Big Data and Visualization
The simulation and visualization program investigates advanced computational and hardware techniques to understand and predict physical phenomena, as well as unique image rendering methods to enhance the interpretation of complex systems and data sets. There has been a special emphasis on leveraging the data deluge (big data) coming from cheap sensor technology and computing resources. This program develops and advances simulation and visualization capabilities and applies them in a societal context. One goal is to develop enabling technologies for products or processes to be altered and tested in a virtual environment before any physical models are created. Such capability will significantly reduce the time and cost associated with product development, while improving the accuracy, efficiency, and robustness of a product or manufacturing process. In addition to foundational research activities involving graphics, computing, vision and intelligence and data analytics, specific applications of this thrust include designing and optimizing novel manufacturing processes, energy efficient processes and systems as well as understanding biomedical data.
Faculty researchers: Sourabh Bhattacharya, Mark Bryden, Abhijit Chandra, Cody Flemming, Baskar Ganapathysubramanian, Ming-Chen Hsu, Chao Hu, Song-Charng Kong, Adarsh Krishnamurthy, Valery Levitas, Beiwen Li, Reza Montazami, Jim Oliver, Rafael Radkowski, Soumik Sarkar, Cris Schwartz, Xinwei Wang and Eliot Winer.