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Computer Science Professional Experience

Columbus, Ohio, United States
January 22, 2018

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Seeking a full-time job which will lead to opportunities in the field of Computer Science by enhancing my technical skills.


Master of Science, Computer Science: GPA: 3.8/4.0; 2016-2018 University of North Carolina at Charlotte.

B. Tech., Computer Science and Engineering: GPA: 3.7/4.0; May 2016 Jawaharlal Nehru Technological University, India.


Programming Language: C, C++, JAVA, PHP, Python, Scala.

Database: MySQL, ORACLE, PostgreSQL, MongoDB.

Scripting: HTML 5, Java Script, CSS 3.

Machine Learning Frameworks: Scikit-learn, Tensorflow.

Big Data Frameworks: HADOOP 2.6.5, Spark 2.0.2, PIG, HIVE, HBASE, OOZIE, KAFKA, SQOOP, MLlib

Good understanding of SAS, R, Octave.

Visualization tools: Tableau


Big Data Analytics, Cloud Computing, Database Systems, Machine Learning, Artificial Intelligence. PROFESSIONAL EXPERIENCE Jan 2014- Feb 2015

Co-founded a non-profit organization called OpenBlood and developed a website called which enables the users to find blood donors when required.

Worked as database administrator and developed the backend of the platform using PHP. CERTIFICATIONS:

Oracle certified JAVA SE 6 Programmer (OCJP 6)


Collaborative Filtering with Bayesian Classifier for Movie Recommendations using Spark Dec 2017

Developed a Bayesian Classifier using Spark in Python interface that could recommend a movie to the user based on the ratings given by the user to similar movies and the ratings received for a movie.

Dataset used - MovieLens 100k

Technology - Python (NumPy, SciPy), Apache Spark Multiple Linear Regression using Spark Nov 2017

Implemented multiple linear regression using the closed form expression for the ordinary least squares estimates of the linear regression coefficients computed using summation. Google Page Rank Algorithm using Map Reduce Oct 2017

Implemented the Google’s page rank algorithm on the Wikipedia corpus using Hadoop map reduce. Information retrieval using TFIDF in Map Reduce Sep 2017

Developed a search engine that could query through thousands of documents. Implemented TFIDF by combining term frequency (TF) and inverse document frequency algorithms in Hadoop map reduce. CIFAR 10 Image Classification using Convolutional Neural Networks April 2017.

Implemented and analysed CIFAR 10 dataset for Object Detection and Image Classification using various algorithms: KNN, Artificial Neural networks and applied PCA before applying the technique of neural networks.

Later, have implemented the same on Convolutional Neural Networks (Custom CNN & AlexNet architecture) and analysed that CNN outperforms other traditional methods. Sentiment analysis on Amazon Baby Products Dataset Jan – Apr 2017

Implemented and analysed various algorithms for Sentiment Analysis for the Amazon Baby Product Dataset, where the algorithms learn to analyse various reviews and classify them to one of the five categories of 1 to 5 as part of our Machine Learning course.

Algorithms include: Decision Tree, Artificial Neural Networks, KNN, Adaboosting, SVM and Naive Bayes classifier. Implemented the above listed algorithms using scikit-learn in Python. Eight Puzzle Problem, N Queens Problem, Unbeatable Tic-Tac-Toe game (AI) Nov - Dec 2016

Implemented various AI search algorithms and Game playing agent using MinMax algorithm with cut off and alpha-beta pruning in JAVA.

Report generation using SAS and comparison of results with R Oct - Dec 2016

Developed a sales report in SAS for a shoe company using a dataset present in the SASHELP directory and compared the results with the reports generated using R. Phi Beta Lambda (E-Commerce website) Sep - Dec 2016

Developed an e-commerce website as a part of the Database Systems term project.

Designed and developed the entire database in MySQL with backend PHP.

Implemented advanced database concepts like triggers, sub procedures, advanced views and events. Binarized Text Recognition March 2016

Developed an android application which recognizes and extracts the text present in an image and saves the text onto a file.

Integrated Tessaract OCR and TTS engine with the application. Heart Disease Categorization July 2015

Developed a neural network using octave which categorizes the type of heart disease a person can get based on the data from Cleveland hospital.

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