Sparse data system estimation with application to pharmacokinetics 

RANSAC-based semi-supervised learning algorithms for partially labeled data, with application to neurological screening from eye-tracking data 

Analysis, design, and optimization of large-scale networks of dynamical systems 

Data-driven learning for dynamical systems in biology 

Algorithmic aspects of throughput-delay performance for fast data collection in wireless sensor networks 

Data privacy in deep learning using trusted hardware 

‘Sensor’ship and Spatial Data Quality 

Failure prediction for rod pump artificial lift systems 

Architectural innovations for mitigating data movement cost on graphics processing units and storage systems 

Neighborhood and graph constructions using non-negative kernel regression (NNK) 

Inference of multiple curves and surfaces from sparse data 

Learning the semantics of structured data sources 

Information granulation and dimensionality reduction of seismic vibration monitoring data using orthonormal discrete wavelet transform for possible application to data mining, 2003 

Deriving real-world social strength and spatial influence from spatiotemporal data 

Signal processing methods for interaction analysis of functional brain imaging data 

Towards trustworthy and data-driven social interventions 

Data-driven multi-fidelity modeling for physical systems 

USC Computer Science Technical Reports, no. 826 (2004) 

Inference of computational models of tendon networks via sparse experimentation 

A method for characterizing reservoir heterogeneity using continuous measurement of tracer data 

Improving machine learning algorithms via efficient data relevance discovery 

Modeling of Earth's ionosphere and variational approach for data assimilation 

Scalable multivariate time series analysis 

Cache analysis and techniques for optimizing data movement across the cache hierarchy 

A reference-set approach to information extraction from unstructured, ungrammatical data sources