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Journal Publications


  1. D.M. Silva, R. Kumar, R. Nateghi, 2020. The critical role of humidity in summer electricity demand across the United States. Nature Communications, 11(1)1-8. [link]
  2. R. Obringer, S. Mukherjee, R. Nateghi, 2020. Evaluating the climate sensitivity of coupled electricity-natural gas demand using a multivariate framework. Applied Energy, 262, p.114419. [link]
  3. A.P. Kanmani, R. Obringer, B. Rachunok, and R. Nateghi, 2020. Assessing global environmental sustainability via an unsupervised clustering framework. Sustainability, 2020, 12(2):563. [link]
  4. R Obringer, R. Kumar, R. Nateghi, 2020. Managing the water–electricity demand in a changing climate. Climatic Change, 1-20. [link]
  5. J. Bennett, E. Johncox, A. Baker, R. Nateghi, 2020. Characterizing the key predictors of renewable energy penetration for sustainable and resilient communities, ASCE Journal of Management in Engineering, the special issue on Management of Resilience in Civil Infrastructure Systems: An Interdisciplinary Approach, 36(4), p.04020016. [link]
  6. B. Rachunok, R. Nateghi, 2020.The sensitivity of infrastructure resilience to the spatial distribution of disaster impacts. Reliability Engineering and Systems Safety, 193, p.106658. [link]
  7. P. Alipour, S. Mukherjee, R. Nateghi, 2019. Assessing climate sensitivity of peak electricity load for resilient power systems planning and operation: A study applied to the Texas region, Energy, 185,1143-1153 [link].
  8. Pamela Murray-Tuite, Haizhong Wang, Christopher Zobel, Y. Gurt Ge, R. Nateghi, 2019. Critical time and space considerations for data and modeling in interdisciplinary hazards and disasters research, Risk Analysis, [link]
  9. R. Obringer, R. Kumar, R. Nateghi, 2019. Analyzing the climate sensitivity of the coupled water-electricity demand nexus in the Midwestern United States. Applied Energy, 252:113466. [link]
  10. T. Saeed, R. Nateghi, T. Hall, B. Waldorf. Statistical Analysis of Area-wide Alcohol-related Driving Crashes: A Spatial Econometric Approach, Geographical Analysis, [link]
  11. B.C. Bruss, R. Nateghi, B. Zaitchick. When the well runs dry: Predicting observed GRACE satellite groundwater storage trends, Frontiers in Environmental Science, 7:85[link]
  12. BRachunok, J. Bennett, R. Nateghi. Twitter and disasters: a social resilience fingerprint. IEEE Access,7, 58495-58506.. [link]
  13. R. Nateghi, Pamela Murray-Tuite, 2019. The frontiers of uncertainty estimation and communication in interdisciplinary disaster research, Risk Analysis, 10.1111/risa.13337. [link]
  14. Y. Gurt Ge, Christopher Zobel, Pamela Murray-Tuite, Haizhong Wang, & R. Nateghi, 2019Building an interdisciplinary team for disaster response research: A data-driven approach, Risk Analysis, [link]
  15. S. Mukhopadhyay, Vineeth CR, R. Nateghi, 2019Evaluating regional climate-electricity demand nexus: A composite Bayesian predictive framework. Applied Energy, 235:1561-1582. [link]
  16. D. Gotham, W. McClain, S. Mukherjee, R. Nateghi, P. Preckel, L. Raymond, Schubert P., Singh S., Wachs E. Climate change impacts on Indiana’s energy demand and supply, Climatic Change, 1-15. [link]
  17. S. Mukherjee, R. Nateghi, 2019. A data‐driven approach to assessing supply inadequacy risks due to climate‐induced shifts in electricity demand. Risk Analysis, 39(3), 673-694. [link] [Winner of the Best Paper Award in Risk Analysis (SRA 2019)]
  18. Y. Qiao, S. Chen, T.U. Saeed, R. Nateghi, S. Labi, 2018. Acquiring insights on repair policy using discrete choice models. Transportation Research part A: Policy and Practice,113:491-508.  [link]
  19.  R. Obringer, R. Nateghi, 2018. Predicting reservoir levels using statistical learning techniques, Scientific Reports, 8(1):5164.[link]
  20. S. Mukhopadhyay, R. Nateghi, Makaradn Hastak, 2018. A Multi-hazard approach to assess sever weather-induced major power outage risks in the U.S., Reliability Engineering and Systems Safety,175:283-305. [link]
  21. R. Nateghi, 2018. Multi-dimensional infrastructure resilience modeling: an application to hurricane-prone electric power distribution systems, Access, IEEE, Digital Object Identifier 10.1109/ACCESS.2018.2792680. [link]
  22. M. Lokhandwala, R. Nateghi, 2018. Leveraging advanced predictive analytics to assess commercial cooling load in the U.S., Sustainable Production and Consumption,14, 66-81. [link]
  23. R. Nateghi, S. Mukherjee, 2017. A multi-paradigm framework to assess the impacts of climate change on end-use energy demand, PloS one,12(11): e0188033. [link]
  24. S. Mukhopadhyay, R. Nateghi, 2017. Climate, weather, socio-economic and electricity usage data for the residential and commercial sectors in FL, U.S., Data in Brief, 13:192-195. [link]
  25. S. Mukhopadhyay, R. Nateghi, 2017. Climate sensitivity of energy consumption in the built environment: an application to the state of Florida, Energy , 128: 688-700. [link]
  26. R. Nateghi, J.D. Bricker, S.D. Guikema, A. Bessho, 2016. Statistical analysis of the effectiveness of seawalls and coastal forests in mitigating tsunami impacts in Iwate and Miyagi prefectures, PloS One, 11(8), p.e0158375. [link]
  27. R. Nateghi, S.D. Guikema, G.Y. Wu, C.B. Bruss, 2016. Critical assessment of the foundations of power transmission and distribution reliability metrics and standards, Risk Analysis 36(1): 4-15. [link]
  28. Guikema S.D., R. Nateghi, S.M. Quiring, A. Staid, A.C. Reilly, M. Gao, 2014. Predicting hurricane power outages to support storm response planning, Access, IEEE 2: 1364-1373. [link]
  29. Staid A., S.D. Guikema, R. Nateghi, S.M. Quiring, M. Gao, 2014. Simulation of tropical cyclone impacts to the US power system under climate change scenarios, Climatic Change: 127 (3-4): 535-546.[link]
  30. R. Nateghi, S.D. Guikema S.M. Quiring, 2014. Forecasting hurricane-induced power outage durations. Natural Hazards 74:1795-1811. [link]
  31. R. Nateghi, S.D. Guikema, and S.M. Quiring, 2013. Power outage estimation for tropical cyclones: improved accuracy with simpler models, Risk Analysis 34 (6):1069-1078. [link]
  32. R. Nateghi, S.D. Guikema, S.M. Quiring, 2011. Comparison and validation of statistical methods for predicting power outage durations during hurricanes, Risk Analysis 31(12):1897-1906. [link]
  33. R.A. Francis, S.M. Falconi, R. Nateghi, S.D. Guikema, 2011. Probabilistic life cycle analysis model for electric power infrastructure risk mitigation in hurricane-prone coastal areas, Climatic Change 106 (1): 31-55. [link]

Under Review

  1. E. Wongso, R. Nateghi, B. Zaitchik, S. Quiring, R. Kumar, A data-driven framework to characterize state-level water withdrawals in the U.S. Water Research Journal (under third review).
  2. J. Bennett, B. Rachunok, R. Flage, R. Nateghi. Decoding regional climate attitudes by integrating social media and survey data, Plos One.
  3. B. Rachunok, J. Bennett, R. Nateghi. A Path forward for leveraging social media to improve the study of community resilience, International Journal of Disaster Risk Reduction.
  4. R. Kumar, B. Rachunok, D.M. Silva, R. Nateghi. Asymmetric temperature response of electricity demand points to severe underestimation of load projections in California. Scientific Reports (under second review).
  5. N. Alemazkoor, B. Rachunok, D.R. Chavas, A.Staid, A. Louhghalam, R. Nateghi, M. Tootkaboni. Hurricane-induced outage risk under climate change is primarily driven by the uncertainty in projections of future hurricane frequency.

Conference Proceedings

  1. B. Rachunok, R. Nateghi. Interdependent Infrastructure System Risk and Resilience to Natural Hazards. Proceedings of the 2019 IISE Annual Conference. H.E. Romeijn, A. Schaefer, and R. Thomas (Eds.). 
  2. Obringer, R. and Nateghi, R. (2019) Multivariate modeling for sustainable and resilient infrastructure systems and communities.Proceedings of the 2019 IISE Annual Conference. H.E. Romeijn, A. Schaefer, and R. Thomas (Eds.). 
  3. S. Mukhopadhyay, R. Nateghi. Climate—demand nexus to support long-term adequacy planning in the energy sector, IEEE Xplore 2017 (selected as one of the best conference paper submitted to Power &Energy General Meeting in 2017)
  4. R. Nateghi, Allison Reilly, All-hazard approaches to infrastructure risk reduction: Effective investments through pluralism, 27th European Safety and Reliability Conference (ESREL 2017, Portorož, Slovenia, June 18-22, 2017).
  5. M. Ostovari, D. Yu, B. Katare, C.G. Shields, K. J. Musselman, M. Adibuzzaman, Q. Ye, S. Xie, R. Nateghi, Y. Yih, Bridging the gap between population needs and barriers into onsite clinic use, Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60 (1):1809-1812. doi: 10.1177/1541931213601413.
  6. R. Nateghi, T. Aven. A framework for conceptualizing the performance of and assessing the risks to systems, Safety and Reliability of Complex Engineered Systems - Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015, Pages 839-845.
  7. A. Staid, S.D. Guikema, R. Nateghi, S.M. Quiring, M. Gao. Assessing the sensitivity of power distribution systems in U.S. Metropolitan areas to climate-induced hurricane impacts, Safety and Reliability of Complex Engineered Systems - Proceedings of the 25th European Safety and Reliability Conference, ESREL2015, Pages 4333-4339.
  8. Staid, S.D. Guikema, R. Nateghi, S.M. Quiring, M. Gao, 2014. Simulation methods to assess long-term hurricane impacts to U.S. power systems, PSAM 2014 - Probabilistic Safety Assessment and Management
  9. S.D. Guikema, R. Nateghi, T. Aven, 2013. Multi-hazard risk assessment: moving beyond single, probabilistic models. 11th International Conference on Structural Safety & Reliability (ICOSSAR), New York, NY, 2013, 1233–1238.
  10. S.D. Guikema, R. Nateghi, S.M. Quiring, 2013. Storm power outage prediction modeling. Annual European Safety and Reliability (ESREL) Conference. Amsterdam, Netherlands, 2013, 3089–3096.
  11. S.D. Guikema, Udoh, I., Irish, J. & Nateghi, R. The effects of hurricane surge in power system outage risk models. 11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference, PSAM11 ESREL 2012. Vol. 7, 5740–5746.
  12. R. Nateghi, S.D. Guikema, 2010. A comparison of top-down statistical models with bottom-up methods for power system reliability estimation in high wind events. The International Conference on Vulnerability and Risk Analysis and Management (ICVRAM), College Park, MD, 2010: 594–601.
  13. R. Nateghi, S.D. Guikema, S.M. Quiring, 2010. Statistical modeling of power outage duration times in the event of hurricane landfalls in the U.S. 10th International Probabilistic Safety Assessment & Management Conference (PSAM), Seattle, WA, 2010: Vol. 4, 3117–3128. 

Book Chapters

  1. R. Nateghi, S.M. Quiring and S.D. Guikema. 2010. Estimating the impact of climate variability on cumulative hurricane destructive potential through data mining,” in Hurricanes and Climate Change, Edited by J.B. Elsner, R.E. Hodges, J.C. Malmstadt, and K.N. Scheitlin. Springer, New York.
  2. S.D. Guikema, R. Nateghi, Modeling hurricane power outage risk, Oxford Research Encyclopedia of Natural Hazard Science (accepted for publication) [link].

Other Publications

  1. S.D. Guikema, S.M. Quiring, R. Nateghi, A. Reilly. Predicting power outages from hurricanes: supporting emergency response planning, IAEM Bulletin.