Specialize in the development of software to support science research in the areas of Earth Observation, artificial intelligence, security, GPU-computing, and hardware-accelerated applications. Some ongoing projects include: land cover land use change (LCLUC), object detection, and semantic segmentation of multi-spectral remote sensing imagery.
Development of AI/ML, high-performance computing, and GPU-accelerated software for the analysis of remotely sensed data.
Development of software to support science data processing research.
Lead a team of five undergraduate students in the development of material science computational projects. Developed and implemented software to accelerate molecular dynamics simulations in HPC environments. Assisted and collaborated with ongoing research projects in the area of data mining, clustering, image processing, and machine learning. Studied biological and electrical systems applied to physical sensors by means of molecular dynamics simulations.
Intern: Summer 2016, Fall 2016, Summer 2017, Summer 2018; Contractor under ADNET LLC: Spring 2017, Fall 2017, Spring 2018;
Responsible for the engineering of software and information systems to support a critical log analysis infrastructure for monitoring and anomaly detection of high-performance computing systems. Served as a Linux and Unix system administrator for security and resource intensive systems, including revision control, networking, and user-facing virtual machines. Designed and developed software to support several computing intensive applications via multi-node MPI implementations and DevSecOps initiatives.
2022 – Present PhD Geographical Sciences, University of Maryland, College Park, USA.
2015 – 2020 B.S. Computational Mathematics, Major Computer Science, University of Puerto Rico at Humacao, PR.
Caraballo-Vega, J., M. Carroll, C. Neigh, et al. M. Wooten, B. Lee, A. Weis, M. Aronne, W. Alemu, and Z. Williams. 2023. "Optimizing WorldView-2, -3 cloud masking using machine learning approaches." Remote Sensing of Environment, 284: 113332 [10.1016/j.rse.2022.113332]
Caraballo-Vega, J. A., N. S. Smith, M. L. Carroll, et al. L. Carriere, J. E. Jasen, M. T. Le, J. Li, K. Peck, S. L. Strong, G. S. Tamkin, M. A. Thompson, and J. H. Thompson. 2022. "Remote Sensing Powered Containers for Big Data and AI/ML Analysis: Accelerating Science, Standardizing Operations." IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, [10.1109/igarss46834.2022.9883436]
Specialize in the development of software to support science research in the areas of Earth Observation, artificial intelligence, security, GPU-computing, and hardware-accelerated applications. Some ongoing projects include: land cover land use change (LCLUC), object detection, and semantic segmentation of multi-spectral remote sensing imagery.
Caraballo-Vega, J., M. Carroll, C. Neigh, et al. M. Wooten, B. Lee, A. Weis, M. Aronne, W. Alemu, and Z. Williams. 2023. "Optimizing WorldView-2, -3 cloud masking using machine learning approaches." Remote Sensing of Environment 284 113332 [10.1016/j.rse.2022.113332]
Caraballo-Vega, J. A., N. S. Smith, M. L. Carroll, et al. L. Carriere, J. E. Jasen, M. T. Le, J. Li, K. Peck, S. L. Strong, G. S. Tamkin, M. A. Thompson, and J. H. Thompson. 2022. "Remote Sensing Powered Containers for Big Data and AI/ML Analysis: Accelerating Science, Standardizing Operations." IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium [10.1109/igarss46834.2022.9883436]