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Interdisciplinary Data Science: Bridging Theory and Applications 

Conference

Interdisciplinary Data Science: Bridging Theory and Applications

when where NYUAD Campus who NYU Abu Dhabi Institute
By Invitation Interested scholars please contact nyuad.programs@nyu.edu

Interdisciplinary Data Science: Bridging Theory and Applications 

As data science transforms industries worldwide, the evolving landscape of the field is explored through a focus on integrating diverse data sources, from structured to unstructured, and leveraging emerging technologies. Key challenges such as data integration, ethical concerns, and privacy in data collection and usage are at the forefront of discussions. Interdisciplinary collaboration will drive exploration of the latest advancements in machine learning, AI, and their applications across areas like computational biology, natural language processing, and computer vision. Leading experts from academia and industry convene to foster robust dialogue to bridge the gap between theory and real-world solutions, covering topics from data ethics and privacy to machine learning and beyond.

Convened by
Aaron Kaufman, Assistant Professor of Political Science, NYUAD
Keith Ross, Professor of Computer Science, NYUAD
Hanan Salam, Assistant Professor of Computer Science, NYUAD
Pierre Youssef, Program Head of Mathematics; Associate Professor of Mathematics; Global Network Associate Professor of Mathematics, Courant Institute of Mathematical Sciences, NYUAD


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