Nivya Rachel Cherian

- Designed Edge-Cloud data and AI architectures for industrial condition monitoring, enabling distributed processing of sensor data and supporting scalable, data-driven asset monitoring. - Built end-to-end machine learning workflows for industrial time-series data, including preprocessing, feature engineering, model training and evaluation and developed lightweight CNN and MLP models in PyTorch for equipment state classification. - Implemented and benchmarked Edge AI inference on resource-constrained Siemen

- Implemented and maintained test automation solutions using Python-based Robot Framework for industrial software systems. - Designed and administered automated test cases, including debugging and test execution in Smart Infrastructure environments. - Created and maintained user and technical documentation based on internal engineering platforms. - Supported validation and quality assurance activities for Smart Edge Connector software. - Worked on edge-gateway–based internal connectivity solutions wit

- Analyzed software and data requirements, contributing to test strategy, data validation planning and quality criteria in Agile project environments. - Performed exploratory data analysis and profiling across relational and NoSQL databases (MySQL, MongoDB), writing SQL queries to verify, reconcile and validate large datasets. - Designed and executed manual and automated test cases, building reusable validation checks to ensure data accuracy, completeness and consistency. - Investigated data anomalies and d

- Supported measurement activities in Solar Asset Management team. - Created reports for monthly performance of solar farm.