics and natural language processing. I am working with Ethan Wilcox on comparing human processing of language against the performance of NLP models.
I’m a senior studying EECS (6-2) and Neuroscience (9). I am interested in the intersection between these two fields, and developing more biologically plausible systems of AI. My current project explores how humans resolve ambiguity in communication using models of pragmatic reasoning.
|PhD students||Masters students||Undergraduates||Postdocs||Research Associates||Visitors|
|Klinton Bicknell||Anna Sinelnikova||Suhas Arehalli||Helena Aparicio||Veronica Boyce||Fuyun Wu|
|Rebecca Colavin||K. Michael Brooks||Richard Futrell||Tristan Thrush||Kasia Hitczenko|
|Gabriel Doyle||Wednesday Bushong||Victoria Fossum||Kentaro Nakatani|
|Anubha Kothari||Hannah Campbell||Titus von der Malsburg||Yanan Sheng|
|Emily Morgan||Bonnie Chinh||Eva Wittenberg||Reuben Cohn-Gordon|
|Bozena Pajak||Abhishek Goyal||Aixiu An|
|Y. Albert Park||Jake Prasad||Polina Tsvilodub|
|Till Poppels||Agatha Ventura|
|Nathaniel Smith||Melodie Yen|
|Meilin Zhan||Silvia Cho|
|Beining Jenny Zhang|