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Dr. Julie Johnson

Fall 2024 – Spring 2025 Project Course Descriptions

Computer Science Projects Courses for Fall 2024 – Spring 2025

Dr. Forrest Laine: CS 3892 Autonomous Vehicles

Project Duration: Half of semester

Group size: 3-4 students

Course Grade: 35% homework; 35% project; 25% midterm; 5% participation

Topics: Software for autonomous vehicles. Vehicle control and dynamics, motion planning and decision making, localization and mapping, computer vision and object tracking.

Dr. Gabor Karsai: CS 4239 Cyber – Physical Systems: Foundations and Project

Project Duration: 2/3 of the semester (including proposal, preliminary review, critical design review, final demo, documentation)

Group Size: 2 – 4 people.

Course Grade: Quizzes, homework, and midterm.

Topics:  Topics covered include:

Models of computation: finite state machines, continuous-time systems, hybrid systems, actors, discrete-events, data flow, time-triggered and event-triggered behavior

Basic analysis, control, and systems simulation: bisimulations, reachability analysis, controller synthesis, approximating continuous-time systems.

Mapping to embedded platforms: real-time operating systems, execution time analysis, scheduling, concurrency

Dr. Bobby Bodenheimer: CS 4249 Projects in Virtual Reality Design

Project Duration: Full semester (from 2nd week).

Group Size: Avg group size: 5

Course grade: Individual assignment at the beginning of semester + 5 group project milestones + final project grade + low stakes assignments throughout the course

Topics:

1. History of VR/What VR is.

2. Agile Software Development & Software Maintenance

3. Unity

4. Design of the Metaverse

5. VR Hardware

6. Modeling

7. Rendering

8. Interactions in VR

9. Audio

10. Tracking

11. Evaluation of VR

12. Business of the Metaverse

13. AR

Dr. Ipek Oguz: CS 4359 (formerly 3892) Projects in Machine Learning

Project Duration: Full semester

Group size: 3 – 5 people per group

Grade: 50% project content, 24% presentations throughout the semester, 26% class participation to projects other than their own.

Topics: Students are free on the topics. It has ranged from typical things from computer vision and NLP to more creative things like games, music, and the stock market.

Dr. Daniel Moyer: CS 4269 Project In Artificial Intelligence

Project Duration: Brainstorming/example project for 3 weeks, ending with a pitch day Project development phase (doing the actual work on the project) for 11 weeks, ending with presentation day Writing phase (final write up) 1 week (could be smaller, depends on presentation day scheduling)

Group size: Plan on 4. Min 3, Max 5.

Course Grade: Pitch slides (2 slides 1 minute max), Formal Project description (“what are you working on and how will you tackle it”), Weekly updates (1 page per group, what did you do this week toward your goals), 2 in-person updates (rolling, during the development phase). These are all project-related grades, but they’re meant to structure progress.

Topics:

  1. an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics
  1. an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, and economic factors
  1. an ability to communicate effectively with a range of audiences
  2. an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental and societal contexts
  1. an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives
  1. an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions
  1. an ability to acquire and apply new knowledge as needed, using appropriate learning strategies

Dr. Jules White: CS 4279 Software Engineering Project

 Project Duration: Full Semester

Group Size: 3-4

Course Grade: 100% project

Incremental demos, project plan, final presentation

Dr. Vikash Singh: CS 4287 Principles of Cloud Computing

Project Duration: Half the semester.

Group size: Average group size is 3-4 students.

Grade: Project (group)- 30% / Programming Assignment (3 group work) – 30% / Homework (2 individual) – 10% / In-class activities (Individual/group) – 14% / 2 exams (Individual) – 16% / There is no final exam.

Course Topics:

  • Definition of cloud computing from NIST
  • Service Offering Models of cloud computing (IaaS, PaaS, SaaS, and various other emerging forms)
  • Refresher of selected topics from Computer Architecture, Operating Systems, and Computer Networks
  • Cloud Programming models, Client-to-cloud interface, and protocols
  • RESTful interfaces, cloud-based application hosting, etc.
  • Cloud management infrastructure, e.g., OpenStack, at a level needed to understand. the interface to the cloud and application programming.
  • Resource virtualization of CPU, networking, memory, and secondary storage.
  • Containers – Dockers, Linux; resource scheduling.
  • Cloud packaging and deployment technologies, e.g., Vagrant, Ansible, Docker Swarm.
  • Communication networking technologies for cloud, e.g., software-defined networking and network function virtualization
  • Autoscaling and elasticity concepts and algorithms
  • Tail Latency and Performance issues, including performance interference.
  • Trends in Cloud computing: Fog/Edge Computing, Cloudlets, Internet of Things.
  • Serverless computing (e.g., AWS Lambda)
  • Application models for the Cloud (e.g., MapReduce, Stream Processing, etc).

Dr. Graham Hemingway: CS 4289 Project in Web-Based Software Architecture

Project Duration: Full semester.

Group Size: Groups are 3-5 students, chosen by the students.

Grade: 50% is my evaluation of the student’s individual contributions.  30% is peer feedback from their teams.  20% is one topical lecture that students have to present to the class.

Here is an outline of our schedule:

  • Week 1 (1/8) – Plan & Pitch
  • Week 2 (1/15) – Architect – Tech Stack & Overall User Flow
  • Week 3* (1/22) – Architect – User Flow Details & Screen Mockups
  • Week 4* (1/29) – Prototype
  • Week 5* (2/5) – Prototype
  • Week 6* (2/12) – Prototype
  • Week 7* (2/19) – Build
  • Week 8* (2/26) – Build
  • Week 9* (3/4) – Mid-Point Presentations
  • Week XX (3/11) – Spring Break
  • Week 10* (3/18) – Build
  • Week 11* (3/25) – Build
  • Week 12* (4/1) – Build
  • Week 13* (4/8) – Build
    • Posters Due for Printing 4/??!
  • Week 14* (4/15) – Build
  • Week 16 (4/22) – Final Presentations and Derby Day

* Means there is a topic presentation on the Monday of that week.