Research Assistant Professor
Department of Civil and Environmental Engineering,School of Engineering and Computing, University of South Carolina.
The Carolinas Integrated Sciences & Assessments (CISA; a NOAA-funded research center), University of South Carolina.
Hydro-environmental Research Centre (HRC), Department of Civil Engineering, School of Engineering, Cardiff University, United Kingdom.
Water Engineering and Science. 2009
University of Tehran, Iran. 2002
-GIS in Civil and Environmental Engineering (proposed course-undergraduate level:UofSC)
-GIS in Water Resources Engineering (proposed course-graduate level: UofSC)
-Research in Civil Engineering (UofSC)
-Selected Topics in Civil Engineering (UofSC and Clemson University)
-Thesis Preparation in Civil Engineering (UofSC & Clemson University)
-Thesis Preparation in Agricultural Sciences-Informatics and Agricultural Water System Management (Clemson University)
-Thesis Preparation in Computer Engineering (UofSC & Clemson University)
-Dissertation Preparation in Civil Engineering (UofSC & Clemson University)
-River Basin Management (Cardiff University & UofSC)
-Stochastic Hydrology and Hydroinformatics (proposed course-graduate & undergraduate levels; UofSC)
-Engineering Hydrology (UofSC)
-Advanced Hydrology (graduate level;co-taught with prof. Meadows of UofSC)
-Senior Design in Civil Engineering (co-taught with prof. Meadows of UofSC)
I am trained as a water resources engineer and work to advance the field of hydroinformatics and cyber-physical modeling systems. Much of my current research focuses on developing analytics and intelligent computing systems for flood/storm water and watershed modeling and management. My research sponsors include the National Science Foundation (CBET,CMMI), the U.S. Geological Survey (USGS), Savannah River National Lab, NOAA, and Department of Transportation (DOT).
I am a big believer of diversity and gender balance in STEM as well as in leadership where both men and women embarrass masculine and feminine values! In a field of water resources engineering that is traditionally dominated by males, I have worked to empower female and underserved students in engineering. I value Justice, Equity, Diversity, and Inclusion (JEDI) and I have a written JEDI statement for my research lab. I take an active role in making my research lab a welcoming, inclusive, and supportive environment to everyone. I am a founding member of Women in Artificial Intelligence for Water (WomenInAI4Water) that aims to strengthen the diversity and increase female representation and participation in AI and working towards gender-inclusive water data analytics and modeling in academia. I am highly committed to combat the disparity of women in Engineering and currently contribute to the Society of Women Engineers as well as Clemson PEER and WISE Inclusion programs to inspire future women Engineers.
PhD/MS applicants for Clemson: Please follow the instructions on the Clemson admission page.
Academic Research Interest: My academic research focuses on hydroinformatics and cyber-physical modeling systems, an interdisciplinary approach combining water resources engineering, computer science, and data analytics. The goal is to leverage advanced modeling and computing tools to address problems and challenges associated with water resources systems. Much of my current works are focused on Surface Water Modeling, Flood/Stormwater Computing, Impacts of Flooding on Critical Infrastructure, Smart Cities and Infrastructure, Big Data Analytics, and Geographic Information System (GIS). My team has developed many packages and modeling systems including Flood Analytics Information System (FAIS), Flood Image Classifier, Watershed Toolkit, as well as physical based models.
Industry Research Interest: My industry research interest concentrates around GIS software development, web and mobile application development, and web programming that involve creating, leveraging and utilizing web mapping solutions to solve specific environmental problems, build complete applications, or consume or produce data and geospatial processing services. Web GIS programming applies to both mobile and desktop application development. I am proficient in various programming languages (python, Java, HTML, etc.) and seek collaboration with academics and industry to develop tools that can address applied water resources engineering research and practical settings.
Awards & Honors (selected)
1. Clemson Support for Early Exploration and Development Award. 2021. Clemson University.
2. Advanced Support for Innovative Research Excellence Award. 2017. The University of South Carolina.
3. Outstanding Reviewer Award.2016. ASCE Journal of Hydrologic Engineering.
4. Second ranked Nationwide M.Sc. Competition in Water Engineering. 2000. Iranian Ministry of Sciences and Research.
Professional Services (selected)
1. Chair. The CUAHSI Standing Committee on Informatics, 2021-2022.
2. Member. The World Meteorological Organization (WMO)-GEWEX Hydroclimatology Panel (a global flood crosscutting project lead), 2019-2022 .
Extension and Outreach
I serve on the WMO-Global Energy and Water Exchanges (GEWEX) Hydrometeorology Panel (GHP). I currently lead a global, crosscutting, flood research initiative that allows GHP to propagate flood modeling and research knowledge from one region to the other and synthesize results at the global scale. At the national level, I chair the Consortium of Universities for the Advancement of Hydrologic Science (CUAHSI) Informatics Committee and oversee the CUAHSI informatics and data service activities, Informatics Blog, etc. At the state level, I lead South Carolina surface water modeling systems for SC Water Resources Center. I work collaboratively with state stakeholders as well as with 12 water agents (of the 12 current water agents, 11 of them are female) across the state of South Carolina to address water education and outreach.
* Denotes graduate students under my supervision.
Research Paper (selected)
1.Sadeghi Tabas S.*, Samadi S. 2022. Variational Bayesian Dropout with a Gaussian Prior for Recurrent Neural Networks Application in Rainfall-Runoff Modeling. Environmental Research Letters.DOI:https://doi.org/10.1088/1748-9326/ac7247
2. Pally, R.*, Samadi S. 2022. Application of Image Processing and Convolutional Neural Networks for Flood Image Classification and Semantic Segmentation. Environmental Modelling & Software. 148, p.105285.
3. Samadi S., van Oevelen P., Prein A., Roundy J. K., Dominguez F., Nazemi A. 2021. Opinion: The Role of GEWEX in Moving the Needle on the Resiliency of Society to Flooding. World Meteorological Organization (WMO)- Global Energy and Water Cycle Experiment (GEWEX) Quarterly Newsletter.
4. Samadi S., Sadeghi Tabas S.*, Wilson, C., Hitchcock, D. 2021. Big Data Analytics for Rainfall-Runoff Modeling: A Case Study of the Cape Fear Catchment, North Carolina. Book chapter for the AGU/Wiley edited volume "Advances in Hydroinformatics: Artificial Intelligence and Optimization for Water Resources". In press.
5. Donratanapat, N.*, Samadi S., Vidal, M.J., S. Sadeghi Tabas*. 2020. A National Scale Big Data Analytics Pipeline to Assess the Potential Impacts of Flooding on Critical Infrastructures and Communities. Environmental Modelling & Software.133, p.104828.
6. Samadi S., Pourreza-Bilondi M., Wilson C. A. M.E., Hitchcock, B.D. 2020. Bayesian Model Averaging with Fixed and Flexible Priors: Theory, Concepts, and Calibration Experiments for Rainfall-Runoff Modeling. AGU Journal of Advances in Modeling Earth Systems. 12(7), p.e2019MS001924.
7. Liu H.*, Hitchcock D., and Samadi S. 2020. Spatio-temporal analysis of flood data from South Carolina. Journal of Statistical Distributions and Applications. 7, 11 (2020).
8. B. Toni. Modern Statistical Methods for Spatial and Multivariate Data. In: David Hitchcock, Haigang Liu, and S. Samadi. 2019. Spatial and spatial-temporal analysis: A case study based on precipitation data from South Carolina. STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health. Vol. Netherlands: Springer.
9. Philips, R. C.*, Samadi, S., Meadows, M.E. 2018. How extreme was the October 2015 flood in the Carolinas? An assessment of flood frequency analysis and distribution tails. Journal of Hydrology. DOI: https://doi.org/10.1016/j.jhydrol.2018.05.035.
10. Samadi S., Tufford D., Carbone, G. 2018. Estimating Hydrologic Model Uncertainty in the Presence of Complex Residual Error Structures- Stochastic Environmental Research and Risk Assessment. 32: pp 1259–128.
11. Samadi S., Tufford D., Carbone, G. 2017. Assessing prediction uncertainty of a semi-distributed hydrology model for a shallow aquifer dominated environmental system– Journal of the American Water Resources Association (JAWRA). 53(6): 1368-1389.
12. Samadi S., Meadows M.E. 2017. The Transferability of Terrestrial Water Balance Components under Uncertainty and Non-stationarity: A Case Study of the Coastal Plain Watershed in the Southeastern United States. River Research and Applications. 33:796–808.
13. Pourreza-Bilondi Mohsen, Samadi S., Akhoond-Ali Ali-Mohammad, Ghahraman Bijan. 2016. On the Assessment of Reliability in Semiarid Convective Flood Modeling Using Bayesian Framework. ASCE Journal of Hydrologic Engineering, 05016039:1-16.
14. Sadeghi-Tabas S.*, Samadi S., Akbarpour A., Pourreza Bilondi M. 2016. Sustainable Groundwater Modeling Using Single and Multi-Objective Optimization Algorithms. Journal of Hydroinformatics. DOI: 10.2166/hydro.2016.006.
Peer-Reviewed Conference Papers (selected)
1.Humaira, N., Tabas, S.S., Samadi, S. and Hubig, N.C., 2021, December. FlowDyn: A Dynamic Web-based Streamflow Prediction Pipeline. In 2021 IEEE International Conference on Big Data (Big Data) (pp. 757-767). IEEE.
2.Samadi, S. and Pally, R., 2021. The Convergence of IoT, Machine Learning, and Big Data for Advancing Flood Analytics Knowledge. European Geosciences Union.
3. Pally, R. and Samadi, S., 2021. Application of Image Processing and Big Data Science for Flood Label Detection. European Geosciences Union.
1.Pally, R. *, Kranjit, R. *, Sadeghi Tabas, S*. Samadi, S., 2022. Image processing for Flood data analytics system. Register through Clemson CURF.
2.Donratanapat, N.*, Kranjit, R. *, Sadeghi Tabas, S*. Samadi, S., 2022. A system for Flood tweets analytics and sentiment assessment. Register through Clemson CURF.
1. Pally, R.*, and Samadi, S. 2022. A Python tool for Flood Image Classification and Semantic Segmentation (funded by NSF). Released strictly using the MIT license.
2. Donratanapat, N.*, Samadi S. 2020. A Google Module for Computing Rapid Surface Runoff (funded by NSF). Released strictly using the MIT license.
3. Sadeghi Tabas, S.*, Samadi S. 2020. A Deep Learning Application for Managing Water Resources Systems (funded by NSF; will be Beta-tested in 2021).
4. Donratanapat, N.*, Samadi S., and Vidal, J. 2019. “FAIS”: Flood Analytics Information System (funded by NSF). Released strictly using the MIT license.
6. Liu H. *, Hitchcock D., and Samadi S. 2018. A tree-based model and spatial information for stochastic analysis of hydrological extremes. Python tool.