👋 Welcome to IEL

IEL advances science, engineering and education towards…

…an intelligent and human-responsive energy infrastructure in the built environment.

The Intelligent Environments Laboratory (IEL), led by Prof. Zoltán Nagy, is an interdisciplinary research group in the Department of Civil, Architectural and Environmental Engineering (CAEE) at The University of Texas at Austin.

IEL advances science, engineering and education towards an intelligent and human-responsive energy infrastructure in the built environment. We develop methods in Machine Learning (Supervised, Unsupervised and Reinforcement), Internet of Things, Data Analytics and System Integration/Deployment, with applications in Occupant-Centric Building Design and Operation and Grid-Interactive Smart Communities.

Latest News

CityLearn Challenge featured on Cockrell School news

Check out The Quest to Use AI to Make Buildings More Efficient here: https://cockrell.utexas.edu/news/archive/9629-the-quest-to-use-ai-to-make-buildings-more-efficient

Last updated on Jan 23, 2023 1 min read

New paper on Machine Learning and IAQ

Machine learning seems to be everywhere these days. But how does it perform in predicting indoor air quality or sleep quality in individuals? Our new paper led by Hagen Fritz and Mengjia Tang explores common algorithms and their performance for this task.

Last updated on Dec 10, 2022 1 min read

CityLearn Challenge 2022 - Winners Announced!

🏆And here are the winners! Please join me in congratulating the winners of the CityLearn Challenge 2022: 🥇1st Prize ($8000) Team Together (Alibaba Group, China) 🥈2nd Prize ($5000) Team ambitiousengineers (University of Washingtonand University of Hawaii at Manoa, USA)

Last updated on Dec 8, 2022 2 min read

CityLearn Challenge 2022 @ NeurIPS22

👋👋👋 🏆 Please join us when we announce The CityLearn Challenge 2022 winners ($15,000) at NeurIPS 2022 in an online workshop (Dec 7th, 2022, at 8:00am EST). 🥇🥈🥉 We had over 600 participants 👩🏽‍💻🧑‍💻👩🏻‍💻👨🏾‍💻from 50+ countries🌎🌍🌏, competing in developing the best battery scheduling algorithm for 17 single family homes without seeing the data for some.

Last updated on Dec 5, 2022 1 min read

Are We Ready for Artificial Intelligence in Building Design?

Dr Labib and Dr Nagy talk with ASHRAE Journal Editor John Falcioni on the opportunities and challenges that come with artificial intelligence/machine learning in building design and operations. They also discuss the questions facing the industry in accepting these new tools and the difficulties in preparing the next generation of AI-savvy engineers.

Last updated on Nov 13, 2022 1 min read

Reinforcement Learning for Energy Management in Buildings and Cities (RLEM22)

And that’s a wrap for #RLEM22 #BuildSys22 ! We had a great workshop with around 40 participants from all over the world on the challenges and opportunities of building controls. If you missed it, here is the raw uncut version (~4 hours):

Last updated on Dec 5, 2022 1 min read

IEL @ BuildSys22

⁉️How can we use past data to generate synthetic data to improve our learning controllers 🤨? ‼️Check our our paper led by Marta Fochesato (ETH Zürich) and Fazel Khayatian (Empa) at ACM BuildSys'22 tomorrow (Nov 10).

Last updated on Dec 5, 2022 1 min read

Seminar talk at CU Boulder

Dr Nagy gave a seminar talk at CU Boulder’s Collaborative on Air Quality Research (CAQR) Meeting upon invitation by Prof Shelly Miller.

Last updated on Dec 5, 2022 1 min read

Forecast predicts higher heating costs for homes this winter

Dr Nagy was interviewed on his thoughts on coming heating costs this winter. The interview was syndicated throughout the nation on local news. Here is KSBY in California https://www.ksby.com/news/national/forecast-predicts-higher-heating-costs-for-homes-this-winter

Last updated on Dec 9, 2022 1 min read

Forecast predicts higher heating costs for homes this winter

AI and Electric Power Summit

Together with EPRI we are organizing a session on the AI Grand Challenge on Grid Interactive Smart Communities. We are meeting in person to take our summit journey to Rome where we will move the AI and electric power dial even further.

Last updated on Oct 1, 2022 1 min read

EPRI AI Grand Challenge Webinar

This month’s webinar was focused on reinforcement learning as we had presentations from Dr Henze and his research team at CU Boulder. They discussed the advanced control test bed (ACTB) for buildings as well as opportunities, challenges and cases studies for reinforcement learning control in buildings.

Last updated on Oct 1, 2022 1 min read

Dr Nagy speaks at Amazon

Dr Nagy was the guest speaker in Amazon’s SSI speaker series on Sustainability. He talked about our research on CityLearn. Amazon is sponsoring AWS compute credits for the CityLearn Challenge 2022

Last updated on Oct 1, 2022 1 min read

Dr Nagy joins scientific and program committee of CISBAT

Focused on the built environment’s transition to carbon neutrality and sustainability, CISBAT 2023 offers a scientific platform for the presentation of research that pushes the boundaries of energy efficiency and renewable energy technologies.

Last updated on Sep 15, 2022 1 min read

Dr Nagy receives the 2022 IBPSA-USA Outstanding Researcher Award

This award recognizes one or more individuals who have provided outstanding leadership in the promotion of building simulation through research in the course of their career. The award has be announced at the 2022 ASHRAE/IBPSA-USA BPAC/SimBuild Conference .

Last updated on Oct 20, 2022 1 min read

New Paper: Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings

Led by IEL’s awesome PhD Student Kingsley, we have a new paper in Energy and AI. Open Access: https://www.sciencedirect.com/science/article/pii/S2666546822000489 Title: Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings Abstract:

Last updated on Sep 14, 2022 2 min read

New Paper: Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings

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Meet the Team

Principal Investigators

Zoltan Nagy

Assistant Professor

Grad Students

Allen Wu

Undergraduate Research Assistant (CS)

Calvin Lin

MSc Student

Kingsley Nweye

PhD Student

Praveen Radhakrishnan

MSc Student

Ting-Yu Dai

PhD Student

Yara Almilaify

MSc Student

Alumni

Alessandra Guerini

Visiting MSc Student

Avinash Damania

Undergraduate Research Assistant (CS)

Cassandra Prince

GLUE Student

Dr Hagen Fritz

Research Engineer

Dr. Aysha Demir

Assistant Instructional Professor

Dr. Jose Vázquez-Canteli

Machine Learning Engineer

Dr. June Young Park

Assistant Professor

Edward Mbata

Undergraduate Research Assitant (CAEE)

Eli Ramthun

MSc Student

Ignacio Aguirre Panadero

MSc Exchange Student (Spain)

Ignacio Perez de Rojas

MSc Exchange Student (Spain)

Jacob Wright

Undergraduate Research Assistant (CAEE)

Julien Brown

Undergraduate Research Assistant (Architecture)

Kaylee Trevino

Undergraduate Research Assistant (ECE)

Lauren Chen

Undergraduate Research Assistant (ME)

Megan McHugh

MSc Student

Negar Sheikh Mohammadi Khamseh

Visiting PhD Student (Politecnico di Torino)

Nicolas Castillo-Castejon

MSc Exchange Student (Spain)

Rachel Schutte

MSc Student (CAEE)

Ritvik Annam

Undergraduate Research Assistant (CS)

Sepehr Bastami

Research Engineer

Silvio Brandi

Visiting PhD student (Politecnico di Torino)

Stepan Ulyanin

Research Assistant (Applied Math)

Tejal Kulkarni

Undergraduate Research Assistant (ECE)

Tung To

Undergraduate Research Assistant (ECE)

Vianey Rueda

MSc Student

Viktor Carp

MSc Exchange Student (ETH Zurich)

Wendy Zhang

Undergraduate Research Assistant

Xiya Yang

Exchange Student (NUS Singapore)

Zhiheng Hu

Visiting MSc Student (CMU)

Research Projects

(BEVO) Beacon: A rapidly-deployable and affordable indoor environmental quality monitor

Indoor Air Quality (IAQ) monitoring is essential to assess occupant exposure to the wide range of pollutants present in indoor environments. Accurate research-grade monitors are often used to monitor IAQ but the expense and logistics associated with these devices often limits the temporal and spatial scale of monitoring efforts.

GridLearn

Led by CU Boulder - Griffin Lab (Dr Kyri Baker): Increasing amounts of distributed generation in distribution networkscan provide both challenges and opportunities for voltage regulation across the network. Intelligent control of smart inverters and other smart building energy management systems can be leveraged to alleviate these issues.

CityLearn

CityLearn is an open source OpenAI Gym environment for the implementation of Multi-Agent Reinforcement Learning (RL) for building energy coordination and demand response in cities. Its objective is to facilitiate and standardize the evaluation of RL agents such that different algorithms can be easily compared with each other. Try it out using our example in Google Colab! More details and installation on GitHub: https://github.com/intelligent-environments-lab/CityLearn

Publications

Google Scholar →

Code

GitHub →

Twitter

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