Keynote Speakers

The latest details appear below


Kurt Akeley

KURT AKELEY is a principal researcher at Microsoft Research Silicon Valley (MSR-SVC), where he works in the areas of computer graphics and computer architecture. His research interests include graphics system architecture and the design of displays that better accommodate human visual requirements. He joined Microsoft in July of 2004. From January 2005 through March 2007 Kurt was an assistant managing director of Microsoft Research Asia in Beijing.

Kurt co-founded Silicon Graphics in 1982. During his 19 years at Silicon Graphics he led the development of several high-end graphics systems, including GTX, VGX, and RealityEngine. He also led the development of OpenGL, an industry-standard programming interface to high-performance graphics hardware. His last full-time position with Silicon Graphics was senior vice president and CTO.

Kurt is a named inventor on fifteen patents, a fellow of the ACM, and a member of the National Academy of Engineering. In 1995 he was the recipient of the ACM SIGGRAPH Computer Graphics Achievement Award. He was awarded a BEE degree from the University of Delaware in 1980 and an MSEE degree from Stanford in 1982. He returned to Stanford and earned a PhD in electrical engineering in 2004.

Projection and Parallax

Projection and its time or spatially varying derivative, parallax, are a common thread through my work in computer graphics, stereoscopic display, human vision, and, most recently, light-field display and capture. In this talk I'll present insights, anecdotes, and epiphanies I've accumulated along the way.


Guillaume Thierry

GUILLAUME THIERRY is Professor of Cognitive Neuroscience at Bangor University, and Director of Innovation | Pontio. Using experimental psychology (e.g., reaction times, error patterns), functional brain imaging (functional Magnetic Resonance Imaging, fMRI, and Positron Emission Tomography, PET) and Event-Related Potentials (ERPs) Thierry has studied language comprehension in the auditory and visual modalities, and, in particular, semantic access. In the past seven years, Thierry has investigated a range of themes, such as verbal/non-verbal dissociations, visual object recognition, functional cerebral asymmetry, language-emotion interactions, language development, developmental dyslexia and bilingualism.

Neuromatrix: The world is embodied in our brain

Our brain is an interpreter, probably the most powerful ever conceived by Nature. However, just like every interpreter, it is limited and sometimes it can get things wrong. Most of us take it for granted that what we touch, hear, see, taste and smell is "reality". But this reality is an illusion, a construct, which only exists in our brain, that is, a mental representation. Indeed, what if we could perceive infrared radiations like Cobras or Predator? What if we could see in very low light like cats? What if we could smell people and foods hidden from view 500 yards away? Surely "reality" would feel much different to us if our sensors and brain were able to extract and process such information from the external world. Even more puzzling is the fact that our senses can betray us completely. This is what happens when we see things that are not there or, on the contrary, when we do not see things that are before our eyes. During this lecture, I will attempt to show how the world in embodied in our brain by looking at examples of interactive visual illusions, by showing the power of attention in defining what we see in the world around us, and by introducing patients with brain lesions or mental illness who perceive the world differently.


Frits H. Post

FRITS POST is an associate professor of computer science at TU Delft, where he leads a research group in data visualization since 1990. Initially the group worked primarily in flow visualization, and from 1997 he also started research in Medical Data Visualization. In 1998 he co-founded the TU Delft Virtual Reality (VR) lab, and started research in virtual reality and 3D interaction. He has (co-)authored a large number of publications in many areas of data visualization.

He is involved in many community services and professional activities. He has been a vice chairman of the Eurographics Association, and is currently the chairman of the Eurographics Steering Committee on Data Visualisation and a co-founder of the annual joint Eurographics- IEEE EuroVis Symposium. He is a fellow of the Eurographics Association, has been an Associate Editor of ACM Transactions on Graphics, and has served on the editorial board of Computer Graphics Forum and IEEE Transactions on Visualization and Computer Graphics. He is a member of the Scientific Advisory Board of RIVIC, the Wales Research Institute for Visual Computing.

Data Visualization: Featuring Interactive Visual Analysis

Data visualization is an application-driven field, that is always trying to satisfy its customers and to adapt to the demands, cultures, and workflows of many application areas. Therefore, it is difficult to keep focus on techniques and approaches that are not too application specific. A lot of good work on data visualization consists of single-problem solutions, that cannot be easily merged into general-purpose systems.

In this talk, I will briefly review some current trends and issues, and identify some approaches that are common to many applications. One such approach in data visualization that has attracted interest from the early days is the detection of salient features, or patterns of interest in a data set. The main idea is to extract information at a higher level of abstraction from a mass of data, that is richer in semantics but much smaller in size, and that can help to define scenes and objects for visualization. This idea was pioneered in areas such as flow visualization, but is now more widely applied. It is often considered to be necessity to keep up with the ever rapidly increasing size of data sets, and the demand for interactivity in data visualization and analysis.

Another generic approach in data visualization is called interactive visual analysis (IVA), consisting of a strongly interactive multiple-linked-view interfaces with integrated, powerful data analysis techniques taken from statistical analysis, pattern recognition, machine learning, and other fields. This is built on the assumptions that a single 2D or 3D visualization is often not enough, and spatial views can be augmented with abstract, derived data spaces; that strong interaction helps to promote insight; and that a better balance is needed between human visual inspection and computer-based analysis and reasoning. Interestingly, an IVA interface can serve not only as an environment for exploration of low-level data, but also for defining the high-level features to be extracted, that should summarize the essence of the data. The high-level features are usually highly application specific, and can only be found using theories from the application domains. The big challenge is to create environments for general purpose visual data analysis, and yet allow users to introduce advanced theories and methods from many application domains.

The trend towards more integration in data visualization will be illustrated with cross-links between very different areas, such as medical and flow visualization, and the combined use of techniques from scientific visualization and information visualization, and the absorption of other data analysis techniques. Also, historic and contemporary examples of feature extraction and interactive visual analysis will be shown.

Download a pdf copy of the presentation slides.