Publications
My publications.
2023
- Topological Simplification of Signals for Inference and Approximate ReconstructionGary Koplik, Nathan Borggren, Sam Voisin, and 4 more authorsIn 2023 IEEE Aerospace Conference, Mar 2023
As Internet of Things (loT) devices become both cheaper and more powerful, researchers are increasingly finding solutions to their scientific curiosities both financially and com- putationally feasible. When operating with restricted power or communications budgets, however, devices can only send highly- compressed data. Such circumstances are common for devices placed away from electric grids that can only communicate via satellite, a situation particularly plausible for environmental sensor networks. These restrictions can be further complicated by potential variability in the communications budget, for ex-ample a solar-powered device needing to expend less energy when transmitting data on a cloudy day. We propose a novel, topology-based, lossy compression method well-equipped for these restrictive yet variable circumstances. This technique, Topological Signal Compression, allows sending compressed sig-nals that utilize the entirety of a variable communications budget. To demonstrate our algorithm’s capabilities, we per-form entropy calculations as well as a classification exercise on increasingly topologically simplified signals from the Free- Spoken Digit Dataset and explore the stability of the resulting performance against common baselines.
2022
- Topological Feature Tracking for Submesoscale EddiesSam Voisin, Jay Hineman, James B. Polly, and 6 more authorsGeophysical Research Letters, Mar 2022e2022GL099416 2022GL099416
Abstract Current state-of-the art procedures for studying modeled submesoscale oceanographic features have made a strong assumption of independence between features identified at different times. Therefore, all submesoscale eddies identified in a time series were studied in aggregate. Statistics from these methods are illuminating but oversample identified features and cannot determine the lifetime evolution of the transient submesoscale processes. To this end, the authors apply the Topological Feature Tracking (TFT) algorithm to the problem of identifying and tracking submesoscale eddies over time. TFT identifies critical points on a set of time-ordered scalar fields and associates those points between consecutive timesteps. The procedure yields tracklets which represent spatio-temporal displacement of eddies. In this way we study the time-dependent behavior of submesoscale eddies, which are generated by a 1-km resolution submesoscale-permitting model. We summarize the submesoscale eddy data set produced by TFT, which yields unique, time-varying statistics.
2021
- [Whitepaper] Automation is All You Need: Faster Earth Systems Models with AI/MLKenneth Ball, Jay Hineman, Sam Voisin, and 2 more authorsDec 2021
Tropical cyclones can induce extreme water cycle events through dramatic precipitation and storm surge. More reliable models of intensity will translate into better prediction of the impact of extreme events in large scale Earth systems simulations. We demonstrate and describe AI/ML methodologies for rapid assimilation of new, in situ data products.