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Aug 2014May 2016

MS, Computer Science

Indiana University, Bloomington                                       GPA:3.63/4.00
Aug 2007May 2011

BEng, Electronics and Telecommunications

Priyadarshini College of Engineering, Nagpur              GPA:3.60/4.00

Work experience

Jun 2015Present

Web Developer [C#, ASP.NET, MVC, Agile, JavaScript, jQuery]

Indiana University, Bloomington
  • Developed application-wide error logging component for, enabling efficient issue tracking and resolution
  • Developed a customer on-boarding component that generates service requests and send emails to concerned team facilitating convenient customer on-boarding
Feb 2012Jul 2014

Software Engineer [C#, ASP.NET, Agile]

Infosys Limited, Hyderbad
  • Developed an efficient system that fetched real-time GPS data of on-field technicians every 5 minutes and displayed them on map
  • Was responsible for the system design and entire back-end development
  • The project helped the client to save around $10,000 every quarter


Bot or Not [Java, MySQL, R, WEKA]                                                                                                      Implemented various classifiers like ID3, Logisitic Regression and Naive Bayes to identify bot bidders using the bid information of around 7.5M instances

Predicting usefulness of Yelp reviews [Java, Lucene API, MongoDB, WEKA]                                     Created a retrieval model which can predict the business categories and usefulness of a Yelp review. Used Linear Regression and SMOReg to predict the number of votes a review can get

Reinforcement learning [Java]                                                                                                                     Built a fully and partial observable domain for an agent, which learned an optimal policy to reach the goal state using Value Iteration and Q-Learning

Malware classification [Java, MySQL, R]                                                                                              Developed an effective machine learning model using Random Forest to classify nearly 11000 malware files (500 GB of assembly code files) into 1 of 9 malware families

PageRank using Hadoop map-reduce [Java, Hadoop, Map-Reduce]                                            Created a URL ranking application using hadoop, map-reduce and PageRank algorithm

Clustering of movie-lens dataset [Java, MySQL, R]                                                                        Constructed an unsupervised learning model using Agglomerative Clustering to derive an effect of age and profession of the users on the ratings they give to movies of various genres

Bit-Torrent Client [C++]                                                                                                                                   Implemented Bit-Torrent protocol to build a multi-threaded Bit-torrent client application, capable of sharing files of various formats among multiple peers over the network