Supradha Ramesh

Recommendation for Anomaly Detection and Prediction with machine learning algorithms - Automated selection of best-suited data mining/machine learning algorithm on uploaded temporal data(time-series). The prototype application works and the pipeline of pre-processing, feature-extraction, transformation and model selection and hyper-parameter tuning. Datasets were Smart Home, Smart cities, Equipement monitoring and health sensors.

Project: UniversAAL, Dynamic alarm triggering based on emergency events from smart home data. Improved networking protocols (SIP protocol) implementing hand-free emergency and alarm notification features.

Working in IoT predictive maintenance team. Have acquired various insights on SAP HANA and other services. Rolled out automation of translation service with the help of Jenkin pipelines.

Area P&I which responsible for the Development and Cloud Delivery of all on-demand solutions and provides customers and partners with services across the full HCM Cloud portfolio which includes SuccessFactors BizX Suite, Learning Solution, Analytics. Verification and optimization the data from different sources including contract management which is a key factor to enable optimization of operations costs. Automation of data center deployment and Data clean up activities including, mapping and swapping etc.

Distributed Systems And Algorithms. Ubiquitous/Mobile Computing. Concepts and Technologies for Distributed Systems and Big Data Processing Deep Learning Business Intelligence and Data Warehousing Peer to Peer Systems and Applications. Network Security

Neural Networks. Object-Oriented Programming Concepts. Distributed database systems. Theory of computation. Operating systems.