Tova A.

Responsibilities:

• Structured the backend flow (model → explanation → metrics → UI streaming), making the system modular, scalable, and capable of running long XAI jobs smoothly.

• developed a unified model interface that enables supporting multiple model formats and tasks within one consistent explainability pipeline.

• Implemented model-loading logic that preserves differentiability across formats, ensuring gradient-based XAI methods operate reliably.

• Designed normalization methods that stabilize Quantus metrics such as Complexity and Sparsity, enabling consistent, comparable scores across diverse models and heatmap behaviors.

• Integrated the Randomisation metric into the evaluation flow and verified its behavior by checking model kernels and ensuring results reflect reliable model-behavior validation.

• Implemented spider-chart generation and supporting logic to present multi-metric results clearly and enable intuitive comparison.

• Added live progress, heatmap, and metric streaming to the UI, enabling responsive interaction during long-running explainability evaluations.

• Built metric postprocessing that aggregates, scales, and normalizes outputs into uniform, interpretable 0–1 evaluation ranges.