Simon Elias Bibri, PhD, is an internationally recognized and highly impactful researcher in the fields of sustainable smart cities, smarter eco-cities, environmental sustainability and resilience, and advanced and converging AI systems. His work focuses on how advanced technological frameworks can be conceptualized, developed, integrated, and deployed within urban and environmental systems to transform sustainable development and advance ecological sustainability.  Currently, he serves as a Senior Researcher and Scientific Coordinator at the Swiss Federal Institute of Technology in Lausanne (EPFL). He has a diverse professional background, having served as Head of Computer Department, Software Development and IT Business Engineer, IT Project Manager, Green ICT and Environmental Sustainability Strategist, Research Associate, Assistant Professor, and International Expert. He was a visiting scholar at Lund University for one year and a visiting senior researcher at Royal Institute of Technology (KTH) in Sweden. He served as Expert in Artificial Intelligence and Applied Machine Learning for Climate Action for the United Nations Framework Convention on Climate Change (UNFCCC) and International Expert in Sustainable Cities for the United Nations Industrial Development Organization (UNIDO). He serves as Expert for Focus Group on Smart Sustainable Cities, Environmental Sustainability, and Digital Twins for the  International Telecommunication Union (ITU). He also serves as Editor-in-Chief of the International Journal of Environmental Studies at Taylor & Francis, Editor-in-Chief of the Book Series of  Advanced and Converging AI  Systems for Environmental Science and Sustainability at Elsevier, Associate Editor of the Sustainable Cities and Society journal at Elsevier, and Lead Editor of the Sustainable Artificial Intelligence-Powered Applications book series at Springer.

Dr. Bibri's academic journey exemplifies both interdisciplinarity and transdisciplinarity. His intellectual background encompasses computer science, computer engineering, systems science, innovation science, environmental science, and social sciences. He holds a bachelor's degree in computer engineering and a postgraduate degree in management science: Advanced Management Program (AMP). Notably, he earned multiple master's degrees from different esteemed Swedish universities, namely Lund University, West University, Blekinge Institute of Technology, Stockholm University, Malmö University, and Mid-Sweden University. He received his PhD in Computational and Information Technology from the Norwegian University of Science and Technology (NTNU), specializing in data-driven smart sustainable cities.

Dr. Bibri is a prolific scholar with numerous highly cited journal articles, 11 authored books, 5 edited works, and 18 co-edited volumes to his credit. His work has been cited over 18500 times, resulting in an h-index of 60. His impact has been recognized by Stanford University and Elsevier as one of the top 1% of scientists worldwide, a distinction he has held for six consecutive years. He has also been listed by ScholarGPS as the #1 highly ranked scholar in sustainable cities, #2 in Urbanism, and #8 in environmental sustainability in the world.

Recent Publications (2025-2026)

Journal Articles and Book Chapters:

1. Bibri, S. E., Huang, J., Krogstie, J., Osama, O., & Yigitcanlar, T. (2026). The Next Frontier of Generative Intelligence in Smarter Eco-Cities: A Systematic Review of Deep Generative and Hybrid Modeling Applications for Environmental Sustainability, Sustainable Cities and Society, https://doi.org/10.1016/j.scs.2026.107408.

2. Soltani, A., Ziafati Bafarasat, A., Bibri, S. E., Ramezani, L., & RoohaniQadikolaei, M. (2026). Between Algorithm and Agora: Ethical Challenges in AI-Assisted City Planning—A Systematic Review and Conceptual Framework. Progress in Planning, 203(2), 101043. https://doi.org/10.1016/j.progress.2026.101043

3. Bibri, S. E., Huang, J. (2026). An Applied World Model for Cross-Domain Sustainable Smart City Flows: Representation Learning, Latent Dynamics, Simulation–Inference, Long-Horizon Trajectory Prediction, and Policy Intelligence, Environmental Science and Ecotechnology (in press).

4. Bibri, S. E., Huang, J., Osama, O., Krogstie, J. (2026). Converging Agentic AI, Generative Agentic AI and Digital Twins for Sustainable Smart Cities: A Systematic Review of Autonomous and Adaptive Intelligence for Environmental Sustainability and Resilience. Environmental Science and Ecotechnology. In press.

5. Bibri, S. E., Huang, J., & Osama, O. (2026). A Generative AI-Driven Transcalar Framework for Sustainable City Design: A Thematic Synthesis of Deep Generative and Hybrid Models Across Six Spatial Scales, Sustainable Horizons (in press).

6. Bibri, S.E., & Huang, J. (2025). Artificial Intelligence of Things for Sustainable Smart City Brain and Digital Twin Systems: Pioneering Environmental Synergies of Real-Time Management and Predictive Planning, Environmental Science and Ecotechnology,  https://doi.org/10.1016/j.ese.2025.100591

7. Bibri, S. E., Huang, J., Osama O., & Kenawy, I. (2025). Synergistic Integration of Digital Twins and Zero Energy Buildings for Climate Change Mitigation in Sustainable Smart Cities: A Systematic Review and Novel Framework, Energy and Buildings, https://doi.org/10.1016/j.enbuild.2025.115484

8. Huang, J., Bibri, S. E., & Keel, P. (2025). Generative Spatial Artificial Intelligence for Sustainable Smart Cities: A Pioneering Large Flow Foundation Model for Urban Digital Twin. Environmental Science and Ecotechnology, 24 100526, https://doi.org/10.1016/j.ese.2025.100526 

9. Bibri, S. E., & Huang, J.(2025). AI and AI-powered Digital Twins for Smart, Green, and Zero-Energy Buildings: A Systematic Review of Leading-Edge Solutions for Advancing Environmental Sustainability Goals. Environmental Science and Ecotechnology. Vol 28, 100628. https://doi.org/10.1016/j.ese.2025.100628 

10. Bibri, S. E., & Huang, J.(2025). Generative AI of Things for Smart Sustainable Cities: Synergizing Cognitive Augmentation, Resource Efficiency, Network Traffic, Cybersecurity, and Anomaly Detection for Environmental Performance, Sustainable Cities and Society, 106826, https://doi.org/10.1016/j.scs.2025.106826

11. Bibri, S.E., Huang, J., & Yigitcanlar, T., (2025). Introduction to Digital Twins for Smart Metabolic Circular Cities: Foundations, Technologies, Practices, and Emerging Trends. In SE Bibri, T Yigitcanlar, J Huang (Eds.), Digital Twins for Smart Metabolic Circular Cities: Innovations in Planning and Climate Resilience, (Smart Cities Book Series), Elsevier, UK. ISBN: 9780443333330. 

12. Bibri, S.E., Huang, J., & , Omar, O., (2025). Leveraging Digital Twins for Zero-Energy Building Ratings in Sustainable Smart Cities: A Comprehensive Review and Novel Framework. In SE, Bibri, SE, T Yigitcanlar, J Huang (Eds.), Digital Twins for Smart Metabolic Circular Cities: Innovations in Planning and Climate Resilience (Smart Cities Book Series), Elsevier, UK. ISBN: 9780443333330. 

13. Bibri, S.E., (2025), From Eco-Urbanism to Smarter Eco-Urbanism: AI, AIoT, and GenAI for Advancing Green Infrastructure, Environmental Solutions, Climate Resilience, and Community Engagement with Artificial Intelligence, In SE Bibri (Eds.), Ecological Urbanism: Integrating Green Infrastructure, Technological Innovations, and Climate Resilience, Springer, https://10.1007/978-3-032-01528-0_1.

14. Bibri, S.E., & Mahmoud, I.H., (2026), Emerging Practices and Artificial Intelligence Innovations in Green Urbanism: Nature-Based Solutions, Resilience, and Environmental Strategies, In IH Mahmoud, SE Bibri (Eds.), Innovative Technologies and Circular Solutions for Sustainable Urban Communities, Springer, https://doi.org/10.1007/978-3-031-99036-6.

15. Bibri, S.E., (2026), Navigating Complexity in Sustainable and Smart Cities: Integrating Ecological Intelligence, Technological Innovation, and Climate Resilience, In SE Bibri, S Eden, M Amer  (Eds.), Sustainable and Smart Cities: Ecological Design, Technological Innovation, and Climate Resilience, Springer, https://doi.org/10.1007/978-3-032-00545-8_1.

16. Bibri, S. E. (2027). Advanced and Converging AI Systems for Environmental Sustainability, Climate Resilience, and Smarter Eco-cities: Foundations, Applications, and Future Directions. In S. E. Bibri & J. Huang (Eds.), Advanced and converging AI systems for smarter eco-cities: Deep learning, deep generative, and foundation models for environmental, geospatial, spatiotemporal and timeseries intelligence. Elsevier (forthcoming).

17. Al-Khawand, G., Bibri, S. E., & Robeck, P. (2027). Generative Intelligence for Smarter Eco-cities: A Systematic Review of Applications and Challenges of Integrated Urban and Environmental Foundation Models. In S. E. Bibri & J. Huang (Eds.), Advanced and converging AI systems for smarter eco-cities: Deep learning, deep generative, and foundation models for environmental, geospatial, spatiotemporal and timeseries intelligence. Elsevier (forthcoming).

18. Robeck, P., Bibri, S. E., & Al-Khawand, G. (2027). Geospatial, Spatiotemporal and Time-series Foundation Models for Multimodal Urban and Environmental Intelligence: A Critical Cross-domain Review and Integrated Conceptual Framework. In S. E. Bibri & J. Huang (Eds.), Advanced and converging AI systems for smarter eco-cities: Deep learning, deep generative, and foundation models for environmental, geospatial, spatiotemporal and timeseries intelligence. Elsevier (forthcoming).

19. Bibri, S. E. (2027).  Generative, Agentic, and Generative Agentic AI for Environmental Sustainability and Resilience: Deep Generative and Hybrid Modeling and Autonomous and Adaptive Intelligence for Advancing Climate Action. In S. E. Bibri & J. Huang (Eds.), Advanced and converging AI systems for smarter eco-cities: Deep learning, deep generative, and foundation models for environmental, geospatial, spatiotemporal and timeseries intelligence. Elsevier (forthcoming).

20. Bibri, S. E., Omar, O., & Huang, J. (2027). GANs and their Hybrid Architectures for Environmental Sustainability and Resilience: Emerging Applications and a Conceptual Framework. In S. E. Bibri & J. Huang (Eds.), Advanced and converging AI systems for smarter eco-cities: Deep learning, deep generative, and foundation models for environmental, geospatial, spatiotemporal and timeseries intelligence. Elsevier (forthcoming).

Authored and Edited Books—Elsevier, Springer, and Routledge

1. Bibri, S.E. (2026).  The Next Frontiers of Quantum Generative Intelligence for Smarter Eco-Cities Transforming Environmental Sustainability Through Augmented Deep Generative and Foundation Models, Elsevier. https://doi.org/10.1016/C2026-0-00265-7

2. Bibri, S. E. (2027). World Models for Next-Generation Urban Digital Twins: Dynamical Modeling and Simulation of Urban–Environmental Flows through Deep Learning, Deep Generative, and Foundation Models. Elsevier (Forthcoming).

3. Bibri, S. E. (2027). Toward Generative Agentic AI-Powered Urban Digital Twins: Predictive, Generative, Spatiotemporal, and Autonomous Intelligence for Physical, Environmental, Ecological, and Metabolic Systems and Flows. Elsevier (Forthcoming).

4. Bibri, S.E., & Huang, J. (2026), Advanced and converging AI systems for smarter eco-cities: Deep learning, deep generative, and foundation models for environmental, geospatial, spatiotemporal and timeseries intelligence, Elsevier (Forthcoming).

5. Bibri, S.E., & Huang, J. (2026), The Generative AI-Driven Sustainable Smart City: Deep, Hybrid, and Foundation Models for Environmental Planning, Computational Design, and Climate Resilience, Routledge. DOI: 10.1201/ 9781003650126

6. Bibri, S.E., (2025), Generative AI and Generative AI of Things for Sustainable Smart Cities: Pioneering Environmental Innovations, Climate Solutions, and Infrastructural Transformations, Routledge. DOI: 10.1201/9781003672500
.

7. Bibri, S. E. (2025). Artificial Intelligence of Things for Smarter Eco-Cities: Pioneering the Environmental Synergies of Urban Brain, Digital Twin, Metabolic Circularity, and Platform. Routledge, DOI: 10.1201/9781003536420.

8. Alberti, F., Bibri, S. E., Gallo, P., Matamanda, A. R. et al. (Eds.). (2025). Urban and Transit Planning (Vol. 1): Strategies, Innovations and Climate Management. Springer. ISBN: 978-3-031-75708-2. 

9. Gallo, P., Bibri, S. E., Alberti, F., Matamanda, A. R. et al. (Eds.). (2025). Urban and Transit Planning (Vol. 2): Culture and Sustainability for Built Environment. Springer. ISBN: 978-3-031-75708-2.

10. Bibri S. E., Yigitcanlar, T., & Huang, J. (Eds.). (2025) Digital Twins for Smart Metabolic Circular Cities: Innovations in Planning and Climate Resilience, Smart Cities Book Series, Elsevier. ISBN: 9780443333347.

11. Bibri S. E., Giusseppe, G. et al. (Eds.). (2025) Sustainable Cities: Pioneering Approaches to Green Urbanism and Climate Resilience, ASTI Book Series, Springer. ISBN:978-3-031-86094-2.

12. Mahmoud I.H. & Bibri S. E. (Eds.). (2026). Innovative Technologies and Circular Solutions for Sustainable Urban Communities,  ASTI Book Series, Springer. ISBN:978-3-031-99038-0.

13. Bibri S. E. (Ed.). (2026). Ecological Urbanism: Integrating Green Infrastructure, Technological Innovations, and Climate Resilience, ASTI Book Series, Springer. ISBN:978-3-032-01527-3.

14. Bibri S. E., Eden, S., & Amer, M., (Ed.). (2026). Sustainable and Smart Cities: Ecological Design, Technological Innovation, and Climate Resilience, Springer. ISBN: 978-3-031-99038-0.

15. Majumdar, S., Bibri S. E., Choudhury, M., & Omar, O., (Ed.) (2026). AI and Generative AI for Spatial Analysis in Sustainable Smart Cities:  Innovative Planning Practices and Environmental Solutions, SAIBA Book Series, Springer (Forthcoming).

16. Bibri S. E., & Omar, O., (Ed.) (2026). The Regenerative City: Urban Ecology and Architectural Strategies for Resilient Communities, ASTI Book Series, Springer (Forthcoming).

17. Aghajanian, A., Bibri S. E., & Fayyaz, M., (Ed.) (2027).  Artificial Intelligence for Civil Engineering, Architecture, and the Built Environment: An Integrated Engineering Approach, Elsevier (Forthcoming).

18. Omar, O., Bibri S. E., & Liang, X. (Ed.) (2027). Transforming Sustainable Development through Deep Generative and Foundation Models: Emerging Solutions for Environmental Sustainability and Climate Resilience. Elsevier (Forthcoming).