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Phase transition of random plaquette models
Tiling with Electrons: fractionalization and emergent symmetry
Pyroptosis & Innate Immunity: Mechanisms & Therapeutics Potentials
【数学之美-杰出学者讲坛】2024年第6期 || Some recent results on conformally in...
报告题目:
Innovation analytics: measuring the creativity of designs using machine learning
 报告人:
Professor Mary Lou Maher
Department of Software and Information Systems 
College of Computing and Informatics 
University of North Carolina Charlotte, USA
报告时间:
2014-11-04 10:00
报告地点:
精密仪器系和机械工程系大楼四楼会议室4304
主办单位:
机械系
  简介:
Mary Lou Maher, Ph.D., most recently a Senior Research Scientist in the iSchool at the University of Maryland and Honorary Professor of Design Computing in the Design Lab at the University of Sydney, is the Chair of the Department of Software and Information Systems in the College of Computing and Informatics at University of North Carolina Charlotte. Mary Lou completed a BSc at Columbia University in 1979, and a MS and Ph.D. at Carnegie Mellon University, completing the Ph.D. in 1984. As the Professor of Design Computing at the University of Sydney she was co-Director of the Key Centre of Design Computing and she established a new degree program: the Bachelor of Design Computing. While at the National Science Foundation (NSF) from 2006-2010, she was Deputy Director of the Information and Intelligent Systems Division and a Program Director. At NSF, she established the CreativeIT program and helped manage the Human Centered Computing, Cyber-Enabled Discovery and Innovation, Design Science, and Social-Computational Systems Programs. While at the University of Maryland, she developed collaborative projects on crowdsourcing design for citizen science and introduced design thinking to graduate projects in information management.
Research Description: Mary Lou’s research interests span a broad area of design and computing, specifically the study and development of novel interaction and communications technology, and models of design and creativity. Her research draws on and contributes to human-computer interaction, intelligent systems, computer-supported collaborative work, design science, and computational creativity. Her current research has a focus on developing social-computational models and new technology as we scale up from creativity enhancing human-computer interaction, through effective collaborative systems, to large-scale and highly motivating collective intelligence and crowdsourcing. Some highlights of her recent research are: developing models of motivation, innovation, and diversity in collective intelligence, designing tangible and immersive interaction environments and evaluating their impact on creative cognition; the design and study of virtual worlds for collaboration and education; and developing computational models of curiosity for extending the functionality of search and motivated reinforcement learning algorithms.
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