Upcoming Events
Applied Mathematics Seminar: Need More Power: Energy Efficient Motion for Legged Robots
Conference/Seminar
Speaker: Dr. Mario Harper, Assistant Professor at the Department of Computer Science, USU
ZOOM ID: 945 1753 3441 PWD: USUAMS
Abstract: I hope you come out of this talk knowing a little about how to constrain mathematical models and machine learning to enable walking, adaptable robots ready to work in the real world. Humans are quite good at walking and we often forget how complex this process, for very little energy we can move almost anywhere. Replicating this type of organic walking behavior is challenging in the best of circumstances, but it is compounded when the real world gets involved (foot-ground interaction is not easy to model). Now imagine a robot tasked with moving in an unstructured outdoor environment it has never experienced. Come and see how we approach complex issues in modern robotic systems, ask questions and perhaps you will find that the mathematics of robotics is interesting to you!
Applied Mathematics Seminar: Harnessing the Power of Time Series Data
Conference/Seminar
Zoom ID: 945 1753 3441
Passcode: USUAMS
Speaker: Soukaina Filali Boubrahimi, Assistant Professor of computer science at USU.
abstract:
Time series data are ubiquitous in daily life. From our heart rates measurements, credit cards transactions, to daily bitcoins pricing, all discrete-valued data that have a time component are considered time series data. The limitation of having huge datasets is not at the storage level, as Moore's Law predicted it well, but in the ability to extract useful information from it. In this talk, I will expose some ideas on how to harness the power of time series data through some applications such as solar events predictions and spatiotemporal shape interpolation. I will also discuss our recent model, 1DCNN shapelet miner, a novel interpretable motif discovery model inspired from the idea of mining recurring patterns in DNA that are presumed to have a biological function. Finally, I will provide a discussion on some promising directions on multivariate time series classification using shapelets mining algorithms.
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