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Air Force-backed center to make machine learning more independent, predictable, secure

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Artificial intelligence has become so smart and commonplace that most people accept computer-generated restaurant recommendations or movie suggestions without blinking an eye. Underneath the virtual surface, however, much remains mysterious in the realm of machine learning, where systems attempt to mimic the remarkable way humans learn. Machine learning capabilities aren't yet up to the task of handling highly complex, rapidly changing or uncertain environments, and artificial intelligence can easily be tricked by false information from a clever adversary -- critical situations for national defense. In an effort to build the next generation of machine-learning methods to support its needs, the Air Force Office of Scientific Research and the Air Force Research Laboratory have awarded $5 million to establish a university center of excellence devoted to efficient and robust machine learning at the University of Wisconsin–Madison. The center also includes researchers from the Toyota Technological Institute at Chicago (TTIC).


Multi-university collaboration will use data science to find the next El Nino

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Hurricane Harvey, shown in 2017. A new data project hopes to sniff out weather patterns. The El Nino and La Nina patterns in the Pacific Ocean are notorious for their long-distance effects on weather as far away as Africa and the Midwestern United States. But climate experts also know of several other such patterns, known as teleconnections, and believe that there are many more to be discovered. The new TRIPODS Climate project, a collaboration among the University of Wisconsin–Madison, the University of Chicago, and the University of California, Irvine, will develop novel data science tools to sniff out these hidden patterns, improving weather forecasts and scientific understanding of global climate.


Data science aims to find next El Niño

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The El Niño/La Niña pattern in the Pacific Ocean is notorious for its long-distance effects on weather as far away as Africa and the Midwestern United States. But climate experts also know of several other such patterns, known as "teleconnections," and believe that there are many more to be discovered. The new TRIPODS Climate project, a collaboration among the University of Chicago, University of Wisconsin-Madison and the University of California-Irvine, will develop novel data science tools to sniff out these hidden patterns, improving weather forecasts and scientific understanding of global climate. Researchers will apply data science methods such as machine learning, network analysis and predictive modeling to the growing flood of climate data. "There are fundamental challenges pervasive in data science that are epitomized in the climate science setting, making this collaboration a nice opportunity for advances on a number of fronts," said Rebecca Willett, professor of computer science and statistics at UChicago.


#289: On Design in Human-Robot Interaction, with Bilge Mutlu

Robohub

Professor Mutlu discusses design-thinking at a high-level, how design relates to science, and he speaks about the main areas of his work: the design space, the evaluation space, and how features are used within a context. He also gives advice on how to apply a design-oriented mindset. Bilge Mutlu is an Associate Professor of Computer Science, Psychology, and Industrial Engineering at the University of Wisconsin–Madison. He directs the Wisconsin HCI Laboratory and organizes the WHCI D Group. He received his PhD degree from Carnegie Mellon University's Human-Computer Interaction Institute.


UW launches new school of computer science, responding to student demand and workforce need

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The lab is directed by Bilge Mutlu, associate professor of computer science, psychology and industrial engineering, and focuses on the study of how humans interact with robots including specialization in human-robot collaboration, robot-mediated communication and designing robot peers for children. The University of Wisconsin-Madison announced on Thursday the creation of its first new school in two decades, responding to high demand from students and a burgeoning need in the state's workforce. The vision for a new School of Computer, Data and Information Sciences reflects a number of forces coming together on the flagship campus. Computer science is now the most popular undergraduate major at the university, growing to 1,560 students in 2018. Over several years, massive increases in student enrollment strained the computer science department's resources.