Publications
94 entries (content: 81, overrides: 0, legacy: 0, PDF: 14).
Mudunuru, M., Ahmmed, B., Rau, E., Vesselinov, V.V., Karra, S., Machine Learning for Geothermal Resource Exploration in Tularosa Basin, New Mexico, Energies, 2023. PDF
Solander, K.C., Talsma, C.J., Vesselinov, V.V., The drivers and predictability of wildfire re-burns in the western United States (US), Environ. Res.: Climate 2, 2023, 10.1088/2752-5295/acb079 PDF
Mudunuru, M., Vesselinov, V.V., Ahmmed, B., Geothermalcloud: Machine learning for geothermal resource exploration, Journal of Machine Learning for Modeling and Computing, 10.1615/JMachLearnModelComput.2022046445, 2022. PDF
Rupe, A., Vesselinov, V.V., Crutchfield, J.P., Nonequilibrium statistical mechanics and optimal prediction of partially-observed complex systems, New Journal of Physics, 10.1088/1367-2630/ac95b7, 2022. PDF
Vesselinov, V.V., Ahmmed, B., Mudunuru, M., Karra, S., Middleton, R., Discovering hidden geothermal signatures using non-negative matrix factorization with customized k-means clustering, Geothermics, 10.1016/j.geothermics.2022.102576, 2022. PDF
Ahmmed, B, Vesselinov, V.V., Machine learning and shallow groundwater chemistry to identify geothermal prospects in the Great Basin, Renewable Energy, 10.1016/j.renene.2022.08.024, 2022. PDF
Vesselinov, V.V., Ahmmed, B., Mudunuru, M., Karra, S., Middleton, R., Discovering the Hidden Geothermal Signatures of Southwest New Mexico, World Geothermal Congress, Reykjavik, Iceland, 2021. PDF
Wu, H., O'Malley, D., Golden, J.K., Vesselinov, V.V., Inverse Analysis with Variational Autoencoders: A Comparison of Shallow and Deep Networks, Journal of Machine Learning for Modeling and Computing, 10.1615/JMachLearnModelComput.2022042093, 2022. PDF
O'Malley, D., Golden, J.K., Vesselinov, V.V., Learning to regularize with a variational autoencoder for hydrologic inverse analysis, arXiv:1906.02401v1, 2021. PDF
Fleming, S.W., Watson, J.R., Ellenson, A., Cannon, A.J., Vesselinov, V.V., Machine learning in Earth and environmental science requires education and research policy reforms, 10.1038/s41561-021-00865-3, 2021. PDF
Siler, D.L., Pepin, J.D., Vesselinov, V.V., et al., Machine learning to identify geologic factors associated with production in geothermal fields: A case-study using 3D geologic data, Brady geothermal field, Nevada, Geothermal Energy, 10.1186/s40517-021-00199-8, 2021. PDF
Morra, G., Bozdag, E., Knepley, M., Rass, L., Vesselinov, V.V., A Tectonic Shift in Analytics and Computing Is Coming, AGU EOS, 10.1029/2021EO159258, 2021. 10.1029/2021EO159258, 2021. PDF
Fleming, S.W., Vesselinov, V.V., Goodbody, A.G., Augmenting geophysical interpretation of data-driven operational water supply forecast modeling for a western US river using a hybrid machine learning approach, Journal of Hydrology, 10.1016/j.jhydrol.2021.126327, 2021. PDF
Ahmmed, B, Mudunuru, M.K., Karra, S., Vesselinov, V.V., Machine Learning to Discover Mineral Trapping Signatures due to CO2 Injection, International Journal of Greenhouse Gas Control, 10.1016/j.ijggc.2021.103382, 2021. PDF
Ahmmed, B, Mudunuru, M.K., Karra, S., James, S.C., Vesselinov, V.V., A comparative study of machine learning models for predicting the state of reactive mixing, Journal of Computational Physics, 10.1016/j.jcp.2021.110147, 2021. PDF
Mehana, M., Guiltinan, E., Vesselinov, V.V., Middleton, R., Hyman, J., Kang, Q., Viswanathan, H., Machine-Learning Predictions of the Shale Wells’ Performance, Journal of Natural Gas Science and Engineering, 10.1016/j.jngse.2021.103819, 2021. PDF
Mudunuru, M.K., Viswanathan, H.S., Carey, J. W., Chen, L., Kang, Q., Karra, S., Vesselinov, V.V., Middleton, R.S., Johnson, P.A., Subsurface energy: Flow and reactive-transport in porous and fractured media, Handbook of Porous Materials (invited), World Scientific Publishers, 10.1142/9789811223419_0004, 2020. PDF
Lopez, C.A, Vesselinov, V.V., Gnanakaran, S., Alexandrov, B.S., Unsupervised Machine Learning for Analysis of Coexisting Lipid Phases and Domain Growth in Biological Membranes, J. Chem. Theory Comput. 10.1021/acs.jctc.9b00074, 2019. PDF
Vesselinov, V.V., Mudunuru, M., Karra, S., O'Malley, D., Alexandrov, B.S., Unsupervised Machine Learning Based on Non-Negative Tensor Factorization for Analyzing Reactive-Mixing, Journal of Computational Physics, 10.1016/j.jcp.2019.05.039, 2019. PDF
Alexandrov, B.S., Stanev, V., Vesselinov, V.V., Rasmussen, K., Nonnegative tensor decomposition with custom clustering for microphase separation of block copolymers, Statistical Analysis and Data Mining, 10.1002/sam.11407, 2019. PDF
Vesselinov, V.V., Alexandrov, B.S., O'Malley, D., Nonnegative Tensor Factorization for Contaminant Source Identification, Journal of Contaminant Hydrology, 10.1016/j.jconhyd.2018.11.010, 2018. PDF
O'Malley, D., Vesselinov, V.V., Alexandrov, B.S., Alexandrov, L.B., Nonnegative/binary matrix factorization with a D-Wave quantum annealer, PlosOne, 10.1371/journal.pone.0206653, 2018. PDF
Telfeyan, K., Migdisov, A.A., Pandey, S., Vesselinov, V.V., Reimus, P.W., Long-term stability of dithionite in alkaline anaerobic aqueous solution, Applied Geochemistry, 10.1016/j.apgeochem.2018.12.015, 2018. PDF
Stanev, V., Vesselinov, V.V., Kusne, A.G., Antoszewski, G., Takeuchi,I., Alexandrov, B.A., Unsupervised Phase Mapping of X-ray Diffraction Data by Nonnegative Matrix Factorization Integrated with Custom Clustering, Nature Computational Materials, 10.1038/s41524-018-0099-2, 2018. PDF
Iliev, F.L., Stanev, V.G., Vesselinov, V.V., Alexandrov, B.S., Nonnegative Matrix Factorization for identification of unknown number of sources emitting delayed signals PLoS ONE, 10.1371/journal.pone.0193974. 2018. PDF
Stanev, V.G., Iliev, F.L., Hansen, S.K., Vesselinov, V.V., Alexandrov, B.S., Identification of the release sources in advection-diffusion system by machine learning combined with Green function inverse method, Applied Mathematical Modelling, 10.1016/j.apm.2018.03.006, 2018. PDF
Qian, E., Peherstorfer, B., O'Malley, D., Vesselinov, V.V., Wilcox, K., Multifidelity Monte Carlo Estimation of Variance and Sensitivity Indices, SIAM Journal on Uncertainty Quantification, 10.1137/17M1151006, 2018. PDF
Lu, Z., Vesselinov, V.V., Lei, H., Identifying Arbitrary Parameter Zonation using Multiple Level Set Functions, Journal of Computational Physics, 10.1016/j.jcp.2018.03.016, 2018. PDF
Hansen, S.K., He, J., Vesselinov, V.V., Characterizing the impact of model error in hydrologic time series recovery inverse problems, 10.1017/j.advwatres.2017.146.R2, Advances in Water Resources, 2018. PDF
Lin, Y., O'Malley, D., Vesselinov, V.V., Guthrie, G.D, Coblentz, D., Randomization in Characterizing the Subsurface, SIAM News, 2018. PDF
Hansen, S.K., Haslauer, C.P., Cirpka, O.A., Vesselinov, V.V., Direct Breakthrough Curve Prediction from Statistics of Heterogeneous Conductivity Fields, Water Resources Research, 10.1002/2017WR020450, 2018. PDF
Vesselinov, V.V., Mudunuru. M., Karra, S., O'Malley, D., Alexandrov, Unsupervised Machine Learning Based on Non-negative Tensor Factorization for Analysis of Filed Data and Simulation Outputs, Computational Methods in Water Resources (CMWR), Saint-Malo, France, 10.13140/RG.2.2.27777.92005, 2018. PDF
Vesselinov, V.V., O'Malley, D., Alexandrov, B.S., Contaminant source identification using semi-supervised machine learning, Journal of Contaminant Hydrology, 10.1016/j.jconhyd.2017.11.002, 2017. PDF
Hansen, S.K., Pandey, S., Karra, S., Vesselinov, V.V., CHROTRAN 1.0: A mathematical and computational model for in situ heavy metal remediation in heterogeneous aquifers, Geoscientific. Model Development, 10.5194/gmd-10-4525-2017, 10, 4525–4538, 2017. PDF
Lin, Y, Le, E.B, O'Malley, D., Vesselinov, V.V., Bui-Thanh, T., Large-Scale Inverse Model Analyses Employing Fast Randomized Data Reduction, Water Resources Research, 10.1002/2016WR020299RRR, 2017. PDF
Hansen, S.K., Vesselinov, V.V., Local equilibrium and retardation revisited, Groundwater, 10.1111/gwat.12551, 2017. PDF
Hansen, S.K., Vesselinov, V.V., Reimus, P., Lu, Z., Inferring subsurface heterogeneity from push-drift tracer tests, Water Resources Research, 10.1002/2017WR020852R, 2017. PDF
Bakarji, J., Vesselinov, V.V., O’Malley, D., Agent-based Socio-hydrological Hybrid Modeling for Water Resource Management, Water Resources Management, 10.1007/s11269-017-1713-7, 2017. PDF
Zhang, X., Sun, A.Y., Duncan, I.J., Vesselinov, V.V., Two-Stage Fracturing Wastewater Management in Shale Gas Development, Ind. Eng. Chem. Res., 10.1021/acs.iecr.6b03971, 2017. PDF
Zhang, X., Vesselinov, V.V., Integrated Modeling Approach for Optimal Management of Water, Energy and Food Security Nexus, Advances in Water Resources, 10.1016/j.advwatres.2016.12.017, 2017. PDF
O'Malley, D., Vesselinov, V.V., ToQ.jl: A high-level programming language for D-Wave machines based on Julia. IEEE High Performance Extreme Computing, 10.1109/HPEC.2016.7761616, 2016. PDF
Lin, Y, O'Malley, D., Vesselinov, V.V., A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses, Water Resources Research, 10.1002/2016WR019028, 2016. PDF
Hansen, S.K., Berkowitz, B., Vesselinov, V.V., O'Malley, D., Karra, S., Push-pull tracer tests: their information content and use for characterizing non-Fickian, mobile-immobile behavior, Water Resources Research, 10.1002/2016WR018769RR, 2016. PDF
Zhang, X., Vesselinov, V.V., Energy-Water Nexus: Balancing the Tradeoffs between Two-Level Decision Makers Applied Energy, Applied Energy, 10.1016/j.apenergy.2016.08.156, 2016. PDF
Hansen, S.K., Vesselinov, V.V., Contaminant point source localization error estimates as functions of data quantity and model quality, 10.1016/j.jconhyd.2016.09.003, 2016. PDF
Throckmorton, H., Newman, B., Heikoop, J., Perkins, G., Feng, X., Graham, D., O'Malley, D., Vesselinov, V.V., Young, J., Wullschleger, S., Wilson, C., Active layer hydrology in an arctic tundra ecosystem: quantifying water sources and cycling using water stable isotopes, Hydrological Processes, 10.1002/hyp.10883, 2016. PDF
Grasinger, M., O'Malley, D., Vesselinov, V.V., Karra, S., Decision Analysis for Robust CO2 Injection: Application of Bayesian-Information-Gap Decision Theory, International Journal of Greenhouse Gas Control, 10.1016/j.ijggc.2016.02.017, 2016. PDF
Mattis, S.A., Butler, T.D. Dawson, C.N., Estep, D., Vesselinov, V.V., Parameter estimation and prediction for groundwater contamination based on measure theory, Water Resources Research, 10.1002/2015WR017295, 2015. PDF
O’Malley, D., Vesselinov, V.V., Bayesian-Information-Gap Decision Theory (BIG-DT) with an application to CO2 sequestration, Water Resources Research, 10.1002/2015WR017413, 2015. PDF
Lu, Z., Vesselinov, V.V., Analytical Sensitivity Analysis of Transient Groundwater Flow in a Bounded Model Domain using Adjoint Method, Water Resources Research, 10.1002/2014WR016819, 2015. PDF
Barajas-Solano, D. A., Wohlberg, B., Vesselinov, V.V., Tartakovsky, D. M., Linear Functional Minimization for Inverse Modeling, Water Resources Research, 10.1002/2014WR016179, 2015. PDF
O’Malley, D., Vesselinov, V.V., Cushman, J.H., Diffusive mixing and Tsallis entropy, Physical Review E, 10.1103/PhysRevE.91.042143, 2015. PDF
O’Malley, D., Vesselinov, V.V., A combined probabilistic/non-probabilistic decision analysis for contaminant remediation, Journal on Uncertainty Quantification, SIAM/ASA, 10.1137/140965132, 2014. PDF
Vesselinov, V.V., O'Malley, D., Katzman, D., Robust Decision Analysis for Environmental Management of Groundwater Contamination Sites, In Vulnerability, Uncertainty, and Risk Quantification, Mitigation, and Management (ed. Michael Beer, Siu-Kui Au, and Jim W. Hall), 2916 pp, ISBN: 9780784413609, 10.1061/9780784413609.197, 2014. Link
O’Malley, D., Vesselinov, V.V., Cushman, J.H., A Method for Identifying Diffusive Trajectories with Stochastic Model, Journal of Statistical Physics, Springer, 10.1007/s10955-014-1035-6, 2014. PDF
Alexandrov, B., Vesselinov, V.V., Blind source separation for groundwater level analysis based on non-negative matrix factorization, Water Resources Research, 10.1002/2013WR015037, 2014. PDF
O’Malley, D., Vesselinov, V.V., Analytical solutions for anomalous dispersion transport, Advances in Water Resources, 10.1016/j.advwatres.2014.02.006, 2014. PDF
Heikoop, J.M., Johnson, T.M., Birdsell, K.H., Longmire, P., Hickmott, D.D., Jacobs, E.P., Broxton, D.E., Katzman, D., Vesselinov, V.V., Ding, M., Vaniman, D.T., Reneau, S.L., Goering, T.J., Glessner, J., Basu, A., Isotopic evidence for reduction of anthropogenic hexavalent chromium in Los Alamos National Laboratory groundwater, Chemical Geology, 10.1016/j.chemgeo.2014.02.022, 2014. PDF
Freedman, V.L., Chen, X., Finsterle, S., Freshley, M., Gorton, I., Gosink, L., Keating, E., Lansing, C., Moeglein W., Murray C., Pau, G., Porter, E., Purohit, S., Rockhold, M., Schuchardt, K., Sivaramakrishnan, C., Vesselinov, V.V., Waichler, S., A high-performance workflow system for subsurface simulation, Environmental Modelling & Software, 55, pp. 176-189, 10.1016/j.envsoft.2014.01.030, 2014. PDF
O’Malley, D., Vesselinov, V.V., Groundwater remediation using the information gap decision theory, Water Resources Research, 10.1002/2013WR014718, 2014. PDF
Harp, D.R., Vesselinov, V.V., Accounting for the influence of aquifer heterogeneity on spatial propagation of pumping drawdown, Journal of Water Resource and Hydraulic Engineering, 2(3), pp. 65-83, 2013. PDF
Vesselinov, V.V., Katzman, D., Broxton, D., Birdsell, K., Reneau, S., Vaniman, D., Longmire, P., Fabryka-Martin, J., Heikoop, J., Ding, M., Hickmott, D., Jacobs, E., Goering, T., Harp, D.R., Mishra, P., Data and Model-Driven Decision Support for Environmental Management of a Chromium Plume at Los Alamos National Laboratory (LANL), Waste Management Symposium 2013, Session 109: ER Challenges: Alternative Approaches for Achieving End State, Phoenix, AZ, http://wmsym.org, 2013. PDF
Vesselinov, V.V., Pau, G., Finsterle, S, AGNI: Coupling Model Analysis Tools and High-Performance Subsurface Flow and Transport Simulators for Risk and Performance Assessments, Computational Methods in Water Resources (CMWR 2012), 2012. PDF
Vesselinov, V.V., Harp, D., Adaptive hybrid optimization strategy for calibration and parameter estimation of physical models, Computers & Geosciences, 10.1016/j.cageo.2012.05.027, 2012. PDF
Harp, D., Vesselinov, V.V., Contaminant remediation decision analysis using information gap theory, Stochastic Environmental Research and Risk Assessment (SERRA), 10.1007/s00477-012-0573-1, 2012. PDF
Mishra, P.K., Gupta, H.V., Vesselinov, V.V.; On simulation and analysis of variable-rate pumping tests, Ground Water, 10.1111/j.1745-6584.2012.00961.x, 2012. PDF
Mishra, P.K., Vesselinov, V.V., Neuman, S.P.; Radial flow to a partially penetrating well with storage in an anisotropic confined aquifer, Journal of Hydrology, 10.1016/j.jhydrol.2012.05.010, 2012. PDF
Harp, D., Vesselinov, V.V., An agent-based approach to global uncertainty and sensitivity analysis, Computers & Geosciences, 10.1016/j.cageo.2011.06.025, 2012. PDF
Harp, D., Vesselinov, V.V., Analysis of hydrogeological structure uncertainty by estimation of hydrogeological acceptance probability of geostatistical models, Special issue of Uncertainty Quantification (invited), Advances in Water Resources, 10.1016/j.advwatres.2011.06.007, 2012. PDF
Mishra, P.K., Vesselinov, V.V., Unified Analytical Solution for Radial Flow to a Well in a Confined Aquifer, arXiv:1110.5940, 2011. PDF
Vesselinov, V.V., Harp, D., Decision support based on uncertainty quantification of model predictions of contaminant transport, CMWR 2010: XVIII International Conference on Water Resources, J. Carrera (Ed), CIMNE, Barcelona 2010. PDF
Harp, D., Vesselinov, V.V., Identification of Pumping Influences in Long-Term Water Level Fluctuations, Ground Water, 10.1111/j.1745-6584.2010.00725.x., 2010. PDF
Morales-Casique, E, Neuman, S.P., Vesselinov, V.V., Maximum Likelihood Bayesian Averaging of air flow models in unsaturated fractured tuff using Occam and variance windows, Special issue of Stochastic Environmental Research and Risk Assessment (SERRA) Journal celebrating 70th anniversary of Shlomo P Neuman, vol. 24, 10.1007/s00477-010-0383-2, 2010. PDF
Harp, D., Vesselinov, V.V., Stochastic inverse method for estimation of geostatistical representation of hydrogeologic stratigraphy using borehole logs and pressure, invited, Special issue of Stochastic Environmental Research and Risk Assessment (SERRA) Journal celebrating 70th anniversary of Shlomo P Neuman, vol. 24, 10.1007/s00477-010-0403-2, 2010. PDF
Vrugt, J., Stauffer, P., Wöhling, Th., Robinson, B., Vesselinov, V.V., Inverse Modeling of Subsurface Flow and Transport Properties Using Recent Advances in Global Optimization, Parallel Computing and Sequential Data Assimilation, Vadose Zone Journal, pp 843-864, 2008. PDF
Morales-Casique, E., Neuman, S.P., Vesselinov, V.V., Maximum likelihood Bayesian averaging of air flow models in unsaturated fractured tuff, pp.70-75, IAHS Publication 320, ISBN 978-1-901502-49-7, 2008. PDF
Harp, D., Dai, Z., Wolfsberg, A., Vrugt, J., Robinson, B., Vesselinov, V.V., Aquifer structure identification using stochastic inversion. Geophysical Research Letters L08404, 10.1029/2008GL033585, 2008. PDF
Vesselinov, V.V., Uncertainties In Transient Capture-Zone Estimates, Computational Methods in Water Resources XVI, (edited by P. Binning, P. Engesgaard, H. Dahle, G. Pinder & W. Gray), Balkema, Rotterdam, ISBN 90-5809-124-4, pp. 307-314, 2006. PDF
Vrugt, J.A, Robinson, B.A., Vesselinov, V.V., Improved Inverse Modeling in Geophysics: Combined Parameter and State Estimation, Geophysical Research Letters, v.32, L18408, 10.1029/2005GL023940, 2005. PDF
Vesselinov, V.V., Estimation of parameter uncertainty using inverse model sensitivities, Computational Methods in Water Resources XV (CMWR 2004) (ed. Miller, C., Farthing, M.W., Gray, W.G., Pinder, G.), Elsevier, ISBN 0-444-51839-8, pp. 508-514, 10.1016/S0167-5648(04)80139-4, 2004. PDF
Hyun et al 2002 PDF
Keating 2002 model coupling GW PDF
Miller et al PDF
Mishra et al 2012 Confined aquifer JH PDF
Talsma et al 2022 Characterizing Drought Behavior in the Colorado River Basin Using Unsupervised PDF
Vesselinov and Robinson 2005 Delineation of capture zones in transient groundwater flow systems ModelCARE PDF
Vesselinov et al 2015 Model Assisted Decision Analyses Related to a Chromium Plume at Los Alamos National Laboratory PDF
Vesselinov OMalley Katzman 2016 ZEM Integrated Framework for Real Time Data and Model Analyses for Robust Environmental Management Decision Making PDF