Two Faculty Spearhead New ML/AI Conferences

Po-Ling Loh

Po-Ling Loh was the one of the key people who created the Midwest Machine Learning Symposium. The symposium aims to convene regional machine learning researchers for stimulating discussions and debates, to foster cross-institutional collaboration, and to showcase the collective talent of machine learning researchers at all career stages. It will be held at the Logan Center at University of Chicago on June 6-7, 2018. The MMLS was founded in 2017 and Prof. Loh is this year’s chair. More information:
http://midwest-ml.org/2018/


Dimitris Papailiopoulos

Dimitris Papailiopoulos co-chaired the first SysML Conference in Stanford, California February 15-16, 2018. SysML is a new conference targeting research at the intersection of systems and machine learning. The conference aimed to elicit new connections amongst these fields, including identifying best practices and design principles for learning systems, as well as developing novel learning methods and theory tailored to practical machine learning workflows. More information:   http://www.sysml.cc/2018/index.html

 

Computer-generated database of diffusion values is shared online

Dane Morgan
Dane Morgan
Professor
Materials Science & Engineering

University of Wisconsin—Madison engineers recently used powerful computers to quickly and accurately develop the world’s largest computed database of information about an important materials-mixing process called diffusion.

Led by Dane Morgan, Harvey D. Spangler Professor in Materials Science and Engineering at UW–Madison, the researchers published details of their advance July 19 in the journal Scientific Data. They also made the entire database freely available online, along with an online application to easily search and visualize the data and a utility called the Materials Simulation Toolkit (MAST) for engineers across the globe to access and use in their own materials design applications.

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