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I worked as part of the Data Enrichment Platform team to develop innovative solutions for product data classification and data cleansing. This leveraged Machine Learning methods as well as heuristics-based techniques. A microservice architecture built on Python-FastAPI/React was used to make the system extendable and usable by external teams.Prior to this, I worked on creating an ETL pipeline for data migration and contributed to the back-end of a portal that simplified the workflow of… Show more I worked as part of the Data Enrichment Platform team to develop innovative solutions for product data classification and data cleansing. This leveraged Machine Learning methods as well as heuristics-based techniques. A microservice architecture built on Python-FastAPI/React was used to make the system extendable and usable by external teams.Prior to this, I worked on creating an ETL pipeline for data migration and contributed to the back-end of a portal that simplified the workflow of product induction for suppliers. Show less

Did my internship on perception of simulated auditory source width expansion with Dr. T.V. Sreenivas and Aarthi S and co-wrote an IEEE paper on the same.

My responsibility was to develop algorithms and code certain modules for a smart metering project to implement functions like Time of Use metering, Maximum Demand, RTC-UTC conversion, Load Survey and Tamper Proofing. The coding was done in embedded C.I also prepared a comprehensive report which dealt with the fundamentals of energy metering and included the algorithms I worked on. This report was later adopted as the training manual for new recruits.

I interned at Zenmeter solutions from May 20 - July 3, 2015. As part of the project, I developed software modules for smart metering and worked with a RENESAS microcontroller. I also learned about several communication protocols including the ZIgbee protocol for radio communication. I prepared a 90 page report on the fundamentals of metering at the end of the project.