Computer Science Graduate Student at
University of Southern California
I am currently specializing in Data Science at University of Southern California in a Masters' program in Computer Science. Over the years, I have built up a skill-set in Software Engineering, Web development as well as Mobile App development and Data Analytics.
If you want to connect for working together in any of these areas, or if you have an opportunity which you feel I can fit into, you can reach out to me.
Digital Vibes Jan'15 - July'15
Worked on developing mobile application using HTML5, AngualarJS, NodeJS and Cordova for Iphone and Android. The application allowed users to create and manage events and invite their friends to their events.
IEEE - VESIT Aug'13 - Jun'15
Managed the web development team for developing and maintaining the website for IEEE VESIT. I was also responsible for conducting various technical workshops and online events for the members enrolled in IEEE - VESIT.
EdX Oct'13 – Nov'13
Working as World Teaching Assistant for CS169.1x Course held by EDX, Work involves providing technical assistance,upgrading auto graders and solving doubts of people all around the world related to Ruby On Rails and also got to work on the auto-grader that is being used for the course.
Mobility Frame Jun‘13 – Aug‘13
Developed a management and reporting portal for the company users using HTML5 and Java for reporting and assigning task to the employees
University of Southern California Aug'15 – Present
University of Mumbai Aug'11 – May'15
This paper presents Heterogeneous Parallel Programming, which is a well-orchestrated and co-ordinated effective use of a suite of diverse high performance machines to provide super-speed processing for computationally demanding tasks with diverse computational needs. GPUs are accoutered with a much more throughput oriented design as compared to that of the CPUs thus making them a powerful alternative to boast overall performance
The paper proposes an robust anomaly detection system can be applied to any field from health to networks in order to accurately detect outliers due to the robust and adaptive nature of MCD algorithm. It uses K-means clustering algorithm combined with principal component analysis technique(PCA) and Robust MCD to build the very generalized and robust anomaly detection system.
This paper evaluates the Android platform and also proposes a framework that incorporates context-aware services along with machine learning capability in order to provide a one of a kind pattern oriented framework that not only aids in development of mobile applications but also utilizes the hardware support of sensors of the Android hardware system to utilize the full potential of the mobile platform. Finally this paper also evaluates the framework by building an application that helps to solve the transit problems arising due to potholes present in the streets of Mumbai. The application built effectively maps the locations of such potholes and helps commuters avoid such potholes and thus saves the repair costs of vehicles.
The project was to make various task easy on windows operating system. This is an application which allows user to operate the computer using speech and allows user to do daily task such as checking the weather, opening some application, setting reminders and many other tasks using speech.
Website using for recording the score and providing updates for Cricket League tournament held by Sports Club of VESIT which also included a fantasy League game for the tournament.
Using psychological models, user's digital footprint and his browser web history, the application provided users constructive insights into their personalities and also provide career choices.