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Noga Zaslavsky

BCS Fellow in Computation, MIT

About me

I’m a BCS Fellow in Computation at the MIT Department of Brain and Cognitive Sciences, where I collaborate with several labs including the Computational Psycholinguistics Lab, EvLab, TedLab, and the Computational Cognitive Science Group. My research aims to understand language and cognition from first principles, building on ideas and methods from machine learning and information theory. I’m particularly interested in finding computational principles that explain the ways in which human languages encode meaning; how this representation of meaning evolves and adapts to changing environments; how it is learned and implemented in the brain; and how it interacts with other cognitive functions, such as perception, decision making, and reasoning about others. I believe that such principles could advance our understanding of human cognition and guide the development of human-like artificial intelligence.

Before joining MIT, I did my PhD under the supervision of Naftali Tishby at the Center for Brain Sciences at the Hebrew University. I was also a visiting graduate student at UC Berkeley for two years, where I was affiliated with the LCLab, the Simons Institute, and ICSI. Before that, I was a research intern at IBM Project Debater. My BSc is in Computer Science and Cognitive Science from the Hebrew University.

Here’s my PhD Thesis and CV.

Selected Publications

All publications ≫

A Rate–Distortion view of human pragmatic reasoning

Zaslavsky, Hu, and Levy. arXiv, 2020.

Efficient compression in color naming and its evolution

Zaslavsky, Kemp, Regier and Tishby. PNAS, 2018.
ELSC Prize for Outstanding Publication

Toward human-like object naming in artificial neural systems

Eisape, Levy, Tenenbaum, and Zaslavsky. BAICS, ICLR 2020

Color naming reflects both perceptual structure and communicative need

Zaslavsky, Kemp, Tishby and Regier. topiCS, 2019.
CogSci Computational Modeling Prize

Deep learning and the Information Bottleneck principle

Tishby and Zaslavsky. IEEE ITW, 2015.

Teaching

  • Language in the Mind and Brain (9.S52), Guest Lecturer
    Topic: Artificial neural network models of language processing
    Department of Brain and Cognitive Sciences, MIT
    Spring 2021

  • NeuroBridges Summer School, TA
    Cluny, France
    October 2–12, 2018

  • Introduction to Machine Learning, TA
    School of Computer Science and Engineering, The Hebrew University
    Undergraduate and graduate level (~270 students)
    Spring 2016

  • Introduction to Information Processing and Learning, TA
    Center for Brain Sciences, The Hebrew University
    Graduate level
    Fall 2013, 2014, 2016