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Cornell Tech’s academic environment encourages tight integration across disciplines, couples fundamental research with practice, and supports societal and commercial ventures alongside research and education.

In addition to world-class academic work, a distinguishing characteristic of our research is that it engages deeply with external communities, organizations, and industry to address real-world problems and contexts that amplify the direct societal and commercial impact of our research.

Research Events

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Seminar @ Cornell Tech: Demba Ba

"Deeply-Sparse Signal Representations, Artificial Neural Networks and Hierarchical Processing in the Brain": Two important problems in neuroscience are to understand 1) how the brain represents sensory signals hierarchically and 2) how populations of neurons encode stimuli and how this encoding is related to behavior. My talk will focus on the tools I have developed to answer the first question.
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Seminar @ Cornell Tech: Yaron Singer

"Algorithms in the Era of Machine Learning: An Inconvenient Truth": The traditional approach in algorithm design assumes that there is an underlying objective that is known to the algorithm designer and the focus is on efficiently optimizing that objective. In many applications however, the objectives we aim to optimize are not known but rather learned from data. So what are the guarantees of the algorithms we develop and teach when the input is learned from data?
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Noah Smith headshot

LMSS @ Cornell Tech: Noah Smith (University of Washington)

Noah Smith is a Professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington, as well as a Senior Research Manager at the Allen Institute for Artificial Intelligence. Previously, he was an Associate Professor of Language Technologies and Machine Learning in the School of Computer Science at Carnegie Mellon University.
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In The News

Media Highlights

Cornell Sun

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Cornell Chronicle

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Wired

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