Collaboration and Knowledge Transfer
Open-Source, On-Farm Systems for Precision Agriculture Applications
In this presentation, we overview UCSB SmartFarm. SmartFarm is an open source computing system that combines data from a variety of sensors, integrates recent advances in data analytics, machine learning, and user interfaces (compatible with those available from public clouds), and implements support for automatic self-management and fault resilience, precluding the need for an IT staff to maintain the system. SmartFarm combines these technologies to provide on-farm decision support for growers and to automate and inform precision agriculture solutions and farm operations.
Chandra Krintz is a Professor of Computer Science (CS) at UC Santa Barbara and Chief Scientist at AppScale Systems Inc. Chandra holds M.S./Ph.D. degrees in CS from UC San Diego. Chandra's research interests include programming systems, cloud and big data computing, and the Internet of Things (IoT). Chandra has supervised and mentored over 70 students, has published her work in a wide range of top venues, is the recipient of multiple teaching and research awards, and has led several educational and outreach programs that introduce computer science to young people.
Foundations of Deep Learning
The impact of deep neural networks in numerous application areas of science, engineering, and technology has never been higher than right now.
Still, progress in practical applications of deep learning has considerably outpaced our understanding of its foundations. Many fundamental questions remain unanswered. Why are we able to train neural networks so efficiently? Why do they perform so well on unseen data? Is there any benefit of one network architecture over another?
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