Inferring mobility behaviors from trajectory datasets 

Shrinkage methods for big and complex data analysis 

The effects of compaction methods on the permeability of soils 

Tobacco and marijuana surveillance using Twitter data 

Statistical insights into deep learning and flexible causal inference 

Envisioning seismic Los Angeles: data visualization techniques for an interactive seismicity and building response map application 

Estimation of graph Laplacian and covariance matrices 

Microphotonics for tailored infrared emission and secure data encryption 

Data-driven approaches to studying protein-DNA interactions from a structural point of view 

Integrated reservoir characterization for unconventional reservoirs using seismic, microseismic and well log data 

Effective data representations for deep human digitization 

Modeling biochemical components and systems through data integration and digital arts approaches 

Efficient stochastic simulations of hydrogeological systems: from model complexity to data assimilation 

Computational tools for large-scale analysis of brain function and structure 

Responsible AI in spatio-temporal data processing 

Efficient machine learning techniques for low- and high-dimensional data sources 

Subsidence, compaction of sediments and effects of water injection, Wilmington and Long Beach offshore oil fields, Los Angeles County, California. 

A comparison of pixel-based, object-based, deep learning, and data fusion image classification approaches in delineating urban tree canopy in City Terrace 

Evaluating the MAUP scale effects on property crime in San Francisco, California 

Beyond parallel data: decipherment for better quality machine translation 

Theoretical and computational foundations for cyber‐physical systems design 

Learning enabled optimization for data and decision sciences 

Generating gestures from speech for virtual humans using machine learning approaches 

Applications of Wasserstein distance in distributionally robust optimization 

Real-world evaluation and deployment of wildlife crime prediction models