Skip navigation

Publications

Journal Publications

Published

  1. Y. Qiao, S. Chen, T.U. Saeed, R. Nateghi, S. Labi. Acquiring insights on repair policy using discrete choice models. Transportation Research part A: Policy and Practice (accepted for publication).  [link]
  2.  R. Obringer, R. Nateghi, Predicting Reservoir Levels Using Statistical Learning Techniques, Scientific Reports, 8(1):5164.[link]
  3. S. Mukhopadhyay, R. Nateghi, Makaradn Hastak. 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]
  4. 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]
  5. M. Lokhandwala, R. Nateghi, 2018. Leveraging advanced predictive analytics to assess commercial cooling load in the U.S., Journal of Sustainable Production and Consumption,14, pp.66-81. [link]
  6. 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]
  7. 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]
  8. S. Mukhopadhyay, R. Nateghi, 2017. Climate sensitivity of energy consumption in the built environment: an application to the state of Florida, Journal of Energy , 128: 688-700. [link]
  9. 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 One11(8), p.e0158375. [link]
  10. 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 Anal. 36(1): 4-15. [link]
  11. 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]
  12. 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]
  13. R. Nateghi, S.D. Guikema S.M. Quiring, 2014. Forecasting hurricane-induced power outage durations. Nat. Haz. 74:1795–1811. [link]
  14. R. Nateghi, S.D. Guikema, and S.M. Quiring, 2013. Power outage estimation for tropical cyclones: improved accuracy with simpler models, Risk Anal. 34 (6):1069-1078. [link]
  15. R. Nateghi, S.D. Guikema, S.M. Quiring, 2011. Comparison and validation of statistical methods for predicting power outage durations during hurricanes, Risk Anal. 31(12):1897-1906. [link]
  16. 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. S. Mukhopadhyay, R. Nateghi. A place-based, sectoral, data-driven approach to assess inadequacy risks in the electric power system under climate variability. Journal of Risk Analysis (under second review).
  2. 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, Journal of Climatic Change.
  3. S. Mukhopadhyay, Vineeth CR, R. Nateghi Evaluating regional climate-electricity demand nexus: A composite Bayesian predictive framework. Applied Energy.
  4. Pamela Murray-Tuite, Haizhong Wang, Christopher Zobel, Y. Gurt Ge, R. Nateghi. Critical Time and Space Considerations for Data and Modeling in Interdisciplinary Hazards and Disasters Research, Journal of Risk Analysis.
  5. R. Nateghi, Pamela Murray-Tuite. The Frontiers of Uncertainty Estimation and Communication in Interdisciplinary Disaster Research, Journal of Risk Analysis (under second review).
  6. Y. Gurt Ge, Christopher Zobel, Pamela Murray-Tuite, Haizhong Wang, & R. Nateghi. Consideration and Guidance of Building an Interdisciplinary Disaster Research, Journal of Risk Analysis (under second review).
  7. B.C. Bruss, R. Nateghi, B. Zaitchick. When the well runs dry: Predicting observed GRACE satellite groundwater storage trends, Frontiers in Environmental Science.
  8. B. Rachunok, R. Nateghi, B. Katare, V. Meimand. Predicting the influence of local environment on changes in county-level obesity rates: 2007-2015, PloS One.

In Preparation

  1. E. Wongso, R. Nateghi, B. Zaitchik, S. Quiring, R. KumarPredictive modeling and statistical inferencing to characterize the U.S. water footprint. Water Research Journal.
  2. P. Ajidarma, S. Gong, L.N.R. Nanduri, R. Nateghi. A comparative assessment of advanced statistical and machine learning techniques for predicting electric vehicles sales in the U.S., Civil Engineering and Environmental Systems.
  3. E. Wongso, R. Nateghi. Identifying the key predictors of U.S. residential electricity consumption: a regional analysis
  4. R. Nateghi, S.D. Guikema, T. Aven. Multi-hazard risk assessment: moving beyond single, probabilistic models.
  5. S.D. Guikema, I. Udoh, J.L. Irish, R. Nateghi. The effects of hurricane surge in power system outage risk models, Nat. Haz.
  6. R. Nateghi, S.D. Guikema, M. Gao. Evaluating risk mitigation investments in coastal power systems prone to hurricane impacts.
  7. S.D., Guikema, S.M. Quiring, K. Buckstaff, M. Beck, B. McRoberts, R. Nateghi, T. Logan. Storm damage and restoration labor estimation: An all-weather model, Access, IEEE.

Conference Proceedings

  1. 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)
  2. R. Nateghi, Allison Reilly, All-hazard approaches to infrastructure risk reduction: Effective investments through pluralism, 27th European Safety and Reliability Conference (ESREL 2017, Portoro┼ż, Slovenia, June 18-22, 2017).
  3. 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.
  4. 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.
  5. 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.
  6. 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
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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)

Other Publications

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