I teach and lead research in Subsurface Data Analytics, Geostatistics, and Machine Learning.
My team is the Texas Center for Data Analytics and Geostatistics
Our Research Scope, Goals, and Philosophy
I lead 12 Ph.D. students with the following scope, goals, and philosophy directing our research work. We are working hard to enable the digital transformation in spatial, subsurface modeling. We feel a weight of responsibility to serve society, promote diversity, productive and a positive working environment.
We are developing new spatial data analytics methods and workflows for feature engineering, integrating geoscience information and engineering physics, anomaly detection, spatial significance, etc. New ways to add value with data!
We are making data analytics and machine learning possible for spatial, subsurface settings. Our new methods integrate the spatial context including location, spatial correlation, representativity, scale, and uncertainty. Current methods are not generally ready off the shelf!
We are building spatial, subsurface heterogeneity, and uncertainty models with cutting-edge deep learning methods. These new models will be a step-change in our ability to model and explore the subsurface and other spatial settings. Faster, more realistic uncertainty models to explore the complicated subsurface!
We are building fast, deep learning-based surrogate models for the physics-based transfer functions commonly applied to the subsurface, including fluid flow through porous media. These models span all scales and enable real-time feedback for subsurface modeling and development decision making.
We remain true to the fundamental principles of probability and geostatistics with a focus on prior model development, bias mitigation, data-driven characterization, updating with new information, stationarity decisions, spatial prediction with uncertainty, and integration of diverse data/information sources.
Society is facing a digital revolution. We serve society by supporting and assisting organizations and individuals in learning new digital skills, including academia, students, along with industry, working professionals.
We collaborate widely with other research groups to enhance our mutual productivity and student experience. We resist the common silo'ed, competitive tendency by adopting a "win together" attitude.
We seek to build a positive, respectful, diverse professional environment to maximize education and productivity. All are free to express their constructive ideas and to find innovative solutions. Diverse opinions, transparent communication, helpful scientific reviews and debates, are welcome by all. We follow the scientific method and teach and practice the best leadership skills taught in the industry.
The subsurface is a difficult setting; therefore, we must collaborate and integrate the established best practice and new cutting-edge technologies.