We live in an era in which the creation of new data from simulations, sensors, experiments, imaging, is growing exponentially such that every two days we create as much new data as we did from the beginning of mankind until the year 2003. One of the greatest scientific challenges of the 21st century is to effectively understand and make use of the vast amount of information being produced. Visual data analysis will be among our most important tools to understand such large and often complex data. In this talk, I will present state-of-the-art visual analysis techniques for discovery applied to important Big Data problems in science, engineering, and medicine.

Chris R. Johnson is a Distinguished Professor of Computer Science and founding director of the Scientific Computing and Imaging (SCI) Institute at the University of Utah. He also holds faculty appointments in the Departments of Physics and Bioengineering. He holds appointments in the Departments of Physics and Bioengineering. His research interests are in the areas of scientific computing and scientific visualization. In 1992, Dr. Johnson founded the SCI research group, now the SCI Institute, which has grown to to employ over 200 faculty, staff and students. Professor Johnson serves on a number of international journal editorial and advisory boards to national and international research centers. He is a Fellow of AIMBE (2004), AAAS (2005), SIAM (2009), and IEEE (2014). He received a Young Investigator’s (FIRST) Award from the NIH in 1992, the NSF National Young Investigator (NYI) Award in 1994, the NSF Presidential Faculty Fellow (PFF) award from President Clinton in 1995, a DOE Computational Science Award (1996), the Presidential Teaching Scholar Award (1997), the Governor’s Medal for Science and Technology from Utah Governor Michael Levitt, the Utah Cyber Pioneer Award, the IEEE Visualization Career Award, IEEE IPDPS Charles Babbage Award and the IEEE Sidney Fernbach Award, and the University of Utah’s most prestigious faculty award, the Rosenblatt Prize.