Student Projects

I am happy to advise master’s and independent study projects in CSE. Here is a list of topics I am interested in:

  • curriculum development & Software projects
    • lab and project development: “Creating labs and assignments using iPython notebooks to introduce the data science and machine learning workflow with real-world applications
    • autograder project: “Developing Gradescope autograder capabilities for cse416a and cse517a
  • research projects
    • educational research: “Sentiment Analysis for CS Education
      • Techniques
        • text mining
        • sentiment classification
        • opinion mining
        • exploratory data analysis/statistics/visualization
      • Analyzing Student Data
    • graph-based ML: applications of graph-based machine learning using graph kernels or graph convolutional neural networks
      • text classification based on graph-of-word representations
      • social network analysis
      • classification/regression tasks on biological networks
      • images and 3d objects represented as graphs

Previous and Current Projects

Predicting Student Emotions from Written Feedback using Crowd Sourcing and Machine Learning with Robert Kasumba

Capturing Student Feedback and Emotions in Large Computing Courses: A Sentiment Analysis Approach (SIGCSE TS 2021 paper, presentation) with Robin Linzmayer

When comparing the emotions students had when working on the assignments with the grades they achieved, we observe that a larger fraction of female students have significantly higher grades and a larger fraction of male students have significantly higher emotions as shown in Figure below (middle and right). This means that more female students have high assignment grades but lower emotion scores as shown in the left panel.

Text Classification with Graph Convolutional Neural Network by Walter Wang

  • This project aims to achieve traditional text classification via a Neural Network approach, where each word and document are embedded as nodes in a graph and send into Convolutional Neural Network for classification.

Mat2Py software project: We ported cse517a machine learning implementation projects and autograder from MATLAB to Python.

Sentiment Analysis on Homework Reviews by Zac Christensen

  • Some assignments (e.g. hw2 vs. hw4) are perceived better/worse than others by students:

  • Sentiment/Emotions do not (or only weakly) correlate with assignment grades:

Study of PATCH-SAN: Learning CNNs from Graph Inputs by Yufei Zhou (code on GitHub)

Boulder Finder: Discovering Boulder Areas from LiDAR Topography Data – A Detection-Classification-Clustering Approach by Eliot Padzensky 

Application of graphs to textural document categorization by Yu Sun (code on GitHub)

Graph Convolutional Neural Networks by Muhan Zhang (code on GitHub, AAAI paper)

Developing and Teaching a Course on Topological Methods for Data Analysis and Machine Learning by Brad Flynn (contact us if you are interested in the course materials)

  • The goal of the project was to design and teach a course that provides computer science students with a light understanding of topology and it’s applications for data analysis and machine learning.

Lung Cancer Detection using Convolutional Neural Networks by Jingyu Xin (code on GitHub

Exploring Deep Learning for Image Generation by Zimu Wang (code and description on GitHub