Dharani Murugan

At Zensar Technologies, I supported an electric-vehicle driving-behaviour data annotation project, labelling and validating real-world driving events for downstream machine learning training.

I designed standardized prompt frameworks for lane changes, violations, and hazard scenarios, improving annotation consistency and reducing review turnaround time. I also applied data-quality checks and structured tagging logic to create clean, analysis-ready datasets.

I'm skilled in advanced SQL, Python, Tableau, Power BI, Metabase, BigQuery, and Spark/PySpark, with experience translating large unstructured datasets into reporting and decision-ready insights.

Through CNN projects in depressive-state audio analysis and skin-cancer detection, I've built classification models, performed exploratory analysis, and worked with preprocessing, feature extraction, augmentation, visualization, and model evaluation.