Scholar
Noga Zaslavsky
Google Scholar ID: VdYiwjwAAAAJ
Assistant Professor, NYU
Citations & Impact
Citations
2,944
H-index
16
i10-index
19
Publications
20
Co-authors
27
list available
Publications
Resume (English only)
Academic Achievements
- Published multiple papers on topics such as efficient compression in semantic systems, rate-distortion theory and human pragmatic reasoning, the Information Bottleneck principle and neural networks, among others. Also received the ELSC Prize for Outstanding Publication.
Research Experience
- Assistant Professor in the Psychology Department at NYU
Background
- Research interests include understanding language, learning, and reasoning from first principles, building on ideas and methods from machine learning and information theory. Particularly interested in computational principles that explain how we use language to represent the environment; how this representation can be learned in humans and in artificial neural networks; how it interacts with other cognitive functions, such as perception, action, social reasoning, and decision making; and how it evolves over time and adapts to changing environments and social needs.
