NSE - Nuclear Science & Engineering at MIT


Haruko Murakami Wainwright, MIT

Haruko Murakami Wainwright

Mitsui Career Development Professor in Contemporary Technology
Assistant Professor of Nuclear Science and Engineering, and
Assistant Professor of Civil and Environmental Engineering


Lab website


Haruko Wainwright joined the Department of Nuclear Science and Engineering as an assistant professor in January 2022. She received her BEng in Engineering Physics from Kyoto University, Japan in 2003; her MS in nuclear engineering in 2006, MA in statistics in 2010 and PhD in nuclear engineering in 2010 from University of California, Berkeley. Before joining MIT, she was a Staff Scientist in the Earth and Environmental Sciences Area at Lawrence Berkeley National Laboratory, and an adjunct professor in Nuclear Engineering at University of California, Berkeley. Her research focuses on environmental modeling and monitoring technologies, with a particular emphasis on nuclear waste and nuclear-related contamination. She has been developing Bayesian methods for multi-type multiscale data integration and model-data integration. She leads and co-leads multiple interdisciplinary projects, including the US Department of Energy’s Advanced Long-term Environmental Monitoring Systems (ALTEMIS) project, and theArtificial Intelligence for Earth System Predictability (AI4ESP) initiative.


Integrated Environmental Monitoring at Nuclear Contaminated Sites

At nuclear contaminated sites, long-term environmental monitoring is critical to ensuring public safety and combatting misinformation. Climate change poses additional concerns since extreme weather could re-mobilize residual contaminants. We are developing a new paradigm of environmental monitoring by integrating state-of-the-art technologies: in situ sensors, geophysics, remote sensing, contaminant transport simulations and machine learning.

Nuclear Waste Disposal

Geological disposal is required to isolate nuclear waste for thousands of years. Models need to address the large uncertainty associated with geological heterogeneity and future climate. At the same time, the existing contamination from waste disposal in the 1940s–1980s provides significant insights on radionuclide mobility and datasets for model validation. We are developing uncertainty quantification (UQ) methods, including global sensitivity analysis, Bayesian parameter estimation, surrogate modeling, and experiment-to-model UQ pipelines. In parallel, we have been developing comparative analysis methodologies for quantifying the environmental impacts of nuclear waste and other energy waste.

Environmental Resilience in Nuclear Energy

Emergency responses during accidents and the recovery from contamination have been challenging in nuclear energy. We are developing science-based methodologies to prepare for, respond to, and recover from environmental disasters. Risk analysis allows us to quantify the consequence and probability of such accidents, and to identify vulnerabilities. Integrated monitoring technologies enable the rapid assessment of accident consequences and planning of the recovery. Remediation technologies have been evolving towards sustainable methods, considering net environmental impacts. Our goal is to build a comprehensive environmental resilience framework in nuclear energy.


Recent Publications

  1. Xu, Z., R. Serata, H.M. Wainwright, M. Denham, S. Molins, H. Gonzalez-Raymat, K. Lipnikov, D. Moulton, and C. Eddy-Dilek (2021), “Reactive Transport Modeling for Supporting Climate Resilience at Groundwater Contamination Sites”, Hydrology and Earth System Sciences, accepted.
  2. Li, W., Wainwright, H. M., Yan, Q., Zhou, H., Dafflon, B., Wu, Y., ... & Tartakovsky, D. M. (2021), “Estimation of evapotranspiration rates and root water uptake profiles from soil moisture sensor array data”, Water Resources Research, e2021WR030747.
  3. Lu, H., Ermakova, D., Wainwright, H. M., Zheng, L., & Tartakovsky, D. M. (2021). “Data-informed Emulators for Multi-Physics Simulations”, Journal of Machine Learning for Modeling and Computing, 2(2).
  4. Ermakova, D., Wainwright, H., Zheng, L., Shirley, I., & Lu, H. (2021). “Global Sensitivity Analysis for U (VI) Transport for Integrating Coupled Thermal–Hydrological–Chemical Processes Models Into Performance Assessment Model.” Journal of Nuclear Engineering and Radiation Science, 7(4), 041902.
  5. Wainwright, H. M. et al. (2020), “Satellite-derived foresummer drought sensitivity of plant productivity in Rocky Mountain headwater catchments: spatial heterogeneity and geological-geomorphological control”, Environmental Research Letters, 15(8), 084018.
  6. Denham, M. E., Amidon, M. B., Wainwright, H. M., Dafflon, B., Ajo-Franklin, J., & Eddy-Dilek, C. A. (2020). “Improving Long-term Monitoring of Contaminated Groundwater at Sites where Attenuation-based Remedies are Deployed”, Environmental Management, 1-20.
  7. Sun, D., Wainwright, H. M., Oroza, C. A., Seki, A., Mikami, S., Takemiya, H., & Saito, K., (2020. “Optimizing long-term monitoring of radiation air-dose rates after the Fukushima Daiichi Nuclear Power Plant”, Journal of Environmental Radioactivity, 220, 106281
  8. Wainwright, H. M., Seki, A., Mikami, S., & Saito, K. (2019). “Characterizing regional-scale temporal evolution of air dose rates after the Fukushima Daiichi Nuclear Power Plant accident”, Journal of environmental radioactivity, 210, 105808.
  9. Wainwright, H., Arora, B., Hubbard, S., Lipnikov, K., Moulton, D., Flach, G., ... & Denham, M., “Sustainable Remediation in Complex Geologic Systems”, The Heaviest Metals: Science and Technology of the Actinides and Beyond, 415, 2019.
  10. Schmidt. F., Wainwright, H.M, Faybishenko, M. Denham, C. Eddy-Dilek, “In-Situ Monitoring of Groundwater Contamination for Sustainable Remediation Using the Kalman Filter”, Environmental Science and Technologies, 52 (13), pp 7418–7425, 2018.