Weekly QuEST Discussion Topics, 8 Jan

Kabrisky Lecture 2021

Dr. Matthew Kabrisky was an Air Force pioneer and innovator.  From Air Force aviator in the 1950s to professor, mentor, and researcher, his discoveries paved the way for many modern technological advancements.  He developed theories of how the human brain processes information to recognize visual objects. This work directly led to the innovation of implanted electrodes for those afflicted with diseases such as epilepsy and injuries that resulted in paralysis. He was the leading international expert on the physiological symptoms of space adaptation sickness, i.e., motion sickness.  His research led NASA to a better understanding and an approach to mitigate the effects of space environments on astronauts.  His research in the area of robust speech recognition laid critical foundations for fostering the development of DoD and private industry products ranging from voice activated controls in advanced tactical aircrafts, to aides for the disabled and handicapped and industrial process control. In the 1990s, he helped lead a team of engineers that developed the world’s most accurate breast cancer detection system.  This highly successful product has helped in the detection of thousands of breast cancers before they would have otherwise been detected. Dr. Kabrisky’s pioneering efforts paved the way for current innovations across the Nation, the Air Force and at the Air Force Institute of Technology.

Every January the QuEST group uses the first lecture of the calendar year to present a ‘state of QuEST’ lecture in his honor as he was a founding member of the QuEST group.  This lecture sometimes takes more than one meeting as it is designed to bring anyone up to speed on how we use terms and to communicate what we seek to accomplish.

n  QuEST is an innovative analytical and software development approach to improve human-machine team decision quality over a wide range of stimuli (handling unexpected queries and contextual adaptation) by providing computer-based decision aids and decision engines controlling agents that may be embedded in a platform interacting with the world that are engineered to provide both intuitive reasoning and “conscious” context sensitive thinking.

n  QuEST provides a mathematical framework to understand what can be known by a group of people and their computer-based decision aids about situations to facilitate prediction of when more people (different training) or computer aids are necessary to make a particular decision.