TechTalk

November 27 2023 (Monday) 4:00-5:00pm
Professor Gregory Abowd have been speaking and writing about the idea of an Internet of Materials (IoM) for nearly a decade. It started as a way to rethink Mark Weiser’s vision of ubiquitous computing in a more modern context, with the same hopeful zeal that Weiser presented in his writings from the late 1980s and early 1990’s. Professor Abowd will summarize how that re-interpretation has inspired his work, and the work of a growing community, for nearly a decade. From those involved in the fundamental understanding of computation to those involved in the practical development and deployment of computation, the future seems bright. We are moving towards a world of increased ubiquity of computation. There appears to be no end in sight for the increased ubiquity of all things computational. From a technical perspective, this is wonderful. More recently, professor Abowd have been forced to think about this vision through a different lens. How we justify any new vision of a technological future must be better grounded in the human motivation and potential impact. After explaining the “successes” of IoM, he will explain why he has fallen far short of a compelling motivation. But there are more compelling motivations, having to do with health, usable security and privacy, and, most importantly, sustainability. We MUST begin questioning a lot of the assumptions on how to make, operate, and dispose of computational objects. IoM is no longer a journey for a hopeful “visionary” to play out his fanciful predictions for the future. It is a mandate to address the fundamental hazards of our current trajectory towards ubiquitous computing.

November 13 2023 (Monday) 3:00-4:00pm
The number of colors in fluorescence microscopy is far less than the types of intracellular compartments. I will present our recent progress in super resolution imaging and deep convolutional neuronal networks to segment 15 subcellular structures. This approach bypasses the limitations of multi-color imaging, accelerates the imaging speed by one order of magnitude, and can accurately segment vesicle organelles with similar shapes and sizes. The super-resolution advantages were demonstrated in resolving the 3D anatomic nanostructures at different mitotic phases and tracking the fast dynamic interactions among nine intracellular compartments in live cell. We show transfer learning ability of our networks among different microscopes, different cell types, and even complexed system of living tissues.