I am a final year Ph.D. student in computational geophysics, King Abdullah University of Science and Technology, advised by Prof. Tariq Alkhalifah. I received my Master’s degree from Tongji University, advised by Prof. Yuzhu Liu, and Bachelor’s degree from Jilin university. I also worked as a research intern at Microsoft Research AI4Science and Microsoft Research Asia.
My research interests span the areas of physics-informed machine learning, operator learning, seismic modeling, fluid dynamics, weather modeling, full waveform inversion, deep generative models, and efficient and scalable learning algorithms.
🔥 News
- 2023.05: 🎉🎉 Receive the KAUST PSE Dean’s award!
- 2023.04: 🎉🎉 NeuralStagger is accepted at ICML 2023!
📝 Publications
Xinquan Huang, Wenlei Shi, Qi Meng, Yue Wang, Xiaotian Gao, Jia Zhang, Tie-Yan Liu
- A novel, simple, and general spatiotemporal decomposition strategy that speeds up the solution of partial differential equations using neural networks.
PINNup: Robust neural network wavefield solutions using frequency upscaling and neuron splitting
Xinquan Huang, Tariq Alkhalifah
- A novel physics-informed neural network framework using frequency upscaling and neuron splitting, yielding efficient, highly accurate, high-frequency wavefield solutions.
Xinquan Huang, Tariq Alkhalifah
- A Single reference frequency loss function for multifrequency wavefield, which mitigate the change in the spatial wavenumber over frequency by adapting the spatial scale to frequency.
Selected Publications ($\dagger$: Corresponding Author)
JCP
Xinquan Huang and Tariq Alkhalifah, (2024), Efficient physics-informed neural networks using hash encoding, Journal of Computational Physics, 501: 112760, 10.1016/j.jcp.2024.112760.Neural Networks
Xinquan Huang, Wenlei Shi, Xiaotian Gao, Xinran Wei, Jia Zhang, Jiang Bian, Mao Yang, Tie-Yan Liu, (2024), LordNet: an efficient neural network for learning to solve parametric partial differential equations without simulated data, in revision.IEEE TGRS
Xinquan Huang and Tariq Alkhalifah, (2024), Microseismic source imaging using physics-informed neural networks with hard constraints, vol. 62, pp. 1-11, Art no. 4503011.GP
Xinquan Huang and Yuzhu Liu, (2024), An efficient elastic full-waveform inversion of multiple parameters with ocean-bottom seismometer data, Geophysical Prospecting, in press.Neural Networks
Tariq Alkhalifah and Xinquan Huang, 2024, Physics-informed neural wavefields with Gabor basis functions, in press.- Fu Wang, Xinquan Huang, Tariq Alkhalifah, 2024, Controllable seismic velocity synthesis using generative diffusion models, in revision.
ICML 2023
Xinquan Huang, Wenlei Shi, Qi Meng, Yue Wang, Xiaotian Gao, Jia Zhang, Tie-Yan Liu, (2023), NeuralStagger: Accelerating physics constrained neural PDE solver with spatial-temporal decomposition, International Conference on Machine Learning (ICML), 13993-14006.IEEE GRSL
Xinquan Huang and Tariq Alkhalifah, (2023), GaborPINN: Efficient physics informed neural networks using multiplicative filtered networks, IEEE Geoscience and remote sensing letter, vol. 20, pp. 1-5, Art no. 3003405.IEEE TGRS
Fu Wang, Xinquan Huang$\dagger$, Tariq Alkhalifah, 2023, A prior regularized full waveform inversion using generative diffusion models, IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-11, Art no. 4509011.JGR: Solid Earth
Xinquan Huang and Tariq Alkhalifah, (2022), PINNup: Robust neural network wavefield solutions using frequency upscaling and neuron splitting, Journal of Geophysical Research: Solid Earth, 127.IEEE GRSL
Xinquan Huang and Tariq Alkhalifah, (2022), Single reference frequency loss for multi-frequency wavefield representation using physics-informed neural networks, IEEE Geoscience and remote sensing letter, vol. 19, pp. 1-5, Art no. 3007105.Geophysics
Yuzhu Liu, Xinquan Huang$\dagger$, Jizhong Yang, Xueyi Liu, Bin Li, Liangguo Dong, Jianhua Geng, Jiubing Cheng, (2021), Multi-parameter model building in the Qiuyue structure with four-component OBS data, Geophysics, 86(5): B291-B301.Patent
Xinquan Huang and Yuzhu Liu, (2020), A source-receiver reciprocal elastic full-waveform inversion for multicomponent OBS data, Patent, patent number: ZL202010499751.8.CJG
Yuzhu Liu, Xinquan Huang, Xianwu Wan, Minao Sun, Liangguo Dong, (2019), Elastic multi-parameter full-waveform inversion for anisotropic media, Chinese Journal of Geophysics(in Chinese), 62(5): 1809-1823.GPP
Yuzhu Liu, Shilin Wu, Weigang Liu, Xinquan Huang, Zheng Wu, (2020), A review of seismic tomographic methods for the inversion of near-surface models, Geophysical Prospecting for Petroleum, 59(1): 1-11.
Conference Papers
EAGE 2023
Xinquan Huang and Tariq Alkhalifah, (2023), Microseismic source imaging using physics-informed neural networks with hard constraints: a field application, 84th EAGE Annual Conference and Exhibition, Volume 2023, p.1-5.EAGE 2023
Xinquan Huang and Tariq Alkhalifah, (2023), GaborPINN: Efficient physics informed neural networks using multiplicative filtered networks, 84th EAGE Annual Conference and Exhibition, Volume 2023, p.1-5.EAGE 2023
Fu Wang, Xinquan Huang, Tariq Alkhalifah, (2023), Prior probability regularized FWI using generative diffusion models, 84th EAGE Annual Conference and Exhibition, Volume 2023, p.1-5.SEG 2022
Xinquan Huang and Tariq Alkhalifah, (2022), Source location using physics-informed neural networks with hard constraints, SEG Technical Program Expanded Abstracts: 1770-1774.EAGE 2022
Xinquan Huang, Tariq Alkhalifah, and Fu Wang, (2022), High-dimensional wavefield solutions using physics-informed neural networks with frequency-extension, 83rd EAGE Annual Conference and Exhibition, Volume 2022, p.1-5.ICIP 2022
Tariq Alkhalifah and Xinquan Huang, (2022), Direct imaging using physics-informed neural networks IEEE International Conference on Image Processing, pp. 2781-2785.NeurIPS 2021 workshop
Xinquan Huang and Tariq Alkhalifah, (2021), Single Reference Frequency Loss for Multi-frequency Wavefield Representation using Physics-Informed Neural Networks, NeurIPS 2021 Workshop AI4Science.SEG 2021
Xinquan Huang, Tariq Alkhalifah, Chao Song, (2021), A modified physics-informed neural network with positional encoding, SEG Technical Program Expanded Abstracts: 2480-2484.SEG 2021
Tariq Alkhalifah, Chao Song, and Xinquan Huang, (2021), High-dimensional wavefield solutions based on neural network functions, SEG Technical Program Expanded Abstracts: 2440-2444.SEG 2020
Fu Wang, Huazhong Wang, and Xinquan Huang$\dagger$, (2020), Rotation invariant CNN using scattering transform for seismic facies classification, SEG Technical Program Expanded Abstracts: 1646-1650.SEG 2019
Xinquan Huang, Yuzhu Liu,and Fu Wang, (2019), A robust full waveform inversion using dictionary learning, SEG Technical Program Expanded Abstracts:1506-1510.SEG 2019
Yuzhu Liu and Xinquan Huang $\dagger$, (2019), Full waveform inversion of an OBS dataset acquired from Q field in East China Sea, SEG Technical Program Expanded Abstracts : 1655-1659.
💻 Internships
- 2022.08 - 2023.03, research intern at Microsoft Research AI4Science, Beijing.
- 2022.05 - 2022.08, research intern at Microsoft Research, machine learning Group, Beijing.
📖 Educations
- 2020.08 - present, King Abdullah University of Science and Technology.
- 2017.09 - 2020.04, Tongji University.
- 2013.09 - 2017.06, Jilin University.
🎖 Honors and Awards
- 2023.05 KAUST PSE Dean’s award
- 2021.06 KAUST virtual workshop Lightning talk contest Honorable Mention
- 2020.04 Outstanding graduate student, Tongji University
- 2019.12 Guanghua Scholarship, Tongji University
- 2019.12 Geophysical Scholarship of Tongji University
- 2019.12 Outstanding student paper Annual Meeting of Chinese Geoscience Union (CGU)
- 2019.09 Third prize China Petroleum Society 2019 geophysical exploration technology symposium
- 2018.12 Third prize (Leader) ”HUAWEI Cup” The 15th Post-Graduate Mathematical Contest In Modeling
- 2018.12 Geophysical Scholarship of Tongji University
- 2017.04 National Excellent Project Jilin University ”Undergraduate Innovation and Entrepreneurship Training Program”: Innovation Training
- 2016.08 The Sanhe Aroundwave Software CO. Scholarship, Jilin University First Place Practical Skills Competition of Geophysics, Jilin University
🏫 Teaching
KAUST
- 2023.01 – 2023.05, Teaching Assistant, Advanced Full waveform inversion
- 2021.08 – 2021.12, Teaching Assistant, Seismic Imaging
💬 Invited Talks
- 2023.10, Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition, Purdue University
- 2021.06, Physics-informed neural network for high-frequency wavefield representation, KAUST Virtual Workshop Intelligent illumination of the Earth