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PUBLICATIONS

BOOK
  • Abbasabadi, N., Ashayeri, M. (Eds). (2024) Artificial Intelligence in Performance-driven Design: Theories, Methods and Tools, Wiley.

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BOOK CHAPTERS

  • Abbasabadi, N., Ashayeri, M., (2024). Digital Twin for Citywide Energy Modeling and Management. In N. Abbasabadi & M. Ashayeri (Ed.), Artificial Intelligence in Performance-driven Design: Theories, Methods, and Tools. Wiley.
  • Abbasabadi, N., (2024) Understanding Social Dynamics in Urban Building and Transportation Energy Behavior. In N. Abbasabadi & M. Ashayeri (Ed.), Artificial Intelligence in Performance-driven Design: Theories, Methods, and Tools. Wiley.
  •  Ashayeri, M., Abbasabadi, N., (2024). A Hybrid Physics-based Machine Learning Approach for Multi-domain Energy and Exposure Modeling. In N. Abbasabadi & M. Ashayeri (Ed.), Artificial Intelligence in Performance-driven Design: Theories, Methods, and Tools. Wiley.
  • Abbasabadi, N., Ashayeri, M., (2024). Machine Learning in Urban Building Energy Modeling. In N. Abbasabadi & M. Ashayeri (Ed.), Artificial Intelligence in Performance-driven Design: Theories, Methods, and Tools. Wiley.
  • Abbasabadi, N., Ashayeri, M., (2024). Occupant-Driven Urban Building Energy Efficiency via Ambient Intelligence. In N. Abbasabadi & M. Ashayeri (Ed.), Artificial Intelligence in Performance-driven Design: Theories, Methods, and Tools. Wiley.
  • Abbasabadi, N., Ashayeri, M. (2017). Towards an adaptive urbanism beyond hard control: The theories of Johnson and Lefebvre. In M. Couceiro da Costa (Ed.), Architectural Research Addressing Societal Challenges (1st Edition ed., vol. 1, pp. 257–62). London, UK: CRC Press/Taylor & Francis Group.

 

JOURNAL ARTICLES
  • Abbasabadi, N., & Ashayeri, M. (2024). From Tweets to Energy Trends (TwEn): An exploratory framework for machine learning-based forecasting of urban-scale energy behavior leveraging social media data. Energy and Buildings. 317, 114440. https://doi.org/10.1016/j.enbuild.2024.114440
  • Ashayeri, M., Piri, S., & Abbasabadi, N. (2024). Exploring U.S. Occupant perception toward indoor air quality via social media and NLP analysis. Journal of Environmental Science and Public Health. 8: 49-58. DOI:10.26502/jesph.96120205
  • Ashayeri, M., & Abbasabadi, N. (2024). Unraveling energy justice in NYC urban buildings through social media sentiment analysis and transformer deep learning. Energy and Buildings, 306, 113914. https://doi.org/10.1016/j.enbuild.2024.113914
  • Ashayeri, M., & Abbasabadi, N. (2022). A framework for integrated energy and exposure to ambient pollution assessment (iEnEx) Toward low-carbon, healthy, and equitable cities. Sustainable Cities and Society. 78, 103647. https://doi.org/10.1016/j.scs.2021.103647
  • Ashayeri, M., Abbasabadi, N., Heidarinejad, M., & Stephens, B. (2021). Predicting intraurban PM2.5 concentrations using enhanced machine learning approaches and incorporating human activity patterns. Environmental Research. 196, 110423. https://doi.org/10.1016/j.envres.2020.110423
  • Abbasabadi, N., Ashayeri, M., Azari, R., Stephens, B., & Heidarinejad, M. (2019). An integrated data-driven framework for urban energy use modeling (UEUM). Applied Energy, 253:113550. https://doi.org/10.1016/j.apenergy.2019.113550
  • Abbasabadi, N., & Ashayeri, M. (2019). Urban energy use modeling methods and tools: A review and an outlook. Building and Environment, 161:106270. https://doi.org/10.1016/j.buildenv.2019.106270
  • Abbasabadi, N. (2019). Developing a data-driven framework for multi-scale integrated urban building and transportation energy modeling. Prometheus, Issue 03: Building, Cities, and Performance I, 36–39. ISSN: 2688-0776. https://prometheus.library.iit.edu/index.php/journal/article/view/75
  • Azari, R., & Abbasabadi, N. (2018). Embodied energy of buildings: A review of data, methods, challenges, and research trends. Energy and Buildings, 168, 225-235. https://doi.org/10.1016/j.enbuild.2018.03.003
CONFERENCE PAPERS & PRESENTATIONS
  • Abbasabadi, N. (2023). Hybrid Twins: Scaling Up Digital Twin for Citywide Energy Modeling and Management.  2023 Region 10 PacTrans Conference.
  • Abbasabadi, N. (2023). Hybrid Twin: Scaling Up Digital Twin from Building to City Levels via Machine Learning and Physics-based Simulations. SBX 2023, Smart Buildings Exchange Conference.
  • Ashayeri, M., Abbasabadi, N. (2023). Evaluating Spatial Disparities of Occupant Sentiment on Indoor Air Quality Across Communities in NYC Using Twitter Data, NLP, and Emotion-AI Approaches. Livable Cities, 2023 Architecture, Media, Politics, Society (AMPS) International Conference.
  • Kamalisarvestani, S. Ashayeri, M. Abbasabadi, N. (2023). An Evolutionary Multi-Objective Optimization Tool for Designing Kinetic Facades Integrating Daylight and Lighting Energy Simulation. The Research-Design Interface, ARCC 2023 International Conference.
  • Abbasabadi, N. Ashayeri, M., (2022). Covid-19 Pandemic and Equity within the Built Environment: Exploring Mobility, Energy, and Health Disparities Using Smart Data. Health in all Design, The Environmental Design Research Association (EDRA). EDRA58 Greenville, SC. June 1-4, 2022. (Digital Media)
  • Luitjohan, S., Ashayeri, M., & Abbasabadi, N. (2022). An optimization framework and tool for context-sensitive solar-driven design using cellular automata (SDCA). 2022 Annual Modeling and Simulation Conference (ANNSIM), 593–604. https://doi.org/10.23919/ANNSIM55834.2022.9859496
  • Abbasabadi, N., Ashayeri, M. (2021). Socioeconomic determinants of public health and residential building energy use in Chicago. 27th World Congress of Architects UIA 2021 Rio. ACSA. Volume II. ISBN 978-1-944214-31-9.
  • Ashayeri, M., Abbasabadi, N. (2021). Energy justice, indoor air quality, and community resiliency against Covid-19 pandemic. Environments by Design: Health, Wellbeing and Place; AMPS: Architecture, Media, Politics, Society.
  • Abbasabadi, N., Azari, R. (2019). A framework for urban building energy use modeling (pp. 386–94). The Future of Praxis: Applied Research as a Bridge Between Theory and Practice, Proceedings of the ARCC Conference, Toronto.
  • Abbasabadi, N., Azari, R. (2019). A data-driven framework for urban building operational energy use modeling. (pp. 71-77). 2019 Symposium on Simulation for Architecture & Urban Design (SimAUD).
  • Abbasabadi N., (2018). A predictive approach for an integrated urban building and transportation energy modeling: An application of artificial intelligence. Building, Cities, and Performance, IIT 3rd International Graduate Student Symposium, Chicago, IL.
  • Abbasabadi N., (2019). An integrated data-driven framework for urban energy use modeling, (poster section) at the Energy-Efficient and Grid-Interactive Buildings, the Rosenfeld Symposium, Lawrence Berkeley National Laboratory, Berkeley, California, IL.
  • Abbasabadi N., (2019). An integrated framework for urban energy use modeling: Applications of artificial intelligence, (presentation). presented at the Artificial Intelligence at IllinoisTech, Active Computational Thinking (ACT) Center, Department of Computer Science, Chicago, IL.
  • Abbasabadi, N., Ashayeri, M. (2012). Recognition of cultural identity and sustainable urban design: Case study Shah-Cheragh historical zone. The first International Conference on Cultural Heritage and Identity Formation, Shiraz Azad University.
  • Abbasabadi, N., Ashayeri, M. (2012). Sustainability in architecture: The place of technology. National Conference on Sustainable Development and Urban Construction, Esfahan Daneshpajoohan Institute of Higher Education.
  • Abbasabadi, N., Ashayeri, M. (2012). Energy management and environmental design: Towards sustainable architecture. 2nd National Conference on Environmental Planning and Management (EPM), University of Tehran.