Jan 2021 – May 2021 · 4 mos · Boston, Massachusetts, United States

Feb 2020 – Jul 2020 · 5 mos · Northeastern University

• Deepcharge is an universal wireless charging solution which allows for any device to be wirelessly charged using Qi compliant standards at any position on the charging pad. This pad has the ability to charge 4 mobiles/smaller devices and 1 laptop.
• 1. Porting python implementation of the Deepcharge wireless charging solution to Embedded C on an STM32F767 microcontroller.
• 2. Developing a switching logic to intelligently take care of power management.

Jun 2020 – Dec 2020 · 6 mos · Boston, Massachusetts, United States

• Upgraded the memory manager for the model simulator to a faster and more memory efficient system with quicker leak checking and heap profiling.
• Developed a parallelized version of a tool which was running serially to improve performance in regression tests with pthreads.

Jan 2019 – Jul 2019 · 6 mos · Greater Bengaluru Area

• Sandvine helps organizations run world-class networks with Active Network Intelligence, leveraging machine learning analytics and closed-loop automation to identify and adapt to network behavior in real-time.
• I worked on Internet Traffic Classification, mainly improving the recognition engine for over 150 applications on Android and iOS. Implementing different mechanisms for identifying and classifying internet data. Primarily worked on distinguishing different games and its traffic. Was part of the testing and also the software development team.

Jul 2017 – Jul 2017 · 0 mo · Bangalore

• ExpertsHub Industrial Skill Development Center specializes in providing experiential and interactive learning solutions by joining hands with anchor facilitators from Industry, research organizations and Top Academic Institutions.
• IoT based development of a Smart Parking system for Malls
• My role:
• 1. Design and Development of an Android app for booking and checking of parking slots.
• 2. Developing the Sensor network using Ultrasonic sensors and a NodeMCU.
• 3. Coding the NodeMCU based on the sensor data.