
Brian Zhang developed modular scoring workflows and enhanced robot feedback mechanisms in the StuyPulse/Aunt-Mary repository, focusing on maintainable and scalable robot control. He refactored elevator-arm scoring into distinct routines and updated the RobotContainer to leverage these new commands, improving the predictability of scoring operations. By consolidating constants into dedicated interfaces and subsystem-specific files, Brian streamlined configuration management and enabled more reliable arm and elevator tuning. Working primarily in Java and applying skills in code organization and embedded systems, he delivered features that improved subsystem integration, reduced maintenance overhead, and accelerated feature validation, demonstrating thoughtful depth in both design and implementation.

February 2025: Focused on scalable scoring workflows and maintainable constants in StuyPulse/Aunt-Mary. Key outcomes include modular scoring routines, improved robot feedback via LEDs, and consolidated constants for arm/elevator tuning, enabling more reliable positioning and faster iteration.
February 2025: Focused on scalable scoring workflows and maintainable constants in StuyPulse/Aunt-Mary. Key outcomes include modular scoring routines, improved robot feedback via LEDs, and consolidated constants for arm/elevator tuning, enabling more reliable positioning and faster iteration.
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