Georges Grinstein

University of Massachusetts, Lowell Computer Science


Lecture Information:
  • February 24, 2016
  • 10:00 AM
  • ECS: 349

Speaker Bio

Georges Grinstein is Professor of Computer Science at the University of Massachusetts Lowell, was head of its Bioinformatics Program, Director of its Institute for Visualization and Perception Research, and is now Chief Scientific Officer of Weave Visual Analytics. He received his Ph.D. in Mathematics from the University of Rochester in 1978. His work is broad and interdisciplinary, covering the perceptual and cognitive foundations of visualization, very high-dimensional data visualization, visual analytics and applications. The emphasis is on the modeling, visualization, and analysis of complex information data and systems. He has over 40 years in academia with extensive consulting, over 300 research grants, products in use nationally and internationally, several patents, numerous publications in journals and conferences, a book on interactive data visualization, founded several companies, been the organizer or chair of national and international conferences and workshops in Computer Graphics, in Visualization, and in Data Mining. He has given numerous keynotes and mentored over 40 doctoral students and hundreds of graduate students. He has been on the editorial boards of several journals in Computer Graphics and Data Mining, a member of ANSI and ISO, a NATO Expert, and a technology consultant for various government agencies and commercial organizations. For the last ten years he has co-chaired the IEEE VAST Challenges in visual analytics leading to new research areas. He has developed and taught new courses, one of which Radical Design focused on how to develop radical new products instead of evolutionary ones. He is a member of the Department of Homeland Security’s Center of Excellence CCICADA (Command, Control and Interoperability Center for Advanced Data Analysis), and directs the development of Weave, an open source web-based interactive collaborative visual analytics system incorporating numerous innovations.

Abstract

Visualization, Information Visualization and Visual Analytics share the same pipeline, basically taking data and producing interactive images on displays. There are some minor differences but all in all they’re quite similar. All three have very similar Grand Challenges (scalability, developing a theory, computing the best presentation, …). I’ve spoken on such and other grand challenges in each of these areas over the last 20 years, identifying what wicked problems really need to be addressed and what big problems would have tremendous impact. Progress on these has been quite slow and technology is moving so much more rapidly than anticipated. In this (brief) talk I will discuss key opportunities for various scientists in the context of grand challenges for visualization. These will have tremendous impact within the next decade and great payoff defining new visualizations, new interactions, new systems and new paradigms. I will select 3 or 4 grand challenges related to my research. These involve making peers of video, text and data, large data visualizations and display fidelity, and visualization for the masses.