Yogesha Suresh Kudwalli

Working on Master thesis titled 'Model learning: Causal Inference on time series data'. Goal is to apply deep learning on time series data to obtain the underlying systems' network structure and dynamics and be able to perform Causal inference. Such a model is intended to be used to run simulations to perform prophylactic anomaly detection and optimize the structure for efficiency and cost of running.

Supported the activities of SAP Cloud Platform BIG Data Site Reliability Engineering team.

Exploratory analysis of Genetic algorithms library 'Jenetics' to model the evolutionary algorithm for Machine learning based automated UI test generation and optimization framework.

- Worked as full stack developer on Informatica Data Integration Hub. - I had been instrumental in 3 major incremental releases of the product. - Contributed to integration with Kafka, Hadoop and Informatica BDM, InstallAnywhere based installer improvement and optimization, Support for

Projects: 1) SAP CPI (Cloud Platform Integration) Node Manager 2) Adapter SDK for SAP CPI 3) Onebuild Tool

Project : SAP CPI (Cloud Platform Integration) - Worked on Node Manager for ESB nodes on cloud which handles lifecycle, health check, failover of such nodes.

- JUnit adpater and eclipse view for Rational Quality Manager - Performance profiling of rational Functional Tester.

- Very Deep Learning - Machine Learning -Applications of AI - Collaborative Intelligence - Embedded Intelligence -Document Analysis - Computer Vision -Multimedia Data Mining -Data Visualization -Computational Geometry -Visual Analytics -Perception -Middleware -Verification of Reactive Systems

Algorithms, Data Structures, Computer Networks, Data Mining, Artificial Intelligence, Compiler Design, Operating Systems, Engineering Mathematics