Daniel O'Malley

Education

• Ph.D., Applied Mathematics
• Purdue University
• 2011

• Masters of Science, Pure Mathematics
• Purdue University
• 2006

• Bachelors of Science, Computer Science and Mathematics
• Purdue University
• 2004

Positions

• 2016 - Present | Scientist
• 2015 - 2016 | Director's Postdoctoral Fellow
• 2013 - 2015 | Postdoctoral Research Associate

Awards

• Director's Postdoctoral Fellow (2014)
• InterPore Fraunhofer Award for Young Researchers (2012)
• Charles C. Chapelle Fellowship (2004)

Professional Societies

• American Geophysical Union (AGU)
• International Society for Porous Media (InterPore)
• Society of Industrial and Applied Mathematics (SIAM)

Publications

• O’Malley, D., S. Karra, J.D. Hyman, H.S. Viswanathan, G. Srinivasan. Efficient Monte Carlo with graph-based subsurface flow and transport models. Water Resources Research. 2018. (DOI: 10.1029/2017WR022073)
• Lovell, A.E., S. Srinivasan, S. Karra, D. O’Malley, N. Makedonska, H.S. Viswanathan, G. Srinivasan, J.W. Carey, L.P. Frash. Extracting hydrocarbon from shale: an investigation of the factors that influence the decline and the tail of the production curve. Water Resources Research. 2018. (DOI: 10.1029/2017WR022180)
• Qian, E., B. Peherstorfer, D. O’Malley, V.V. Vesselinov, K. Willcox. Multifidelity Monte Carlo estimation of variance and sensitivity indices. SIAM/ASA Journal on Uncertainty Quantification. 6:683. 2018. (DOI: 10.1137/17M1151006)
• O’Malley, D. An approach to quantum-computational inverse analysis. Scientific Reports. 8:6919. 2018. (DOI: 10.1038/s41598-018-25206-0)
• Karra, S., D. O’Malley, J.D. Hyman, H. Viswanathan, G. Srinivasan. Modeling flow and transport in fracture networks using graphs. Physical Review E. 97:033304. 2018. (DOI: 10.1103/PhysRevE.97.033304)
• Moore, B.A., E. Rougier, D. O'Malley, G. Srinivasan, A. Hunter, and H. Viswanathan. Predictive modeling of dynamic fracture growth in brittle materials with machine learning. Computational Materials Science. 148. 2018. (DOI: 10.1016/j.commatsci.2018.01.056)
• Vesselinov, V.V., B.S. Alexandrov, and D. O'Malley. Contaminant source identification using semi-supervised machine learning. Journal of Contaminant Hydrology. 212:134. 2018. (DOI: 10.1016/j.jconhyd.2017.11.002)
• Harp, D.R., P.H. Stauffer, D. O’Malley, Z. Jiao, E.P. Egenolf, T.A. Miller, D. Martinez, K.A. Hunter, R.S. Middleton, J.M. Bielicki, and R. Pawar. Development of robust pressure management strategies for geologic CO2 sequestration. International Journal of Greenhouse Gas Control. 64:43. 2017. (DOI: 10.1016/j.ijggc.2017.06.012)
• Lin, Y., E.B. Le, D. O'Malley, V.V. Vesselinov, and T. Bui-Thanh. Large-scale inverse model analyses employing fast randomized data reduction. Water Resources Research. 53:6784. 2017. (DOI: 10.1002/2016WR020299)
• Djidjev, H., D. O'Malley, H. Viswanathan, J.D. Hyman, S. Karra, and G. Srinivasan. Learning on graphs for predictions of fracture propagation, flow and transport. IEEE Parallel and Distributed Symposium Workshops. 2017. (DOI: 10.1109/IPDPSW.2017.11)
• Bakarji, J., D. O'Malley and V.V. Vesselinov. Agent-based socio-hydrological hybrid modeling for water resource management. Water Resources Management. 2017. (DOI: 10.1007/s11269-017-1713-7)
• Hansen, S.K., B. Berkowitz, V.V. Vesselinov, D. O'Malley, S. Karra. Push-pull tracer tests: Their information content and use for characterizing non-Fickian, mobile-immobile behavior. Water Resources Research. 52:12. 2016. (DOI: 10.1002/2016WR018769)
• O'Malley, D. and V.V. Vesselinov. ToQ.jl: A high-level programming language for D-Wave machines based on Julia. IEEE High Performance Extreme Computing. 2016. (DOI: 10.1109/HPEC.2016.7761616)
• Hyman, J.D., J. Jim\'{e}nez-Martínez, H. S. Viswanathan, J. W. Carey, M. L. Porter, E. Rougier, S. Karra, Q. Kang, L. Frash, L. Chen, Z. Lei, D. O'Malley, N. Makedonska. Understanding hydraulic fracturing: a multi-scale problem. Philosophical Transactions of the Royal Society A. 374:2078. 2016. (Cover Article) (DOI: 10.1098/rsta.2015.0426)
• Lin, Y., D. O'Malley and V.V. Vesselinov. A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses. Water Resources Research. 52:6948. 2016. (DOI: 10.1002/2016WR019028)