Mathematical models can direct the design of defective interfering particles as therapeutic antiviral agents for poliovirus.

Patrick Schnable presented novel predictive statistical models to forecast crop performance and maximize overall yield at CSE19.

Careful calibration of sensors that provide information for a large number of measurands is often difficult to achieve in practice.

In this market model, intelligent heterogenous agents trades against each other in a market with latent factors.

Katya Scheinberg describes novel continuous optimization algorithms, which lie at the core of most foundational data science topics.

Amine Kerkeni utilized volumetric deep learning to detect, segment, and classify microfossils in 3D micro-CT scans at CSE19.

Xinlian Liu combined machine learning techniques with MIMIC-III data to suggest best-practice strategies for suicide prevention at CSE19.

At CSE19, Altansuren Tumurbaatar presented a mobile disease surveillance tool that uses CNNs to identify sick faces from a single image.

Maria Weber shared visualization techniques to improve the effectiveness of science communication at CSE19.

Daniel Martin presented an AMR-based ice sheet model that examines the Antarctic ice sheet's response to sheet collapse at CSE19.

At CSE19, Ralf-Peter Mundani discussed the Cave Automatic Virtual Environment, an immersive virtual reality tool for visual data exploration.

Asymptotic expansion techniques can study the harmonic thermal response of vertical geothermal boreholes to sub-annual harmonic excitations.