Natural Language Processing (NLP)

Project Overview 

Natural Language Processing (NLP) is a growing topic of research in the machine learning field. NLP allows computers to understand human language using statistical analysis. The goal of this project is to create a system using NLP models to evaluate survey responses. This would give professors valuable feedback from free responses end of semester survey questions by identifying common themes in student responses. We are combining a variety of pretrained models and established machine learning principles to group similar free response questions together. Currently we are working on gathering requirements to help inform a roadmap for the development of our tool. It is not clear what features faculty members would find the most useful, so we are working on interviewing professors to get a sense on the best approach. This supports our long term goal of making a tool that can extract meaning from student survey responses. We hope this will make student feedback more accessible and frequent for professors.

Objectives 

  1. Determine User Requirements
  2. Revamp Infrastructure

Major Tasks 

The major tasks of the project are outlined below. These are nominal and are likely to change somewhat throughout the course of the year. These are meant to illustrate the general nature of the work that the position entails.

  1. Investigate new technologies and ideas for the tool
  2. Evaluate the current system and ensure everything is functional
  3. Develop front-end system

Open Positions 

Preferred Skills and Interests 

  • Interests / experiences in machine learning subtopics like clustering, sentiment analysis, dimensional analysis
  • Beginning/Intermediate Data Science Experience (e.g. Iris Data set run through)
  • Experience with Data Visualizations (matplotlib)
  • Front-End Development
  • Collaborative coding development experience (e.g. git, docker)

Preferred Academic Years 

  • Looking for First-year/Sophomore/Junior level students  

Preferred Majors

  • CS
  • CpE
  • EE
  • CMDA
  • Statistics
  • Education

Supportive Courses (helpful but not required)  

  • CS/CMDA/STAT 3654/4654
  • CS 1064/2064/ 2104 (for the python experience)
  • Linear Algebra (math concepts for machine learning)

How to Apply 

Applications will be reviewed by Dr. Gray and by continuing researchers on the team.  After a review of the application, our team will contact candidates to schedule an interview (likely to be conducted via zoom).  Review for the positions will be conducted over the 2024 Summer break starting around 7/14/24. Please complete the MS Form, uploading the following documents:

  • A brief (~1 page) essay or cover letter explaining which of the projects you are interested in, and why you think you might be a good fit for that project (or those projects).  If you are applying for multiple projects, extend your essay a little and describe your interest and qualifications for each position.  Be sure to let us know your major and where you are in your academic career (sophomore, junior, etc.) 
  • A resume outlining your work experience and education 

Please reach out to Dr. Gray (dagray3@vt.edu) if you have any questions or concerns. 

See All Projects
Student Responsibilities
Apply Today