Tova A.

Responsibilities:

• Structured the end-to-end backend flow (model → explanation → metrics → UI streaming), making long XAI jobs smooth while keeping the pipeline modular and scalable.

• Developed a unified model interface to support multiple model formats and vision tasks within one consistent explainability pipeline.

• • Implemented differentiable model-loading across formats to ensure gradient-based XAI methods run reliably end-to-end.
• • Designed robust normalization strategies for Quantus metrics (e.g., Complexity, Sparsity), producing stable and comparable scores across diverse models and heatmap behaviors.
• • Integrated the Randomisation metric into the evaluation flow and validated correctness by inspecting model kernels and verifying expected behavior changes.
• • Implemented spider-chart generation and supporting ranking/aggregation logic to present multi-metric results clearly and enable intuitive comparisons.
• • Added live UI streaming of progress, heatmaps, and metrics to keep the interface responsive during long-running evaluations.

• Built metric post-processing to aggregate, scale, and normalize outputs into uniform, interpretable 0–1 evaluation ranges.