I build agentic AI and solve complex time-series and signal processing problems for NASA and Lockheed Martin Space and Earth science missions.
Focus: Agentic Orchestration, Quantitative Research, Variational Autoencoder, Scientific Reasoning, Anomaly Detection, State Estimation
Tooling: Python / MATLAB / C++ / R
Note: Many of my repositories are private due to research, collaboration, or organizational constraints. Recruiters and potential collaborators are welcome to contact me if you would like to learn more about my experience, project scope, or technical contributions.
- Physics-Informed Convolutional Autoencoder for Solar Wind and Space Weather
- Reasoning With a Star: Heliophysics Dataset and Agentic Benchmark
- Agentic AI for Near-Real-Time Ocean Hazard Assessment
- An Intelligent Toolbox for Multi-Scale Oceanography Analysis
- Agentic Orchestration System for Heliophysics Tasks
- Earth Representations Transfer to Titan SAR
- Satellite Telemetry and Time-series Anomaly Detection
| Project | Description | Link |
|---|---|---|
| PISCES: Physics-Informed Solar-wind Convolutional autoEncoder for Space-weather Anomaly Detection and Early Warning | Physics-Informed Machine Learning |  |
| CETUS: How Far Do Representations Trained on Earth Transfer to Cassini SAR of Titan? | Foundation Model Evaluation | |
| Reasoning With A Star: Agentic benchmark for NASA's Heliophysics | Benchmark and Evaluation |  |
| Agentic AI for Near-Real-Time Ocean Hazard Assessment | Agentic System | |
- Signal processing with AI/ML and traditional statistical learning algorithms
- Agentic systems and platforms
- Quant trading and research
- Open to: research collabs and industry roles in AI/ML