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. Research Project: The project fellow will assist in a project that addresses gaps in knowledge of the location and distribution of endemic Caribbean tree species. Using geographic information system methods
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development pertaining to chemical and biological detection. You will gain experience with algorithms, data analysis, Deep Learning, Python, pytorch and /or tensorflow, NLP, genetic algorithm, computer vision
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and resilience of U.S. infrastructure to future disasters. The 2025-2026 IRSP focus is Caribbean Island water infrastructure, including potable water distribution, stormwater drainage, and water
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intelligence Sensor integration and fusion for distributed simultaneous localization and mapping (SLAM) Machine perception for object detection, identification, and tracking Test, Evaluation, Verification, and
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investigation and developing software algorithms and techniques to support human or machine information interactions for the purpose of information retrieval/dissemination, analysis and/or decision making
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algorithms) that enable rapid creation of new high-fidelity multi-scale/multi-physics computer models of materials capable of utilizing modern extreme-scale computing environments. The success of multi-scale
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Mexico, and elsewhere), and in relating particle composition to measurements of size distributions, air mass trajectories, etc.; (2) development of algorithms to process complex spectral data and identify
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the development of image/signal processing algorithms from a multidisciplinary approach, to include multiple sensor modalities. These multidisciplinary research opportunities incorporate theoretical and
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and often different from the canonical types of data used to benchmark machine learning (ML) algorithms. In this opportunity, we will be evaluating how state-of-the-art ML techniques can be used
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techniques for assessing cyber vulnerability and degree of adversarial activity over wired and wireless networks with distributed intrusion detection sensors, (ii) developing experimentally-validated models