Check out some of my projects on my GitHub profile or on DevPost!


  • Created a poetry translator: input a prose sentence, and it translates it into a more “poetic” version of the sentence
  • Final project for CSE 390: Natural Language Processing
  • Used NLP and machine learning techniques such as Dependency Parsing and K-Nearest Neighbors classifier
  • Used Stanford Lexicalized Parser to create training and test sets
  • Python 3.5 in Eclipse PyDev
  • Code


  • Created a stock trading website as final project for class (CSE 305: Principles of Database Systems)
  • Had to support 3 different types of accounts, all with different functions
  • Buy/sell stocks, manage account information, see stock price history, implemented stop prices
  • Set up an Apache Tomcat 8 server through Eclipse
  • MySQL, Java, JSP, JDBC, HTML, CSS using Eclipse, MySQL Workbench
  • Code

Architecture Analysis

  • Wrote a method to calculate the Core size of a system, based on cyclic dependencies among components
  • Also added the ability to calculate propagation cost with and without self-dependencies
  • Includes a runner for JDepend, in order to calculate metrics
  • Done as part of my work at Applied Visions, Inc. in researching software architecture and quality analysis
  • Written in Java; used jDSM, jBLAS, JDepend, and DependencyFinder libraries
  • Code


  • Created a quick application that analyzes input text for sentiment in order to determine emotions
  • Used Python3.4 and TextBlob, a natural language processing Python library
  • User types in text, and my program determines whether the emotions in the text are “positive,” “negative,” or “neutral”
  • Uses built-in sentiment analysis tools in TextBlob
  • Done at Unhackathon 2015 by the Stony Brook Computing Society
  • DevPost Page

Sentiment Analysis Class Project

  • Trained a classifier to determine how positive a movie review was on a scale of 0-4
  • Worked in a group of 3 people
  • Used Python, scikit-learn, and nltk
  • Cleaned the training reviews with nltk and used scikit-learn to create a vocabulary for the bag of words model
  • Used the vocabulary to train the Naive Bayes classifier to determine the sentiment rating of a given review based on probability
  • Compared our Naive Bayes classifier to one provided in the scikit-learn package
  • Code

Machine Learning Neuron Implementation

  • Implemented a neuron that learns the outputs of logical functions
  • Used Python and the PyDev environment in Eclipse
  • Done at Unhackathon 2014 by the Stony Brook Computing Society
  • Won first place in the “Most Learning for a Hack” category
  • DevPost Page

Operations Research Senior Project

  • Learned about the basic concepts of Operations Research from a textbook
  • Used Java to code a solution to an optimization problem