July 10, 2017
I have no idea how I did that: The remarkable learning abilities of the human brain
Abstract: Humans have multiple learning systems that for the most part are functionally and anatomically distinct, evolved at different times for different purposes, and that learn in qualitatively different ways. Progress on understanding these systems has been slowed because most difficult learning tasks recruit multiple systems, making it difficult to know which system mediated any specific performance improvement. One approach that circumvents this problem is to study how people learn new categories of objects. This research has allowed us to map the neural networks that underlie each system and has identified many important and surprising differences in how the systems learn.
Bio: Dr. Ashby is the author of 3 books and more than 150 other publications. He has served as associate editor of the Journal of Experimental Psychology: Learning, Memory & Cognition, as Chair of the NIH Cognition and Perception Study Section, and as a member of various other editorial boards and grant review panels. He is past president of the Society for Mathematical Psychology, winner of the Howard Crosby Warren Medal, and a fellow of the Society of Experimental Psychologists, the Psychonomic Society, and of the Association for Psychological Science.
July 5, 2017
The rock we tricked into thinking
Abstract: You may not know it, but you likely have 5,000,000,000 tiny electrical switches in your pocket. Each switch is precisely and purposefully linked with the others to form an inconceivably intricate tapestry -- a tapestry capable of everything from recognizing language to flying a plane. The growth of computer processors has shaped modern life and yet we still have so many important and fundamental questions remaining. Professor Sherwood will discuss the state of the art in computing and how the demands for energy efficient and intelligent systems is driving the creation of entirely new approaches to the problem inspired by the human brain.
Bio: Tim Sherwood is a Professor of Computer Science at UCSB, specializing in the development of high performance, low power, and mathematically verifiable computer systems. He holds a BS from UC Davis, MS and PhD degrees in Computer Science and Engineering from UC San Diego, and now serves as the Associate Vice Chancellor for Research for UCSB. He is a Distinguished Scientist of the ACM, Co-Founder of a startup on computer hardware security, winner of the UCSB Academic Senate Teaching Award, and 7-time recipient of the “top-pick” award from IEEE Micro Magazine for contributions related to chip and silicon system design.
June 28, 2017
The challenges that society brings to engineering design
Abstract: Engineers are often tasked with building the physical infrastructure capable of serving the underlying societal demands. Examples include transportation networks, power grids, data centers, and many more. A fundamental challenge associated with these "socio-technical" systems is that their underlying performance is largely impacted by how society chooses to use them, and unfortunately society tends to use such systems in a highly inefficient way. In this talk we will shed some light on the unique challenges that surface when seeking to design and control such systems.
June 26, 2017
The math of swarming robots, superconductors, and slime mold
Abstract: Systems of interacting agents arise throughout the natural world and are studied in such varied disciplines as engineering, physics, and biology. What is the optimal way for a swarm of robotic bees to pollinate a bed of crops? How can we use vortex motion in superconductors to develop new technologies for renewable energy? How does a colony of slime mold communicate using chemical signals? Prof. Katy Craig will describe the mathematics underlying systems of interacting agents and how such systems can be analyzed using an age old scientific technique: what happens if we poke it?
Bio: Katy Craig was born in Dallas, Texas, and attended college at Stanford University. After college, she briefly worked at Apple Computer, before realizing that she just wanted to do math all day. She then went to Rutgers University in New Jersey to obtain her Ph.D. After graduating from Rutgers, she spent a year at UCLA as a National Science Foundation Mathematical Sciences postdoctoral fellow and then a year at UCSB as a UC President’s postdoctoral fellow. She loved UCSB so much that she didn’t want to leave, and she is now an assistant professor in the department of mathematics.
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