• Created APIs and infrastructure to enable machine learning model persistence, serving, versioning and customization.

• Designed a feature that allows users to create a model and reconcile two data tables that do not have an identifying primary key

• Designed no code facet blocks for preprocessing and data operations

• Set up a unit testing framework for the system

• Built a cloud data management solution on SAP Cloud Platform which used CRUD operations and supported upload features using Node JS.

• Designed APIs for image enhancement features which extracted relevant information from the images using Python.

• Designed a rich User Interface by incorporating the backend oData services using SAP UI5.

• Debugged code using SAP ABAP which needed to be transferred to the cloud services.

Designed a classifier to classify sports data obtained using wearable devices which had an accelerometer, magnetometer and gyroscope attached. The aim was to classify cricket shots based on the type of shot and the region of the field the ball might go. Used the Deep Neural Networks (DNN) classifier for multi class classification and implemented the system on python.

Developed a centralized mobile phone detector using Arduino Duemilanove (ATmega328) which detected the RF signals from the mobile phone during incoming and outgoing calls, SMS and video transmission. On detecting a signal, a buzzer was sounded and a message was displayed on an LCD screen