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Challenges and opportunities for developing new smart data processing techniques
2019-08-05 09:16  

Abstract: Humanity has reached a point where the technology capacity to produce data has long surpassed our means to meaningfully analyze them. In contrast, data have become more complex, which makes their analysis a challenging task. Nowadays, we are at the dawn of a new era when all human activities will be assisted and guided by smart data processing. Technologies for processing complex data have tremendous potential to improve the quality of life in emerging societies. Such technologies are in high demand to tackle the most urgent needs in the Brazilian society. Better and cheaper networking technology are needed for ubiquitous and low-cost education, including people living in remote sites. Improving data modelling and prediction will help us to optimize the generation of environment-friendly energy with solar and wind farms. Monitoring large areas through high-quality image processing will feed smarter models to understand and possibly act on the effects of climate change. For improving large urban sprawls, high performance data processing systems and efficient drone imaging can be employed for monitoring traffic congestion; help public security; and imaging poorly maintained neighborhoods to detection of Aedes aegypt-prone regions. All these opportunities need new algorithms and techniques to ensure the quality of the knowledge extracted from the huge amount of non-structured, noisy, non-stationary, and highly interconnected data. In this talk I will discuss the opportunities that this new era brings and how multi-national researchers can team up to share expertise and align efforts.

BioProf. Marcelo Keese Albertini, received B.S degree in Computer Science in 2007, and Ph.D degree in Computer Science and Computational Mathematics in 2012, both from University of Sao Paulo, Brazil,. In 2013, he joined the Department of Computer Science, Federal University of Uberlandia, and is currently the associate professor(tenure-track). His current research interests are Data science based on Machine Learning, Data Mining and Statistics,Research of algorithms and data structures for processing and modeling big data.

Time:3-4 p.m. on Aug 8, 2019

Location2ndfloor, School of Information Engineering, Chang’an University

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