Frank’s technical practice combines direct investigation, analytical work, specialist research direction and CAD-to-print iteration. These examples show how each contributes to the Solar Revitalizer™ research program.
Technical investigation and local prototypesMoody’s / Enterprise AI
SQL · Python · Tableau · Power BI · Claude Code · Codex · VS Code · Docker
Investigated code, APIs, databases and logs, prepared local proofs of concept and translated findings into testable requirements. Partnered with Engineering through production delivery.
Solar Revitalizer™ relevance. Informs source traceability, data-quality checks, exception handling and human review when designing research workflows and routing decisions.
Analysis and experiment designGoogle / Product analytics
SQL · Python · Telemetry analysis · Dashboards · Product experiments
Connected behavioral data and customer feedback to hypotheses, experiment interpretation and product priorities.
Solar Revitalizer™ relevance. Informs practical baselines, useful measurements and evaluation criteria: does additional evidence improve the decision enough to justify collecting it?
Configuration and operating practiceHealth Recovery Solutions / Workflow tooling
Jira · Confluence · SharePoint
Configured shared intake, ownership, documentation and reporting workflows across teams.
Solar Revitalizer™ relevance. Informs research coordination, versioned protocols, issue ownership and accountable follow-through as a study moves from scope to execution.
Product analysis and quality assuranceSNAP Interactive / Analytical collaboration
Splunk · Funnel analysis · Experiment inputs · Regression testing
Worked with data scientists on behavioral insights and experiments, combining user interviews with analysis and QA.
Solar Revitalizer™ relevance. Informs comparisons that consider both measured behavior and operational consequences, including failure cases and review burden.
Analytical implementationSBX / Solar-data analysis
Python · NumPy · pandas · Chronological evaluation · Data-quality checks
The separate solar-data study compares three plant-power models using chronological training, validation and test periods. Temperature features did not consistently improve on the quadratic baseline.
Solar Revitalizer™ relevance. Provides a concrete example of comparing models and preserving their limits. The proposed module-intake study requires its own measurements and independent reference findings.
Research direction and interpretationSBX / Specialist modeling
PyTorch · TensorFlow · Vertex AI · Databricks · MATLAB feasibility models
Directed research questions, priorities and evaluation needs in collaboration with scientific contributors who developed the specialist implementations.
Solar Revitalizer™ relevance. Connects model development and research interpretation to the next experiment, resource decisions and qualified technical collaboration.
Research program toolingSBX / Modeling and design tooling
MATLAB · COMSOL Multiphysics · Autodesk Fusion 360 · AWS Cloud
MATLAB, COMSOL Multiphysics, Autodesk Fusion 360 and AWS Cloud have been part of SBX’s modeling, design and computing work.
Solar Revitalizer™ relevance. Relevant to numerical investigation, physical layouts and computational workflows. Measurements and calibration determine when a system model can guide a physical experiment.
CAD-to-print practiceCAD and physical prototyping
CadQuery · Python · NumPy · STEP/STL/3MF · Bambu Studio · FDM printing
Uses dimensioned models, geometry and mesh checks, print preparation and physical feedback to iterate practical prototypes.
Solar Revitalizer™ relevance. Informs specimen design, fit and manufacturing constraints for materials research. Qualifying a recovered feedstock remains a material-specific experiment.
