Welcome to my webpage!

ABOUT ME

I am currently Associate Professor of Geophysics in the Department of Earth & Atmospheric Sciences at University of Houston.  I obtained my PhD in geophysics in 2015 from Colorado School of Mines, and BS in geophysics in 2008 from China University of Geosciences in Wuhan, China.

My research interests revolve around the theme of better imaging, characterization and monitoring of subsurface systems. My research is highly interdisciplinary because I constantly cross disciplinary boundaries and utilize methods and tools developed in convex optimization, computer vision, pattern recognition, remote sensing, medical imaging and machine learning. My research is also computationally intensive because I rely on heavy computational resources such as GPUs and clusters to carry out my research. My current research focuses on: 

• Developing advanced methods for critical minerals and rare earth element (REE) deposit exploration using airborne geophysics and joint inversion;

• Solving geophysical inverse problems and assessing uncertainty using deep generative models;

• Developing joint inversion algorithms for integrated imaging of the Earth based on multi-physical geoscience data sets;

• Building 3D quasi-geology model through integrative modeling of multi-physical geoscience data;

• Quantifying uncertainties of geophysical inversions in both deterministic and Bayesian inversion frameworks; 

• Tackling magnetic remanence problem by integrating geophysics and machine learning; and

• Developing advanced numerical algorithms for geologically constrained inversion of various geophysical data.

NEWS

• 03/24/2024 --- Our manuscript 'Reconstruction of multiple target bodies using trans-dimensional Bayesian inversion with different constraints' was accepted for publication in IEEE Transactions on Geoscience and Remote Sensing. In this manuscript, we exended our previous work on quantifying uncertainty of anomalous body shapes from one anomalous body to multiple bodies.  

• 03/18/2024 --- Drs. Sihong Wu, Jiefu Chen, Xuqing Wu and myself visited Amazon's Generative AI Innovation Center (GenAIIC) in Houston and presented our work on the application of generative AI to some geoscience problems. We had great discussions with data scientists Dr. Yingwei Yu and Dr. Yanxiang Yu at Amazon.

• 01/19/2024 --- Our manuscript '3D Monte Carlo geometry inversion using gravity data' was accepted for publication in GEOPHYSICS! We extended our previous work in 2D (https://doi.org/10.1093/gji/ggac430) now to 3D, and we show that, with sparse geometry parameterization, 3D Bayesian inversion is doable. In this work, we also discussed an interesting and effective strategy, based on alpha shape, of incorporating structural constraint into the sampling process.  Check it out at https://doi.org/10.1190/geo2023-0498.1.

• 01/15/2024 --- Prithwijit Chakraborti, a PhD student working with Dr. Aline Melo at University College Dublin, will visit our group from Jan to Sept. He will be working with Jiajia on 2D/3D Earth model building using potential field and drillhole measurements. Welcome, Prithwijit!

• 12/11/2023 --- Jay Ghosh, Sihong Wu and Jiajia attended AGU Fall Meeting in San Francisco. Jay had two poster presentations on the use of machine learning to advance the interpretation of marine magnetic anomalies. It was great to meet so many new and old friends and see some of the most exciting ideas and technical developments in the Earth science. 

• 09/01/2023 --- We are excited to welcome Dr. Sihong Wu to join our group as a post-doc! Dr. Wu specializes in deep learning and electromagnetic data processing, inversion and uncertainty quantification. She obtained her BS from University of Science and Technology of China (USTC), her PhD from Peking University, followed by a post-doc at Peking University in Prof. Qinghua Huang's group. 

• 08/28/2023 --- Jiajia attended IMAGE '23, the joint annual meeting of AAPG and SEG. He gave an invited talk titled 'Mapping critical mineral resources using multiphysics inversion' in one of Special Sessions 'Recent Advance and Road Ahead'.  Xiaolong presented "3D trans-dimensional Monte Carlo geometry inversion and uncertainty quantification using gravity data". Yanyan Hu presented her work on deep learning enhanced joint inversion for mineral exploration using airborne geophysics. 

• 07/28/2023 --- Jiajia is attending a workshop 'Open-Source Tools to Enable Geophysical Data Processing and Inversion' in the gorgeous Banff National Park in Canada. This workshop brings together users and developers of SimPEG ((http://www.simpeg.xyz) and Fatiando a Terra (http://www.fatiando.org) to share the latest advances in their research and software packages, and also discuss the future developments of these two open source projects and communities. More can be found here https://www.birs.ca/events/2023/2-day-workshops/23w2014.

• 07/12/2023 -- - Jiajia attended the 28th IUGG General Assembly held in Berlin, 11 - 20 July 2023, giving an invited oral presentation titled 'Building probabilistic quasi-geology models and mapping mineral resources using joint inversion and geology differentiation', co-authored by Xiaolong Wei. Jiajia also gave another oral presentation titled 'Uncertainty quantification of anomalous body shapes using potential field data in a trans-dimensional Bayesian framework' co-authored by Xiaolong Wei and Mrinal Sen. 

• 06/01/2023 --- Jiajia was promoted to the rank of associate professor and granted tenure, effective September 1st, 2023.

• 03/24/2023 --- Keenan Barker passed his thesis defense with flying colors! Congratulations, Keenan! In his thesis, Keenan developed new deep learning based methods for improving the interpretation of magnetic tensor data. The results are very promising, and can potentially lead to a step change in how tensor data is typically interpreted by human experts.

• 12/05/2022 ---- Xiaolong won the Fall 2022 Dan E. Wells Outstanding Dissertation Award! The award recognizes a graduating doctoral student from the College of Natural Sciences and Mathematics who has performed outstanding research and submitted the best dissertation to the College in terms of scholarship, presentation and organization. The recipient receives an award of $1,000 and is recognized at the Commencement ceremony. Congratulations, Xiaolong!

• 10/26/2022 ---- Our manuscript 'Quantifying uncertainty of salt body shapes recovered from gravity data using trans-dimensional Markov chain Monte Carlo sampling' was accepted for publication in GJI. In this paper, we proposed a sparse geometry parameterization strategy to greatly reduce the number of parameters to be sampled. We investigated how different prior constraints affect the uncertainty of the salt body recovery. The sparse geometry parameterization + the concave hull computation is very powerful.  Check it out at https://doi.org/10.1093/gji/ggac430.

• 09/30/2022 ---- Our manuscript 'Mapping critical mineral resources using airborne geophysics, 3D joint inversion and geology differentiation: A case study of a buried niobium deposit in the Elk Creek carbonatite, Nebraska, USA' was accepted for publication in the special issue Mineral Exploration and Mining Geophysics in Geophysical Prospecting.

• 09/16/2022 ---- Xiaolong was offered a post-doc position in Prof. Jef Caers' group at Stanford University! He will move to California after he defends his dissertation in December. Congratulations, Xiaolong! Very well deserved! 

• 06/10/2022 ---- Congratulations to Xiaolong for being awarded the SEG / Lucien LaCoste Scholarship with over $5,300 cash prize! Very well deservied, Xiaolong! The SEG/Lucien LaCoste Scholarship endowment was established in 1997 in memory of Lucien LaCoste. This endowment provides academic merit based scholarships to graduate students whose primary research has a specialization in Potential Fields instrumentation or data analysis.

•  05/04/2022 ---- Xinyan Li received and accepted a post-doctoral offer from the Department of Land, Air and Water Resources at the University of California, Davis. Xinyan will join the department in December after her doctoral dissertation defense. Congratulations, Xinyan!

• 04/07/2022 ----- Xiaolong's paper "3D probabilistic geology differentiation based on airborne geophysics, mixed Lp norm joint inversion and physical property measurements" was accepted for publication in GEOPHYSICS! In this work, we proposed a new workflow for constructing 3D probablistic quasi-geology models. We used a recently developed mixed Lp norm regularization strategy and an open source framework SimPEG. Check out our work at https://library.seg.org/doi/10.1190/geo2021-0833.1.

• 03/22/2022 ------- Xinyan's paper 'Toward a better understanding of the recoverability of physical property relationships from geophysical inversions of multiple potential-field datasets' was accepted for publication in GJI! In this paper, Xinyan compared the recovered physical property relationships from L2 norm separate and joint inversions, and mixed L12 norm separate and joint inversions. Xinyan's work helps us better understand the recoverability in different situations. Check out her work at https://doi.org/10.1093/gji/ggac130.

• Congratulations to Xiaolong for receving the Best Student Presentation Award in the Mining Sessions at the 2021 IMAGE Meeting in Denver, CO! In this work, Xiaolong developed a new approach to constructing a 3D probabilistic quasi-geology model based on airborne geophysical data and borehole measurements. This new approach allows us to quantify the probability of lithological/geological types at each location in a 3D subsurface.  Check out the illustration below. Well done, Xiaolong!

More details can be found at https://library.seg.org/doi/10.1190/segam2021-3586619.1 and https://library.seg.org/doi/10.1190/geo2021-0833.1.

• My colleagues and I are organizing a special issue on machine learning applications in geophysical exploration and monitoring to be published in Geophysical Prospecting. Deadline for submission is 1 March, 2022. More information can be found here. 

• I was selected to receive the J. Clarence Karcher Award by SEG!  The J. Clarence Karcher Award is given in recognition of significant contributions to the science and technology of exploration geophysics by a young geophysicist of outstanding abilities who, in the unanimous opinion of the Honors and Awards Committee and the Board of Directors, merits such recognition.  Thanks to all who helped me, either directly or indirectly, along the way! News release from SEG: https://seg.org/News-Resources/News/page/the-society-of-exploration-geophysicists-announces-2021-honors-and-awards-recipients

• Congratulations to Xiaolong Wei for being awarded the SEG John R. Butler Jr. Scholarship! Well deserved, Xiaolong! Keep up your excellent work!

• Big congratulations to Xiaolong and Felicia on receiving, respectively, the Best Poster and Best Student Presentation in the Mining Sessions at the 2020 SEG Annual Meeting! 

• Our recent work on sparse inversion of potential-field data was published online https://doi.org/10.1111/1365-2478.13063. As before, our data and codes are publicly available on Zenodo http://doi.org/10.5281/zenodo.4057134. We encourage anyone who is interested to have fun with our codes, to reproduce, and more importantly, to improve our results! As we mentioned in the paper, there are still many open questions to be answered. We hope our codes will stimulate more research along this line.

• Our recent publication Predicting magnetization directions using convolutional neural networks was featured on the cover of the October Issue of JGR: Solid Earth!

• Our recent publication Predicting magnetization directions using convolutional neural networks was featured as an Editor's Highlight on EOS. Few than 2% of AGU journal articles are featured this way! All our data and codes used in this publication are published on Zenodo, which already received 213 downloads in about one month!

• Together with my colleagues Ed Bigert, Sarah Devriese and Aline Melo, I organized a post-convention workshop "Artificial Intelligence/Machine Learning for Mineral Exploration" for this year's SEG Annual Meeting.  This workshop aims to bring together researchers and practitioners from academic and industry to (1) showcase the recent successful applications of machine learning/AI to mineral exploration, (2) stimulate discussions among participants and create dialogues between academia and industry, and (3) identify relevant problems and open questions that can be addressed by machine learning/AI. A detailed workshop schedule as well as short abstracts submitted to this workshop can be found at seg.org/AM/2020/event/detail/workshops, or below.