Our team has a diverse background. We’ve compiled relevant publications from their expertise that contributes to the scope of CLEAN EARTH. We invite you to read their publications. 

  • Cerrai, D., Wanik, D.W., Bhuiyan, M.A.E., Zhang, X., Yang, J., Frediani, M.E. and Anagnostou, E.N., 2019. Predicting storm outages through new representations of weather and vegetation. IEEE Access7, pp.29639-29654.
  • Wanik, D.W., Anagnostou, E.N., Astitha, M., Hartman, B.M., Lackmann, G.M., Yang, J., Cerrai, D., He, J. and Frediani, M.E.B., 2018. A case study on power outage impacts from future hurricane sandy scenarios. Journal of Applied Meteorology and Climatology57(1), pp.51-79.
  • Yang, F., Wanik, D.W., Cerrai, D., Bhuiyan, M.A.E. and Anagnostou, E.N., 2020. Quantifying uncertainty in machine learning-based power outage prediction model training: A tool for sustainable storm restoration. Sustainability12(4), p.1525.
  • Cerrai, D., Koukoula, M., Watson, P. and Anagnostou, E.N., 2020. Outage prediction models for snow and ice storms. Sustainable Energy, Grids and Networks21, p.100294.
  • Cerrai, D., Watson, P. and Anagnostou, E.N., 2019. Assessing the effects of a vegetation management standard on distribution grid outage rates. Electric Power Systems Research175, p.105909.
  • Alpay, B.A., Wanik, D., Watson, P., Cerrai, D., Liang, G. and Anagnostou, E., 2020. Dynamic modeling of power outages caused by thunderstorms. Forecasting2(2), pp.151-162.
  • Watson, P.L., Cerrai, D., Koukoula, M., Wanik, D.W. and Anagnostou, E., 2020. Weather‐related power outage model with a growing domain: structure, performance, and generalisability. The Journal of Engineering2020(10), pp.817-826.
  • Yang, F., Cerrai, D. and Anagnostou, E.N., 2021. The effect of lead-time weather forecast uncertainty on outage prediction modeling. Forecasting3(3), pp.501-516.
  • Hughes, W., Zhang, W., Cerrai, D., Bagtzoglou, A., Wanik, D. and Anagnostou, E., 2022. A Hybrid Physics-Based and Data-Driven Model for Power Distribution System Infrastructure Hardening and Outage Simulation. Reliability Engineering & System Safety, p.108628.
  • Taylor, W.O., Watson, P.L., Cerrai, D. and Anagnostou, E., 2022. A statistical framework for evaluating the effectiveness of vegetation management in reducing power outages caused during storms in distribution networks. Sustainability14(2), p.904.
  • Taylor, W.O., Watson, P.L., Cerrai, D. and Anagnostou, E.N., 2022. Dynamic modeling of the effects of vegetation management on weather-related power outages. Electric Power Systems Research207, p.107840.
  • Udeh, K., Wanik, D.W., Cerrai, D., Aguiar, D. and Anagnostou, E., 2022, January. Autoregressive Modeling of Utility Customer Outages with Deep Neural Networks. In 2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 0406-0414). IEEE.
  • Cerrai, D., Watson, P., Yang, F., Koukoula, M. and Anagnostou, E., 2020. Storm Power Outage Prediction and Verification using NWP Models and Remote Sensing Data. In IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium (pp. 3943-3946). IEEE.