Neural Networks for Building Energy Analysis

This project is closed.

The objective of this research is to evaluate various neural networks architectures for building energy analysis and clustering. We are looking to analyze patterns in dataset such as the PecanStreet data or the UT campus energy use data. Discovering these patterns will help customize energy supply and pave the way for smart buildings and smart city applications.

Project Website
http://nagy.caee.utexas.edu
Qualifications

Qualified research assistants must meet the following criteria:
• CS/EE/ECE student or relevant coursework with applied ML/NN projects
•Proficient programmers (C/C++, Python), knowledge of ML/NN Libraries (scikit-learn, and/or PyTorch) is a strong plus
•Interest in building energy
•Responsible and timely, with the ability to work both independently and as a team
•Highly motivated, exceptional organizational skills, and extremely detail oriented
•Minimum 1-semester commitment
•Commitment of approximately 8-10 hours per week

Project Timeline

1-2 semsters

Duties

Develop algorithm
Test performance of algorithm
Compare and report resutls

Typical Time Commitment
8-10
Desired Length of Commitment
1
Tags
artificial neural networks
neural networks
smart buildings
smart cities
energy
clustering
Sign in to Bookmark
Project Lead
Who to Contact
Zoltan Nagy
Contact Email
nagy@utexas.edu

I'M INTERESTED IN THIS PROJECT. WHAT SHOULD I DO NEXT?

The Office of Undergraduate Research recommends that you attend an info session or advising before contacting faculty members or project contacts about research opportunities. We'll cover the steps to get involved, tips for contacting faculty, funding possibilities, and options for course credit. Once you have attended an Office of Undergraduate Research info session or spoken to an advisor, you can use the "Who to contact" details for this project to get in touch with the project leader and express your interest in getting involved.

Have you tried contacting professors and need more help? Schedule an appointment for additional support.