Publications

Peer-reviewed Journal Articles

• Alizadeh, B., & Behzadan, A. H. (2023). Scalable flood inundation mapping using deep convolutional networks and traffic signage. Computational Urban Science, 3(1), 17.                         https://doi.org/10.1007/s43762-023-00090-1 

• Hillin, Julia, Alizadeh Kharazi, Bahareh; Li, Diya; Thompson, Courtney; Meyer, Michelle; Zhang, Zhe; & Behzadan, Amir H. (In Press), Designing user-centered decision support systems for climate disasters: What information do communities and rescue responders need during floods? Journal of Emergency Management. (Accepted 9/7/2022).

• Alizadeh, Bahareh; Li, Diya; Hillin, Julia; Meyer, Michelle; Thompson, Courtney; Zhang, Zhe; Behzadan Amir H. (2022), Human-Centered Flood Mapping and Intelligent Routing through Augmenting Flood Gauge Data with Crowdsourced Street Photos, Advanced Engineering Informatics, 54, 101730. https://doi.org/10.1016/j.aei.2022.101730. 

• Alizadeh, Bahareh; & Behzadan, Amir H. (2021), Flood depth mapping in street photos with image processing and deep neural networks. Computers, Environment and Urban Systems, 88, 101628. https://doi.org/10.1016/j.compenvurbsys.2021.101628 

• Alizadeh Kharazi, Bahareh; Alvanchi, Amin; & Taghaddos, Hosein (2020), A Novel Building Information Modeling-based Method for Improving Cost and Energy Performance of the Building Envelope. International Journal of Engineering, 33(11), 2162-2173. https://dx.doi.org/10.5829/ije.2020.33.11b.06 

• Alizadeh, B., Sakib, M. N., & Behzadan, A. H. Immersive Virtual Reality to Measure Flood Risk Perception in Urban Environments.                                                                                                https://www.ucl.ac.uk/bartlett/construction/sites/bartlett_construction/files/9014.pdf 

• Alizadeh, Bahareh; & Behzadan, Amir H. (2022), Blupix: Citizen science for flood depth estimation in urban roads. The 5th ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities, Seattle, WA. https://doi.org/10.1145/3557916.3567824 

• Alizadeh, Bahareh; & Behzadan, Amir H. (2022), Crowdsource-based Deep Convolutional Networks for Urban Flood Depth Mapping. 2022 European Conference on Computing in Construction, Rhodes, Greece. https://doi.org/10.48550/arXiv.2209.09200  

• Alizadeh, Bahareh; Li, Diya; Zhang, Zhe; Behzadan, Amir H. (2021), Feasibility Study of Urban Flood Mapping Using Traffic Signs for Route Optimization. In the proceeding of 28th EG-ICE International Workshop on Intelligent Computing in Engineering. Berlin, Germany. https://arxiv.org/abs/2109.11712  

• Alizadeh Kharazi, Bahareh; Alvanchi, Amir; & Taghaddos, Hosein (2017), Investigation of energy consumption of exterior wall construction materials using building information modeling (In Persian). Second National Conference on Applied Research in Civil Engineering (Structural Engineering and Construction Management). 

• Blupix Mobile (2023): An innovative Android app incorporating cutting-edge computer vision technology. Employed TensorFlow Lite, Firebase, Google Street View API, and the Android Location API to enhance its functionality. Available at github.com/ciber-lab/blupix

• Blupix (2021): A dynamic crowdsourcing application hosted on a cyberinfrastructure, leveraging Docker and Azure technologies. This innovative platform secured the 2nd place in the Robert Raskin Student Competition. Available at blupix.geos.tamu.edu

• Blupix dataset (2023): An annotated dataset containing 1500 annotated photos of traffic signs. Available at github.com/ciber-lab/blupix

• Thompson C., Hillin J., Meyer M., Behzadan A.H., Zhang Z., Alizadeh B., Li D. (2021), “Understanding Community Needs for a Hybrid Flood Risk Decision Support System in Texas”, Natural Hazards Research and Applications Workshop, Broomfield, CO.
• Behzadan A.H., Thompson C., Zhang Z., Meyer M., Alizadeh B., Li D., Hillin J. (2021), “Mapping and Communication of Flood Risk with Computer Vision and Community Science”, Texas A&M Disaster PRIMR Conference, College Station, TX.

• Alizadeh, Bahareh (2022) Blupix: Flood depth estimation in urban roads. Selected as finalist for presenting at the 10th annual 3-minutes thesis competition at Texas A&M University. https://www.youtube.com/watch?v=1XkTXpLnuDs 
• Li, Diya; Zhang, Shuyang; Huilin, Julia; Alizadeh, Bahareh (2022) A Geospatial Cyberinfrastructure for Street Level Flood Mapping and Emergency Management, Second place in the 2022 Robert Raskin Student Competition, American Association of Geographers (AAG) Cyber-infrastructure specialty group.

• Alizadeh, Bahareh; Li, Diya; Zhang, Zhe; & Behzadan, Amir H. (2022), Integrating Crowdsourced Data and Artificial Intelligence to Increase Spatial Resolution of Flood Risk Mapping, Planet Texas 2050 Symposium: A Week of Resilience Research in Action, University of Texas at Austin, US.

• Alizadeh, Bahareh; Li, Diya; Zhang, Zhe; & Behzadan, Amir H. (2022), Integrating Crowdsourced Data and Artificial Intelligence to Increase Spatial Resolution of Flood Risk Mapping, Fresh Vision II, Wright Gallery, College of Architecture, Texas A&M University.

• Alizadeh, Bahareh; Li, Diya; Zhang, Zhe; & Behzadan, Amir H. (2022), Enhancing Disaster Resilience in Coastal Regions Using Artificial Intelligence and Crowdsourcing Data Collection, Student Research Week, Texas A&M University, US.

Invited Talks

• Alizadeh, Bahareh (2021) “Open access flood inundation mapping for emergency response in flood events", Abstract presented at The Texas A&M College of Architecture’s 23rd Annual Research Symposium Academic Minutes.

• Alizadeh, Bahareh (2022) “Blupix mobile application for flood depth estimation using crowdsourcing and artificial intelligence", Abstract presented at The Texas A&M College of Architecture’s 24rd Annual Research Symposium Academic Minutes.

• Alizadeh, Bahareh (2022) “Integrating Crowdsourced Data and Artificial Intelligence to Increase Spatial Resolution of Flood Risk Mapping", Graduate course of Theory of Research in Construction Management, Department of Construction Science, Texas A&M University.

• Alizadeh, Bahareh (2022) “Integrating Crowdsourced Data and Artificial Intelligence to Increase Spatial Resolution of Flood Risk Mapping", Graduate course of Seminar I, Department of Construction Science, Texas A&M University.

• Alizadeh, Bahareh (2022) “Flood depth mapping in street photos with image processing and deep neural networks", Landscape Architecture and Urban Planning Annual Faculty Meeting, Department of Landscape Architecture, Texas A&M University.