News & Announcements Archive


Linguistics Program Ranked as #1 by NRC

In it's 2010 report "A Data-Based Assessment of Research-Doctorate Programs in the United States", the National Research Council ranked the Johns Hopkins Department of Cognitive Science as one of the top departments in the country in which to study linguistics.


Dr. Barbara Landau Featured in JHU’s A&S Magazine

Dr. Barbara Landau Featured in JHU’s A&S Magazine
After a decade of research, cognitive scientist Barbara Landau is mapping new territory in Williams syndrome—a rare condition that has long baffled scientists. Click to read the article in Arts & Sciences magazine.


Information Theory in Computer Vision and Pattern Recognition

Information Theory in Computer Vision and Pattern Recognition
This book explores and introduces the latter elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented. Interesting connections between information theory principles when applied to different problems are highlighted, seeking a comprehensive research roadmap. The result is a novel tool both for CVPR and machine learning researchers, and contributes to a cross-fertilization of both areas.


Barbara Landau Named a 2009 Guggenheim Fellow

Barbara Landau Named a 2009 Guggenheim Fellow
Dr. Landau's scientific research addresses the nature of human spatial understanding, the nature of language, and the relationship between the two during early development and in adulthood. The Guggenheim Fellowship will allow her to spend a full year writing a book on the nature of spatial knowledge and language in people with Williams syndrome.


Optimality Theory: Constraint Interaction in Generative Grammar

Optimality Theory: Constraint Interaction in Generative Grammar
This book is the final version of the widely-circulated 1993 Technical Report that introduces a conception of grammar in which well-formedness is defined as optimality with respect to a ranked set of universal constraints.


Dysgraphia: Cognitive Processes, Remediation, and Neural Substrates: A Special Issue of Aphasiology

Dysgraphia: Cognitive Processes, Remediation, and Neural Substrates: A Special Issue of Aphasiology
Written language permeates virtually every aspect of modern society and literacy plays a central role in determining the economic and personal success of the individual. However, while the importance of written language comprehension (reading) is generally acknowledged, the significance of written language expression (spelling) is often overlooked. As a result, there has been relatively little […]


Perception, Cognition, and Language: Essays in Honor of Henry and Lila Gleitman

Perception, Cognition, and Language: Essays in Honor of Henry and Lila Gleitman
These original empirical research essays in the psychology of perception, cognition, and language were written in honor of Henry and Lila Gleitman, two of the most prominent psychologists of our time. The essays range across fields foundational to cognitive science, including perception, attention, memory, and language, using formal, experimental, and neuroscientific approaches to issues of […]


Learnability in Optimality Theory

Learnability in Optimality Theory
Highlighting the close relationship between linguistic explanation and learnability, Bruce Tesar and Paul Smolensky examine the implications of Optimality Theory (OT) for language learnability.


Mathematical Perspectives on Neural Networks

Mathematical Perspectives on Neural Networks
Recent years have seen an explosion of new mathematical results on learning and processing in neural networks. This body of results rests on a breadth of mathematical background which even few specialists possess. In a format intermediate between a textbook and a collection of research articles, this book has been assembled to present a sample of these results, and to fill in the necessary background, in such areas as computability theory, computational complexity theory, the theory of analog computation, stochastic processes, dynamical systems, control theory, time-series analysis, Bayesian analysis, regularization theory, information theory, computational learning theory, and mathematical statistics.