Several decades ago, advances in computers, lasers, and detectors set off a revolution in biological microscopy that continues to this day. The result is an embarrassment of riches, where the quantity and complexity of the data we acquire far outstrips our ability to extract quantitative information from, or better yet, novel biological insights from, any more than a small fraction of it. Dr. Betzig will describe the development and application of several microscope technologies, and the challenges and opportunities posed by the data they produce.
The Berkeley Distinguished Lectures in Data Science, co-hosted by the Berkeley Institute for Data Science (BIDS) and the Berkeley Division of Data Sciences, feature faculty doing visionary research that illustrates the character of the ongoing data, computational, inferential revolution. All campus community members are welcome and encouraged to attend. Arrive at 3:30pm for tea, coffee and discussion prior to the formal presentation.
Eric Betzig is a Professor of Molecular and Cell biology, the Eugene D. Commins Presidential Chair in Experimental Physics, and an Investigator of the Howard Hughes Medical Institute at the University of California, Berkeley. His Ph.D. thesis at Cornell University and subsequent work at AT&T Bell Labs involved the development of near-field optics – an early form of super-resolution microscopy. He left academia in 1995 to work in the machine tool industry, but returned ten years later when he and friend, Harald Hess, built the first super-resolution single molecule localization microscope in Harald’s living room. For this work, he is a co-recipient of the 2014 Nobel Prize in Chemistry. Today, he continues to work in super-resolution, as well as with non-diffracting light sheets for the 4D dynamic imaging of living systems and adaptive optics to recover optimal imaging performance deep within aberrating tissues. He views the quantitative analysis of TB-scale imaging data of subcellular dynamics within multicellular organisms to be one of the most pressing issues and greatest opportunities in biology today.