Department of Electrical and Computer Engineering

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 Department of Electrical and Computer Engineering Research Key areas in research & development Signal Processing & Machine Learning Research Groups Geophysics, Instrumentation and Signal Processing Publications

Publications

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Gaikwad, N. B., Liu, L., Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2025). A high-duty-cycle transmitter unit for steady-state surface NMR instruments. Geoscientific Instrumentation, Methods and Data Systems, 14(2), 139-151. https://doi.org/10.5194/gi-14-139-2025
Vang, M., Larsen, J. J., Christiansen, A. V. & Grombacher, D. (2025). Alleviating interpretational ambiguity in hydrogeology through clustering-based analysis of transient electromagnetic and surface nuclear magnetic resonance data. Hydrology and Earth System Sciences, 29(20), 5315-5329. https://doi.org/10.5194/hess-29-5315-2025
Liu, L., Domenzain Gonzalez, D., Vela, I., Maurya, P. K., Kühl, A. K., Bording, T., Ejlskov, P., Auken, E., Larsen, J. J. & Christiansen, A. V. (2025). An efficient cross-borehole direct current resistivity monitoring instrument. Geophysics, 90(2), D61-D70. https://doi.org/10.1190/geo2023-0518.1
Larsen, J. J., Asif, M. R. & Rafiei Foroushani, M. (2025). Benchmarking deep learning models for wetland mapping in Denmark using high-resolution earth observation data. Abstract from EGU General Assembly 2025, Vienna, Austria. https://doi.org/10.5194/egusphere-egu25-4365
Asif, M. R., Kass, M. A., Herpe, M., Rawlinson, Z., Westerhoff, R., Larsen, J. J. & Christiansen, A. V. (2025). Comparative analysis of deep learning and traditional airborne electromagnetic data processing: A case study. Geophysics, 90(3), WA103-WA112. https://doi.org/10.1190/geo2024-0282.1
Vang, M. Ø., Grombacher, D., Larsen, J. J. & Wilson, S. (2025). Efficient mapping of complex groundwater systems associated with braided rivers using small coil surface nuclear magnetic resonance. Geophysics, 90(3), 1-12. https://doi.org/10.1190/geo2023-0765.1
Asif, M. R., Kass, A., Larsen, J. J. & Christiansen, A. V. (2025). Identifying Induced Polarization Effects in TEM Data by Deep Learning. In 7th Asia Pacific Meeting on Near Surface Geoscience and Engineering, NSGE 2025 (pp. 1-5). European Association of Geoscientists and Engineers, EAGE. https://doi.org/10.3997/2214-4609.202572056
Grombacher, D., Griffiths, M. P., Kass, M. A. & Larsen, J. J. (2024). An investigation of factors affecting the depths of steady-state surface nuclear magnetic resonance signals. Geophysics, 89(2), J9-J17. https://doi.org/10.1190/geo2023-0068.1
Khare, S. K., McLachlan, P., Maurya, P. K. & Larsen, J. J. (2024). An optimized and hybrid gating scheme for the suppression of very low-frequency radios in transient electromagnetic systems. Geoscientific Instrumentation, Methods and Data Systems, 13(1), 27-41. https://doi.org/10.5194/gi-13-27-2024
Asif, MR., Larsen, JJ. & Christiansen, AV. (2024). Automated Processing of Time-Domain Electromagnetic Data Influenced by Induced Polarization Effects. In NSG 2024 30th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420140
Vang, M. Ø., Grombacher, D., Larsen, J. J. & Christiansen, A. V. (2024). Clustering on SNMR and TEM parameters over a saline-freshwater interface to resolve hydrogeological layers. In NSG2024, 30th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420102
Vang, M. Ø., Grombacher, D., Larsen, J. J. & Christiansen, A. V. (2024). Extrapolating sparse SNMR data sets onto dense TEM coverage using spatially variable correlations. Abstract from AGU Fall meeting 2024, Washington DC, United States.
Larsen, J. J., Kass, M. A., Grombacher, D. & Griffiths, M. P. (2024). Feasibility of Surface Nuclear Magnetic Resonance With Absurdly Long Excitation Pulses. Geophysical Research Letters, 51(20), Article e2024GL110826. https://doi.org/10.1029/2024GL110826
Hardenberg, M., Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2024). Feasibility study of steady-state surface NMR with adiabatic pulses. In NSG2024, 30th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420051
Griffiths, M. P., Grombacher, D., Mashhadi, S. R. & Larsen, J. J. (2024). Ground-truth Validation of T2 Estimates from Steady-state Surface NMR. Abstract from AGU Fall meeting 2024, Washington DC, United States.
Griffiths, M. P., Grombacher, D., Mashhadi, S. R. & Larsen, J. J. (2024). Ground-Truth Validation of T2 Estimates From Steady-State Surface NMR. Geophysical Research Letters, 51(24), Article e2024GL112094. https://doi.org/10.1029/2024GL112094
Asif, M. R., Kass, A., Larsen, J. J. & Christiansen, A. V. (2024). Identification of Induced Polarization affected Transient Electromagnetic Data by Deep Learning. Poster session presented at AGU Fall meeting 2024, Washington DC, United States. https://ui.adsabs.harvard.edu/abs/2024AGUFMNS23B1231A/abstract
Grombacher, D., Griffiths, M. P., Vang, M. Ø., Kass, M. A. & Larsen, J. J. (2024). Observation of spikelets in steady-state surface nuclear magnetic resonance data. Geophysics, 89(2), J1-J8. https://doi.org/10.1190/GEO2023-0145.1
Kamble, K., Jensen, C. E. H. & Larsen, J. J. (2024). Optimized Suppression of VLF Radio Noise in Time-lapse Transient Electromagnetic Data. Abstract from AGU Fall meeting 2024, Washington DC, United States.
Naveed, K., Madsen, L. M., Grombacher, D. & Larsen, J. J. (2024). Processing Time-domain Induced Polarization Data Using Variational Mode Decomposition. IEEE Transactions on Geoscience and Remote Sensing, 62, 1-13. Article 5905713. https://doi.org/10.1109/TGRS.2024.3362290
Larsen, J. J., Kass, A., Grombacher, D. & Griffiths, M. P. (2024). Surface NMR with Very Long Transmitter Pulses. Abstract from AGU Fall meeting 2024, Washington DC, United States.
Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2024). Synthetic studies to investigate the ability of steady-state surface NMR to resolve T2. In NSG 2024 30th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420092
Naveed, K. & Larsen, J. J. (2024). Variational Mode Decomposition Based Processing of Surface NMR Data. In NSG2024, 30th European Meeting of Environmental and Engineering Geophysics European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420100
Gaikwad, N., Liu, L., Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2023). A High Duty Cycle Transmitter Unit for Steady-State Surface NMR Instruments. (pp. 1-22). Geoscientific Instrumentation, Methods and Data Systems https://doi.org/10.5194/gi-2023-5
Griffiths, M. P., Grombacher, D., Kass, M. A., Vang, M., Liu, L. & Larsen, J. J. (2023). A surface NMR forward in a dot product. Geophysical Journal International, 234(3), 2284-2290. https://doi.org/10.1093/gji/ggad203
Asif, M. R., Foged, N., Bording, T. S., Larsen, J. J. & Christiansen, A. V. (2023). DL-RMD: a geophysically constrained electromagnetic resistivity model database for deep learning applications. Earth System Science Data, 15(3), 1389-1401. https://doi.org/10.5194/essd-2022-345, https://doi.org/10.5194/essd-15-1389-2023
Liu, L., Grombacher, D., Griffiths, M., Vang, M. & Larsen, J. J. (2023). Signal Processing Steady-State Surface NMR Data. IEEE Transactions on Instrumentation and Measurement, 72, Article 6502313. https://doi.org/10.1109/TIM.2023.3264033
Vang, M., Grombacher, D., Larsen, J. J. & Wilson, S. (2023). SMALL COIL SURFACE NUCLEAR MAGNETIC RESONANCE FOR SHALLOW RESOLUTION OF RIVERS IN NEW ZEALAND. Proceedings of the Symposium on the Application of Geophyics to Engineering and Environmental Problems, SAGEEP, 2023-April.
Vang, M., Grombacher, D., Larsen, J. J. & Wilson, S. (2023). Small coil surface nuclear magnetic resonance in dynamic river systems in New Zealand. In 2nd Conference on Hydrogeophysics 2023, Held at Near Surface Geoscience Conference and Exhibition 2023, NSG 2023 European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202320070
Vang, M., Grombacher, D., Griffiths, M. P., Liu, L. & Larsen, J. J. (2023). Technical note: High-density mapping of regional groundwater tables with steady-state surface nuclear magnetic resonance - three Danish case studies. Hydrology and Earth System Sciences, 27(16), 3115-3124. https://doi.org/10.5194/hess-27-3115-2023
Naveed, K., Meldgaard Madsen, L., Grombacher, D. & Larsen, J. J. (2023). Variational Mode Decomposition-Based Processing of Time-Domain Induced Polarization Data. Abstract from NSG2023 29th European Meeting of Environmental and Engineering Geophysics, Edinburgh , United Kingdom. https://doi.org/10.3997/2214-4609.202320133
Asif, M. R., Bording, T. S., Maurya, P. K., Zhang, B., Fiandaca, G., Grombacher, D. J., Christiansen, A. V., Auken, E. & Larsen, J. J. (2022). A Neural Network-Based Hybrid Framework for Least-Squares Inversion of Transient Electromagnetic Data. IEEE Transactions on Geoscience and Remote Sensing, 60, Article 4503610. https://doi.org/10.1109/TGRS.2021.3076121
Griffiths, M., Grombacher, D., Kass, M. A., Liu, L., Vang, M. & Larsen, J. J. (2022). A Reformulated Surface Nmr Forward For Multi-Sequence Acquisitions. In 28th European Meeting of Environmental and Engineering Geophysics, Held at the Near Surface Geoscience Conference and Exhibition 2022, NSG 2022 European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202220109
Kass, M. A., Grombacher, D., Griffiths, M., Vang, M. Ø., Liu, L. & Larsen, J. J. (2022). A steady-state approach to surface nuclear magnetic resonance. In Proceedings of the Symposium on the Application of Geophyics to Engineering and Environmental Problems, SAGEEP (pp. 54). J and N Group, Ltd.. https://www.eegs.org/assets/docs/Symposium/2022SAGEEP/AbstractsbyAuthor/Kass%2C%20A%20STEADY-STATE%20APPROACH%20TO%20SURFACE%20NUCLEAR%20MAGNETIC%20RESONANCE%20-%20SAGEEP%202022%20-%20205367449.pdf
Asif, M. R., Maurya, P. K., Foged, N., Larsen, J. J., Auken, E. & Christiansen, A. V. (2022). Automated transient electromagnetic data processing for ground-based and airborne systems by a deep learning expert system. IEEE Transactions on Geoscience and Remote Sensing, 60, Article 5919814. https://doi.org/10.1109/TGRS.2022.3202304
Asif, M. R., Larsen, J. J., Auken, E. & Christiansen, A. V. (2022). Deep Convolutional Auto-Encoder for Automated Processing of Airborne Time-Domain Electromagnetic Data. 1-5. Paper presented at NSG2022 3rd Conference on Airborne, Drone and Robotic Geophysics, Beograd, Serbia. https://doi.org/10.3997/2214-4609.202220038
Asif, M. R., Maurya, P. K., Christiansen, A. V., Larsen, J. J. & Auken, E. (2022). Deep learning based expert system to automate time-domain electromagnetic data processing. In 34th Symposium on the Application of Geophysics to Engineering and Environmental Problems, SAGEEP 2022 (pp. 6). J and N Group, Ltd..
Larsen, J. J., Langhof, R. B., Kjær, M. W., Vang, M., Liu, L., Griffiths, M. & Grombacher, D. (2022). Efficient processing of surface NMR data with spectral analysis. Geophysical Journal International, 229(1), 286-298. https://doi.org/10.1093/gji/ggab472
Kjaer-Rasmussen, A., Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2022). Fast removal of powerline harmonic noise from surface NMR datasets using a projection-based approach on graphical processing units. IEEE Geoscience and Remote Sensing Letters, 19, Article 8024005. https://doi.org/10.1109/LGRS.2021.3118064
Griffiths, M. P., Grombacher, D., Liu, L., Vang, M. Ø. & Larsen, J. J. (2022). Forward Modeling Steady-State Free Precession in Surface NMR. IEEE Geoscience and Remote Sensing Letters, 60, Article 4513510. https://doi.org/10.1109/TGRS.2022.3221624
Grombacher, D., Griffiths, M. P., Liu, L., Vang, M. & Larsen, J. J. (2022). Frequency Shifting Steady-State Surface NMR Signals to Avoid Problematic Narrowband-Noise Sources. Geophysical Research Letters, 49(7), Article e2021GL097402. https://doi.org/10.1029/2021GL097402
Asif, M. R., Foged, N., Maurya, P. K., Grombacher, D. J., Christiansen, A. V., Auken, E. & Larsen, J. J. (2022). Integrating neural networks in least-squares inversion of airborne time-domain electromagnetic data. Geophysics, 87(4), E177-E187. https://doi.org/10.1190/geo2021-0335.1
Asif, M. R., Maurya, P. K., Larsen, J. J. & Christiansen, A. V. (2022). Investigating the Integration of Neural Networks in Least-Squares Method for Airborne Electromagnetic Data Inversion. 1-5. Paper presented at NSG2022 3rd Conference on Airborne, Drone and Robotic Geophysics, Beograd, Serbia. https://doi.org/10.3997/2214-4609.202220034
McLachlan, P. J., Khare, S. K., Grombacher, D., Larsen, J. J., A. Christiensen, A. & Luria, J. C. Z. (2022). On The Presence of Correlated Noise in Transient Electromagnetic (Tem) Monitoring Data. 1-5. Abstract from NSG2022 28th European Meeting of Environmental and Engineering Geophysics, Belgrade , Serbia. https://doi.org/10.3997/2214-4609.202220119
McLachlan, P. J., Khare, S. K., Grombacher, D., Larsen, J. J., Christensen, A. & Zamora Luria, J. C. (2022). On The Presence of Correlated Noise in Transient Electromagnetic (Tem) Monitoring Data. In NSG2022 28th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202220119
Larsen, J. J., Lévy, L. & Asif, M. R. (2022). Removal of powerline noise in geophysical data sets with a scientific machine-learning based approach. IEEE Transactions on Geoscience and Remote Sensing, 60, Article 5923410. https://doi.org/10.1109/TGRS.2022.3223737
Kremer, T., Irons, T., Müller-Petke, M. & Juul Larsen, J. (2022). Review of Acquisition and Signal Processing Methods for Electromagnetic Noise Reduction and Retrieval of Surface Nuclear Magnetic Resonance Parameters. Surveys in Geophysics, 43(4), 999-1053. https://doi.org/10.1007/s10712-022-09695-3
Gaikwad, N., Liu, L., Griffiths, M. P., Vang, M. Ø., Grombacher, D. & Larsen, J. J. (2022). Thermal Model of the Apsu Transmitter for Lightweight and Compact Heat Sink Design. 11-13. Abstract from The 8th International Workshop on Magnetic Resonance Sounding, Strasbourg, France. https://mrs2021.sciencesconf.org/data/pages/proceedings_MRS2021_distrib_v2.pdf
Larsen, J. J., Griffiths, M., Vang, M., Liu, L. & Grombacher, D. (2021). Apsu - A compact surface NMR instrument for groundwater investigations. In SEG Technical Program Expanded Abstracts 2021 (pp. 3135-3139). Society of Exploration Geophysicists. https://doi.org/10.1190/segam2021-3582046.1
Kass, M. A., Auken, E., Larsen, J. J. & Christiansen, A. V. (2021). A towed magnetic gradiometer array for rapid, detailed imaging of utility, geological, and archaeological targets. Geoscientific Instrumentation, Methods and Data Systems, 10(2), 313-323. https://doi.org/10.5194/gi-10-313-2021

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Revised 13.11.2025
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Jakob Juul Larsen