New Conference Bridges Intellectual Barriers Across Machine Learning Applications

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Contact

JF Salazar

Institute for Data Engineering and Science

jsalazar@gatech.edu

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Summaries

Summary Sentence:

Dana Randall of Georgia Tech and Newell Washburn of Carnegie Mellon University led the formation of the new annual Machine Learning in Science and Engineering Conference.

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Media
  • Dana Randall addresses the audience of the new Machine Learning in Science and Engineering Conference, held at Carnegie Mellon University Dana Randall addresses the audience of the new Machine Learning in Science and Engineering Conference, held at Carnegie Mellon University
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The First Symposium on Machine Learning in Science and Engineering (MLSE’18), jointly organized by faculty from the Georgia Institute of Technology and Carnegie Mellon University, was held in Pittsburgh on June 6-8, 2018. Dana Randall, co-director of the Institute for Data Engineering and Science and Professor in the College of Computing at Georgia Tech, and Newell Washburn, Associate Professor in the Mellon College of Science at Carnegie Mellon University, served as co-chairs of the organizing committee. Randall and Washburn designed the new conference to bridge the diverse research areas that benefit from machine learning. Nearly 400 people attended, including over 40 from Georgia Tech. Among the attendees and session presenters were leaders in academia, government, and industry.

 

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Additional Information

Groups

Institute for Data Engineering and Science, College of Computing, School of Computational Science and Engineering, ML@GT, School of Computer Science, School of Interactive Computing

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Related Core Research Areas
Data Engineering and Science
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Keywords
machine learning, data science
Status
  • Created By: Jennifer Salazar
  • Workflow Status: Published
  • Created On: Jun 18, 2018 - 3:35pm
  • Last Updated: Jun 19, 2018 - 9:43am