
Developed a Circuit Scheduling Timing Visualization Tool for the Qiskit/qiskit-ibm-runtime repository, focusing on enhancing circuit performance analysis. The tool parses and preprocesses timing metadata from compiled quantum circuits, then visualizes this data to help users identify and optimize scheduling bottlenecks. Leveraging Python for backend development and data visualization, the solution integrates seamlessly with existing circuit simulation workflows. The implementation supports data-driven debugging and performance tuning, aligning with business goals of reliability and efficiency in runtime execution. The work demonstrates depth in API development, code refactoring, and documentation, delivering a targeted feature that improves circuit scheduling transparency for developers and customers.
In October 2025, delivered a focused enhancement to Qiskit IBM Runtime: a Circuit Scheduling Timing Visualization Tool that surfaces timing metadata for compiled circuits. The tool provides parsing, preprocessing, and visualization capabilities, enabling developers and customers to analyze and optimize circuit scheduling timing, accelerating performance tuning and debugging. This aligns with business goals of reliability and efficiency in runtime execution.
In October 2025, delivered a focused enhancement to Qiskit IBM Runtime: a Circuit Scheduling Timing Visualization Tool that surfaces timing metadata for compiled circuits. The tool provides parsing, preprocessing, and visualization capabilities, enabling developers and customers to analyze and optimize circuit scheduling timing, accelerating performance tuning and debugging. This aligns with business goals of reliability and efficiency in runtime execution.

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