Ali Siahkoohi

PhD Student

Georgia Institute of Technology

alisk@gatech.edu CV GitHub Google Scholar

Research Experience

Google
Research Intern

Georgia Institute of Technology
Graduate Research Assistant

The University of British Columbia
Graduate Research Assistant

Research Areas

Deep Learning, Natural Language Processing, Inverse Problems, Uncertainty Quantification, Signal Processing

Publications

Felix J. Herrmann, Ali Siahkoohi, Rafael Orozco, Gabrio Rizzuti, Philipp A. Witte, and Mathias Louboutin. Learned wave-based imaging—variational inference at scale. Talk at Delft. June. 2021.
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Ali Siahkoohi, Rafael Orozco, Gabrio Rizzuti, Philipp A. Witte, Mathias Louboutin, and Felix J. Herrmann. Fast and reliability-aware seismic imaging with conditional normalizing flows. Intelligent illumination of the Earth Workshop. June. 2021.
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Mathias Louboutin, Ali Siahkoohi, Rongrong Wang, and Felix J. Herrmann. Low-memory stochastic backpropagation with multi-channel randomized trace estimation. June 2021.
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Ali Siahkoohi and Felix J. Herrmann. Learning by example: fast reliability-aware seismic imaging with normalizing flows. In: SEG Technical Program Expanded Abstracts. Sept. 2021, pp. 1580–1585. doi: 10.1190/segam2021-3581836.1.
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Rajiv Kumar, Maria Kotsi, Ali Siahkoohi, and Alison Malcolm. Enabling uncertainty quantification for seismic data pre-processing using normalizing flows (NF)—an interpolation example. In: SEG Technical Program Expanded Abstracts. Sept. 2021, pp. 1515–1519. doi: 10.1190/segam2021-3583705.1.
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Felix J. Herrmann, Mathias Louboutin, and Ali Siahkoohi. ML@scale using randomized linear algebra. Talk at Microsoft. Mar. 2021.
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Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, Philipp A. Witte, and Felix J. Herrmann. Deep Bayesian Inference for Task-based Seismic Imaging. Talk at KAUST. Mar. 2021.
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Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, Philipp A. Witte, and Felix J. Herrmann. Preconditioned training of normalizing flows for variational inference in inverse problems. In: 3rd Symposium on Advances in Approximate Bayesian Inference. Jan. 2021.
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Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, and Felix J. Herrmann. Unsupervised data-guided uncertainty analysis in imaging and horizon tracking. In: 3rd Annual Meeting of the SIAM Texas-Louisiana Section. Oct. 2020.
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Ali Siahkoohi, Philipp A. Witte, Mathias Louboutin, Felix J. Herrmann, and Gabrio Rizzuti. Seismic Imaging with Uncertainty Quantification: Sampling from the Posterior with Generative Networks. In: SIAM Conference on Imaging Science. IS20. July 2020.
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Ali Siahkoohi, Gabrio Rizzuti, Philipp A. Witte, and Felix J. Herrmann Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows. In: Tech. rep. TR-CSE-2020-2, Georgia Institute of Technology. July 2020.
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Gabrio Rizzuti, Ali Siahkoohi, Philipp A. Witte, and Felix J. Herrmann. Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization. In: SEG Technical Program Expanded Abstracts. Sept. 2020, pp. 1541–1545. doi: 10.1190/segam2020-3428150.1
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Mi Zhang, Ali Siahkoohi, and Felix J. Herrmann. Transfer learning in large-scale ocean bottom seismic wavefield reconstruction. In: SEG Technical Program Expanded Abstracts. Sept. 2020, pp. 1666–1670. doi:10.1190/segam2020-3427882.1.
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Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann. Weak deep priors for seismic imaging. In: SEG Technical Program Expanded Abstracts. Sept. 2020, pp. 2998–3002. doi: 10.1190/segam2020-3417568.1.
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Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann. Uncertainty quantification in imaging and automatic horizon tracking—a Bayesian deep-prior based approach. In: SEG Technical Program Expanded Abstracts. Sept. 2020, pp. 1636–1640. doi: 10.1190/segam2020-3417560.1.
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Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann. A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification. In: 82nd EAGE Conference and Exhibition 2020. Jan. 2020.
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Felix J. Herrmann, Ali Siahkoohi, and Gabrio Rizzuti. Learned imaging with constraints and uncertainty quantification. In: NeurIPS 2019 Deep Inverse Workshop. Dec. 2019.
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Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann. Neural network augmented wave-equation simulation. In: Tech. rep. TR-CSE-2019-1, Georgia Institute of Technology. Sep. 2019.
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Ali Siahkoohi, Rajiv Kumar, and Felix J. Herrmann. Deep-learning based ocean bottom seismic wavefield recovery. In: SEG Technical Program Expanded Abstracts. Aug. 2019, pp. 2232–2237. doi: 10.1190/segam2019-3216632.1.
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Ali Siahkoohi, Dirk J. Verschuur, and Felix J. Herrmann. Surface-related multiple elimination with deep learning. In: SEG Technical Program Expanded Abstracts. Aug. 2019, pp. 4629–4634. doi: 10.1190/segam2019-3216723.1.
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Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann. The importance of transfer learning in seismic modeling and imaging. In: Geophysics 84.6. July 2019, pp. A47–A52. doi: 10.1190/geo2019-0056.1.
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Gabrio Rizzuti, Ali Siahkoohi, and Felix J. Herrmann. Learned iterative solvers for the Helmholtz equation. In: 81st EAGE Conference and Exhibition 2019. June 2019. doi: 10.3997/2214-4609.201901542.
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Felix J. Herrmann, Ali Siahkoohi, and Mathias Louboutin. Machine Learning in Seismic Imaging—from Low-fidelity to High-fidelity. In: SIAM Conference on Computational Science and Engineering. (SIAM CSE). Mar. 2019.
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Ali Siahkoohi, Mathias Louboutin, Rajiv Kumar, and Felix J. Herrmann. Deep-convolutional neural networks in prestack seismic—two exploratory examples. In: SEG Technical Program Expanded Abstracts. Oct. 2018, pp. 2196–2200. doi: 10.1190/segam2018-2998599.1.
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Felix J. Herrmann, Gerard J. Gorman, Jan Hückelheim, Keegan Lensink, Paul Kelly, Navjot Kukreja, Henryk Modzelewski, Michael Lange, Mathias Louboutin, Fabio Luporini, Ali Siahkoohi, and Philipp A. Witte. The power of abstraction in Computational Exploration Seismology. In: Smoky Mountains Computational Sciences and Engineering Conference. Aug. 2018.
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Ali Siahkoohi, Rajiv Kumar, and Felix J. Herrmann. Seismic Data Reconstruction with Generative Adversarial Networks. In: 80th EAGE Conference and Exhibition 2018. June 2018. doi: 10.3997/2214-4609.201801393.
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Ali Siahkoohi and Ali Gholami. Sparsity Promoting Least Squares Migration for Laterally Inhomogeneous Media. In: 7th EAGE Saint Petersburg International Conference and Exhibition. Apr. 2016. doi: 10.3997/2214-4609.201600223.
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Mohmmad Sadegh Ebrahimi, Mohammad Hossein Daraei, Jamshid Rezaei, and Ali Siahkoohi. A Novel Utilization of Wireless Sensor Networks as Data Acquisition System in Smart Grids. In: Materials Science and Information Technology. Vol. 433. Advanced Materials Research. Trans Tech Publications, Jan. 2012, pp. 6725–6730. doi: 10.4028/www.scientific.net/AMR.433-440.6725.
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Amir Najafi, Ali Siahkoohi, and Mohammad B Shamsollahi. A content-based digital image watermarking algorithm robust against JPEG compression. In: 2011 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). IEEE. Feb. 2011, pp. 432–437. doi: 10.1109/ISSPIT.2011.6151601.
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