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Volunteer with the following CS Professors:
Dr. Beaty has several research projects. There is work on any of these for undergraduates. It’s also possible to present at https://www.msudenver.edu/undergraduate-research-creative-scholarship-program/undergraduate-research-conference/.
- A lightweight, “perfect interaction” honeypot. It is written in Python and uses Docker, and can be found at https://github.com/drsjb80/HPotter. There is lots of work that can be done including the following:
- Improving the firewalling code
- Adding to unit and system tests
- Fixing the ssh and telnet clients
- Easing deployment
- Centralized threat posting
- Improving the firewalling code
- A Java DNS server. DNS is an essential part of the internet and has had numerous flaws through the years. See https://github.com/drsjb80/JDNSS.
This DNS server does a lot including MDNS, TLS, and DOH. Some work that needs to be done includes the following:
- Adding JSON DOH
- Adding to unit system tests
- A dark web spider that looks for signs of human trafficking. Source at https://github.com/drsjb80/darkenigma. The following needs to be done:
- Create a MongoDB implementation in addition to the ElasticSearch currently being used
- Add Mongo Compass for easier searching
Please email [email protected] if you are interested in any of these.
Projects/Research
For interested MSU students there are a few projects available to work on. There may be funding available to work on these, depending on the semester, but there is always the opportunity to extend these into a research project that can be published in The Rowdy Scholar or presented at the Undergraduate Research Conference. Most of these projects revolve around Computer Science education or improving education with technology (yes, getting students into the computer science pipeline is another issue, but one which I haven’t delved into yet).
1. Improving student success rates in CS courses
This project is broad in scope and involves analyzing data and developing/implementing tools to help students to learn more effectively in core CS courses using Continuous Assessments (e.g. weekly quizzes) and Peer Instruction (e.g. in-class tasks/assignments completed by pairs or small groups of students working together). Given the broad scope, it’s possible to focus entirely on just one of the following.
- Creating content for continuous assessments (e.g. quizzes) – create a library of quiz content on specific core CS topics at varying levels of difficulty to help students learn core CS concepts
- Carry out (reproducible) data analyses – this is a Data Science type of task that involves writing Python code/notebooks to collect and analyze quiz/exam data (from Canvas); the two main parts of this task are 1) collecting the data, mostly via the Canvas API, and b) running statistical analyses on the data; an early version of this can be found at github.com/sgeinitz/picata
- Implementing communication tools – this final task is to help automate the process of selecting pairs/small groups of students and given them a brief quiz/assignment, with a longer-term goal of offering students personalized study tips/guidance in a course; this will likely involve the creation of a chatbot or similar messaging tool
2. Natural Language Processing
This project is about applying deep learning models to textual and sequential data with one a specific use-case of analyzing open-ended responses to surveys/quizzes. However, the possible applications of NLP are vast so if you are interested in applying NLP to another domain that is a possibility as well. For example, one other project in this area is to utilize an existing large language model (e.g. BERT) and fine-tune it to be used as a ‘Course Assistant’ in a CS course. This may include aspects of the third task above (e.g. implementing an MS Teams chatbot).
3. General Data Science/Machine Learning
Although not an explicit project, if you are interested in competing in Kaggle competitions, or have some other Data Science or Machine Learning task that you would like to tackle but need some additional help, then feel free to reach out for consulting and possible mentorship.
Please email [email protected] if you are interested in any of these or for more information.
Dr. Jiang has been working on research projects on Computer Vision. Machine Learning. AI Tools for Education and Intelligent Agriculture. (See also, https://www.fengjiang8.com/blog )
Students who are interested in these areas can email [email protected] to schedule a meeting/interview.
Dr. Mota research interests are in the areas of data mining, database systems, programming languages, and cloud computing. Below are some projects that he is currently working on and that can involve motivated students who are interested in engaging in research activities.
Exploring Anti-Asian Racism on Twitter
Which types of threat perceptions appear in the racism-infused tweets against Asians reveal in the unique context of the COVID-19 pandemic? What drives harmful tweets to go viral? These are some of the questions that this research project aims to answer.
Skills: API, NoSQL databases, Python, NLP (Natural Language Processing), and statistics.
A Framework for Collaborative Recommendation Systems
Collaborative recommendation systems try to suggest products or services based on the degree of similarity between users. The goal of this project is to develop a framework that can be easily adapted to different recommendation systems based on databases available on the internet, such as Goodreads, Yelp, Tripadvisor, IMDb, among others.
Skills: API, web scraping, graph databases, Python, ranking algorithms, and statistics.
Data Mining Pipeline Architectures
When it comes to building data mining pipelines, there are many options available, from simple pipelines with small datasets that can fit in memory to more complex pipelines with real-time generated data simultaneously analyzed by different processes using cloud computing tools. Students working on this project will have the opportunity to study different data mining pipeline architectures using cutting-edge tools and techniques to solve real-world problems.
Skills: cloud computing, data mining, databases, programming languages.
Please email [email protected] if you are interested in any of these or for more information.
Partnership for Equity: STEM (P4E:STEM)
Cultivating Inclusive Professional Identities in Engineering and Computer Science
https://partnership4equity.org
The P4E:STEM project seeks to cultivate inclusive professional identities in engineering and computer science students through curricular design and implementation. Inclusive professional identities prepare students to be aware, skillful, and mindful when engaging in endeavors associated with their chosen disciplines.
Key characteristics of inclusive professional identities addressed by P4E:
- competence in applying disciplinary knowledge, skills, and abilities
- appreciation of how diversity strengthens a discipline
- ability to act in inclusive ways and create inclusive environments
- consideration of an endeavor’s impact on diverse populations
In this project, diversity and inclusivity are contextualized by the engineering and computer science academic disciplines and those undertakings and professions that draw upon students’ educational experiences in the disciplines.
The P4E:STEM project adopts a broad definition of diversity that encompasses a wide span of demographic characteristics, with emphasis on those commonly associated with underrepresentation, marginalization, and discrimination.
Redistricting Investigation [open source]
Experimentation with geopolitical redistricting by computer
https://metrocs.github.io/redistricting/
The Redistricting project provides a library that supports investigations of splitting a geographic region into election districts and the development of tools that:
• Educate the public on the process of redistricting;
• Demonstrate redistricting by automating the process based on given parameters reflecting a desired outcome;
• Demonstrate how redistricting can be used to establish an advantage for a political party or group (Gerrymandering); and
• Facilitate incrementally adding functionality to redistricting modeling capability.
The initial scope is a Java package that provides utilities for building programs that investigate redistricting scenarios.
The expanded scope includes a user interface for redistricting scenario exploration.
Stakeholder identification:
• Users (public, students, programmers [novice & experienced])
• Educators (instructors, mentors, tutors)
• Maintainers (project developers, maintainers, quality engineers)
ImageLab [open source]
A framework and application for beginning programmers to develop and experiment with image modification
https://metrocs.github.io/imagelab/
ImageLab is a framework and application that allows students to develop image modification processors (filters) and to experience the results visually and musically.
The ImageLab product is intended for use in beginning programming courses (such as CS1050 at MSU Denver).
The interactive ImageLab application is provided as Java source code as well as an executable JAR file.
Quality Tools for BlueJ [open source]
Affording access by beginning programmers to quality-assessment tools
https://github.com/MetroCS/QualityToolsForBlueJ
This effort provides an extension to BlueJ (an IDE for students learning how to write programs) that affords access to quality assessment tools.
The initial deliverable encapsulated Checkstyle to validate adherence to coding conventions.
The project continues to update and expand the set of source code analysis tools.
JBoxes [open source]
An interactive foundation for explorations about programming in Java and other computer science concepts
https://metrocs.github.io/jBoxes/
The main goal of the jBoxes software is to provide learners with a semantic model for a Java-like language—a detailed, concrete conceptual picture of how the computer behaves when it performs the instructions given to it in a program.
jBoxes is the brainchild of Dr. Gerald Shultz, Professor Emeritus at MSU Denver. It has been transformed into an open source software project under the purview of MetroCS.
The project includes the interactive jBoxes application (C++) along with an associated book and reference guide.
Please email [email protected] if you are interested in any of these or for more information.
Learning Analytics and Educational Data Mining
The learning analytics pilots: Identifying and exploring actionable sources of data and building computational tools with analytics to address identified problems at micro (individual), meso (departmental) and macro (institutional) level.
Current Project: Teaching with Analytics – Visualizing Discussion Board
Building a visualization tool for discussion boards in Canvas to improve the student feedback system using text analytics, NLP and data visualization.
1. Building a basic text analytics models for content similarity from unstructured data.
- Data collection and preprocessing.
- Comparing different text analytics algorithm for content similarity.
- Visualizing discussion content.
2. Building a basic text analytics models for self and shared regulation from unstructured data.
- Data collection and preprocessing.
- Classifier models for thematic code categorization.
- Comparison of computational linguistic feature extraction models
- Visualize regulations.
Please email [email protected] if you are interested in any of these or for more information.