Ocean Engineering and Applied Technology

Oscar López, Ph.D.
Assistant Research Professor
772.242.2410
lopezo@fau.edu
Publications
ORCiD profile

• Information theory and signal processing
• Tensor-based statistical inference, high-dimensional data analysis and processing
• Applications to oceanographic and atmospheric data; compression, de-noising and processing
• Computational imaging via compressive sensing techniques
• Hyperspectral imaging
• Seismic data acquisition and imaging
• Underwater imaging in turbid conditions; single-photon counting and lidar

My current focus is on high-dimensional data analysis, with an emphasis on tensor-based methods for statistical inference and computational imaging. My goal is to develop techniques that leverage the multidimensional structure of datasets, to outperform traditional vector and matrix approaches. By viewing the “curse of dimensionality” as an opportunity, I exploit the "concentration of measure" in high-dimensions to design scalable and robust inference algorithms.

Current directions include:

1. Tensor decomposition-based modeling and inference. Demonstrating the theoretical and practical benefits of preserving multiway structure in data.
2. Low-rank recovery and sample complexity. Establishing statistical and computational limits for tensor completion using CP and related decompositions.
3. Applications to computational imaging. Designing decomposition-constrained optimization methods for large-scale oceanographic and atmospheric imaging.

I welcome inquiries from prospective students and postdoctoral researchers.