Cláudio Silva, NYU
The last five years has brought us a revolution in computing through the development of data science. Machine learning and deep learning techniques have been sweeping the field and enabling computers to perform tasks that were previously unattainable. Through new algorithmic developments and new hardware architectures, it is now possible to analyze increasingly large volumes of data. There have also been great advances on touch-based interfaces, virtual and augmented reality displays, and cloud computing. If we consider all these changes, we can reasonably expect that Scientific Discovery Environments in the near future will be drastically different than the ones we are using now. In this talk I will make an attempt to articulate what might be possible to do with next-generation visualization and scientific discovery environments.
Speaker Bio. Cláudio T. Silva is a professor of computer science and data science at New York University. His research interests are primarily in visualization, data science, and geometric computing. Most recently, he has been designing new systems and techniques for analyzing urban and sports data. Claudio is a Fellow of the IEEE and he received the 2014 IEEE Visualization Technical Achievement Award. In 2015, he was elected chair of the IEEE Technical Committee on Visualization and Computer Graphics. His research is current funded by DARPA, DOE, NSF, NASA, and the NYU Moore-Sloan Data Science Environment.