- Lead R&D of applied statistical learning in solar wind connectivity modeling, with the WSA Solar Wind Model (PI: Nick Arge). Created algorithm that produces probabilistic forecast of solar wind footpoint using multiple model variations.- Lead design and implementation of time series algorithm to autonomously identify ionospheric signatures of magnetic reconnection in the cusps (dispersion events), with application to DMSP and upcoming NASA magnetosphere-ionosphere-thermosphere coupling missions (PI: Li-Jen Chen).

Heliophysics:- Neural network methods for reversing image artifacts introduced into scientific data products by on-board Discrete-Wavelet compression used by MMS/FPI (da Silva et al., JGR 2020)- Data management and access design to integrate instrument housekeeping telemetry into the MMS/FPI operations workflow, through methods of database archival, visualization and API access- Lead design and development of multi-mission Automated Fault and Anomaly Detection system, implemented for MMS/FPI- Large scale data correlation and trend analysis to uncover physics-based method for addressing instrument noise (da Silva et al., JGR 2021)- Flight Calibration and ground system development for Micro-Channel Plate Particle Instruments for MMS Mission / Fast Plasma Investigation, including flat-fielding, photo-electron removal, ion/electron balancing, and inter-spacecraft sensitivityEarth Sciences:- ICESat-2 is a NASA Lidar Satellite for building a time-dependent topographic map of the polar ice caps and Greenland.- Data Science and mathematical modeling for calibration and I&T verification of ICESat-2 flagship instrument ATLAS. Responsible for dead time, quantum efficiency, optical misalignment, thermal biases, and validation of T-VAC testing data.

Teaching assistant for graduate courses in Space Weather and Space Systems, and Systems Engineering for Space taught through the Engineering for Professionals program managed out of the Applied Physics Laboratory.

- Development of web-based visualization software for Atmospheric Sciences Data with the GES DISC Distributed Active Archive Center (DAAC): https://giovanni.gsfc.nasa.gov/giovanni/- Development of data center portal for the DAAC, from which scientists discover, visualize, and access atmospheric sciences data. https://daac.gsfc.nasa.gov/

- Experimentation with novel methods for scientists to interact with atmospheric sciences data, including the social components to scientific discovery and tablet-based applications for accessing data.- Developed prototype for next generation Giovanni data visualization system, based on higher quality visualization rendering and the python programming language

- With Google Maps + Internal Apps teams, developed data presentation/management backend for internal geographic information system (GIS). Included cloud-based database optimized for spatial data, and design of algorithms for extracting information from large datasets.