A5076619202- Space Exploration and Technology
- Planetary Science and Exploration
- Semantic Web and Ontologies
- Distributed and Parallel Computing Systems
- Scientific Computing and Data Management
- Astronomical Observations and Instrumentation
- Reservoir Engineering and Simulation Methods
- Advanced Computational Techniques and Applications
- Quality and Safety in Healthcare
- Research Data Management Practices
- Lexicography and Language Studies
- Business Process Modeling and Analysis
- Astro and Planetary Science
- Data Quality and Management
- Machine Learning and Data Classification
- Image Processing and 3D Reconstruction
- SAS software applications and methods
- Library Science and Information Systems
- Cell Image Analysis Techniques
- Scheduling and Optimization Algorithms
- Space Science and Extraterrestrial Life
- Calibration and Measurement Techniques
- Digital and Traditional Archives Management
- Manufacturing Process and Optimization
- Advanced Database Systems and Queries
Jet Propulsion Laboratory
2015-2024
University of Maryland, College Park
2021
California Institute of Technology
2018
NASA has acquired more than 22 million images from the planet Mars. To help users find of interest, we developed a content-based search capability for Mars rover surface and orbital images. We started with AlexNet convolutional neural network, which was trained on Earth images, used transfer learning to adapt network use report our deployment these classifiers within PDS Imaging Atlas, publicly accessible web interface, enable first image NASA’s
Prompt Patterns provide general and reusable solutions to commonly occurring problems within specific contexts while interacting with a Large Language Model (LLM) such as GPT4. A catalog of generic prompt engineering patterns [1] has been published help users improve LLM results promote further research into engineering. Software software are an analog patterns, providing common in particular context.The defines six categories including Input Semantics, Output Customization, Error...
This paper provides an overview of Optical Payload for Lasercomm Science (OPALS) activities and lessons learned during mission operations. Activities described cover the periods commissioning, prime, extended operations, which primary secondary objectives were achieved demonstrating space-to-ground optical communications. Lessons Mission Operations System topics in areas of: architecture verification validation, staffing, support area, workstations, workstation tools, interfaces with...