1. Tejasvee Bolisetty
988 139th AVE NE, Bellevue, WA | +1 (248) 971 3122 | txb140830@utdallas.edu
https://www.linkedin.com/in/tejasveebolisetty | http://github.com/tbolisetty | http://kaggle.com/tbolisetty
Objective
Seeking Full time opportunities in the field of Software Development/Data Science to leverage my Machine Learning and analytics skills
Education
Master of Science in Computer ScienceTheUniversity of Texas at Dallas, Richardson, Texas, USA May 2016 | GPA: 3.80
Bachelor in Computer Science and Engineering Mumbai University, Maharashtra, India May 2011 | GPA: 3.75
Technical Skills
Languages : Java, Python Machine LearningTools& Frameworks : R,Spark MLlib, word2vec, NLTK
Database : MySQL, MSSQL Big Data Frameworks : Hadoop, Apache Spark, Pig, Hive
Web : HTML, CSS Others : AWS, Git, JIRA, Springs Framework
PROFESSIONAL EXPERIENCE
Software Developer Intern, Sabre, Southlake, TX, USA May 2015 – August 2015
 Designed and developed UI module for reporting service of Crew Manager X application
 Designed a framework for providing access to all types of crew management reports according to their roles
 Used REST V2 web services to make useful calls to implement some critical reporting functionalities between client and Jasper Server
 Used Jasper Reports Server framework to create domains for database to directly get data instead of using Hibernate
 Used Jasper soft Studio to design and generate various types of reports according to the requirements
 Used Spring Framework for integrating the reporting module with the application for quicker access
Software Engineer, Larsen and Toubro Infotech, Mumbai, India March 2012 – July 2014
 Designed POC for DCP Midstream Company for managing larger scale data and maintaining logs
 Collected client requirement, designed database and developed a web application for Room management for Learning and
Development department of L&T Infotech
 Handled and supported SAP Master Data for Chevron Corporation’s downstream business units in North and Latin America, Asia
ACADEMIC PROJECTS
Prediction of Rating using Reviews of Yelp Dataset Challenge (Python, Word2Vec, and Spark Deep Learning, Gradient Boosting) Fall 2015
Developed a model to predict users review ratings and classify words used by Yelp users by reducing the variance and avoiding
overfitting of the model. Used Google Word2Vec to generate feature vectors and h20, Spark MLlib to build ensemble models
Stock Market Monitor (Java, AWS RDS, Sparkjava, JavaScript) Spring2016
Developed an application to monitor user specified stocks and expose RESTFul API with following features:
Adding a company, deleting a Company, list all user companies, showing history of the selected company
Simple Search Engine based on Spatial relevance model (Java, Python) Spring2015
Collected spatial data by crawling the webpages and formed Index Construction, Compression and Document Ranking.
Used Stanford CoreNLP package and removed synonyms for Compression. Used Java for modeling and document ranking.
Asynchronous Distributed Minimum Spanning Tree (Java) Fall 2014
Constructs a Minimum Spanning Tree (using Asynchronous GHS algorithm) in an asynchronous distributed computing environment.
This is developed using the multi-threading in Java.
RESEARCH PROJECT
Home Automation (IoT) (Java, Python, Raspberry PI) Fall 2014
Worked on an open source home automation system with Raspberry PI under the guidance of Prof. Venkatesan, S.
Developed an application module for easily and seamlessly connecting Raspberry PI wirelessly with home router.
KAGGLE DATA SCIENCE COMPETITIONS
WALMART: Customer Trip Type Classification Dec 2015
Model: Feature Engineering + Extreme Gradient Boosting (Xgboost)
HOMESITE HOME INSURANCE: Customer Quote Selection (Donein a Team) Feb 2016
Train Data Set Size: 200 MB (1 file with anonymized features for Quote Conversion flag)
Generated around 100 + Features through given anonymized features, Applied Models: Extreme Gradient Boosting (Xgboost) + K-Means
RELEVANT COURSE WORK
Machine Learning, Big DataManagement& Analytics, Distributed Computing, Design& Analysisof Algorithms
InformationRetrieval, Statistical Methodsin Data Science, Implementationof AdvancedData Structures& Algorithms