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Prajval Bavi

Graduate Student
at
Univeristy of North Carolina, Charlotte

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About Me

Currently Masters Student in University of North Carolina, Charlotte.
Actively looking for Summer Internship opportunities in Machine Learning and Data Science.
Currently Working on developing a model for Insurance Fraud Detection using Semi-supervised Machine Learning.
Experienced Senior Member Of Technical Staff with a demonstrated history of working in the Wireless industry.
Skilled in Python, Java, C and Shell Scripting.

Experience

Mojo Networks

Senior Member of Technical Staff

  • Designed and built statistical models and feature extraction systems for gaining insight into Access Point Performance and predict various parameters which have impact on performance.
  • Used models and dashboards to give insight into Access Point Performance and communicated these problems and possible solutions to stakeholders.
  • Developed framework for automation of throughput measurement and to analyze the performance of the Wave1 and 2 Access Points helping improve team efficiency by 50% in generating reports and debugging.
  • Developed framework using MATLAB and Agilent Signal Generator to emulate different noise based environment for testing robustness of Access Points helping company save $10K in Licensing fees.

Cognizant Technology Solutions

Programmer Analyst

  • Developed website application using J2EE, Servlets and JSP under Apache Struts Framework.
  • Developed a tool to automatically generate and send mail’s to Customer as soon as issue was resolved by team leading to speed improvement in responding to the Customer’s by 25%.

Education

University of North Carolina at Charlotte

Aug 2017 - May 2019

Master of Science in Computer Science (GPA - 3.7)

Courses Completed/Taken

University of Pune

Aug 2009 - May 2013

Bachelor of Engineering in Electronics and Telecommnunications (GPA - 3.8)

Courses Completed

Projects

Urban Analytics Platform

Building model for Urban Analytics involving collecting data from different sources such as weather forecasts, traffic data, social media data and collectively synthesizing this data towards predicting and making improvements towards traffic flow in the city of Charlotte.

Insurance Fraud Detection

Building a model to classify Insurance claims as fraud using Semi-supervised Machine Learning.

Tic Tac Toe

Implemented a general game-playing agent for two-player deterministic games, using (1) minimax with alpha-beta pruning, and (2) minimax-cutoff (i.e., with cutoff test to replace terminal test and with evaluation function to replace utility function) with alpha-beta pruning. Applied it to the planar 3*3 Tic-Tac-Toe game and extended it to the planar n*n (n > 3 and n is odd). Has a friendly graphical user interface to allow a human user to play the game agaist the algorithm

GitHub

Skills

Tools

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