Research Interests
I focus on machine learning and data science applications for subsurface modeling and simulation, including: uncertainty quantification, inverse modeling, data assimilation, control & optimization, reduced-order modeling, and physics-informed predictive analytics.
Education
University of Texas at Austin
[2021] - [2025]Ph.D. Petroleum and Geosystems Engineering
Advisors: Dr. Michael Pyrcz & Dr. Carlos Torres-Verdin"Latent space methods for subsurface resource modeling"University of Tulsa
[2019] - [2020]M.S. Mathematics
Advisor: Dr. Shirley Pomeranz"Boundary Element Method for the Dirichlet Problem for Laplace's Equation on a Disk"[2015] - [2019]B.S. Petroleum Engineering
B.S. Applied Mathematics
minors: Computational Science, High Performance Computing
"Predictive Analytics and Artificial Lift Solutions for Liquid Loading wells using Statistical Learning and Physical Modeling"Experience
Intern - Modeling, Optimization and Data Science (MODS)
[05/2024] - [08/2024]ExxonMobil-EMTECIntern - Computational Earth Science (EES-16)
[05/2023] - [08/2023]Los Alamos National LaboratoryResearch Assistant - DiReCT & FE
[2021] - [Present]Digital Reservoir Characterization Technology, UTFormation Evaluation Consortium, UTResearch Assistant - SEES
[2020] - [2021]Subsurface Energy and Environmental Systems, USCTeaching Assistant
[2021] - [2022] & [2018] - [2019]Subsurface Machine Learning, Department of Petroleum Engineering, UTCalculus I, Department of Mathematics, TURock & Fluid Properties, McDougall School of Petroleum Engineering, TUAwards
University Graduate Continuing Fellowship (UT, 2024)
UT-Chevron Energy Fellowship (UT, 2023) - link
University of Texas at Austin Graduate School Fellowship (UT, 2021)
Viterbi School of Engineering/Graduate School Fellowship (USC, 2020)
Ralph W. Veatch Award in Mathematics (Tulsa, 2019)
Thomas C. Frick Award in Petroleum Engineering (Tulsa, 2019)
AADE MidCon Scholarship (Tulsa, 2018)
International Scholarship for Academic Excellence and Outstanding Leadership (Tulsa, 2015)
Skills
Programming:
Python, MATLAB, R, Mathematica
C/C++, Julia, VBA, SQL, UNIX
Software:
MRST, CMG, Petrel, Eclipse
SGeMS, Aries, Harmony, PipeSim, ParaView
Jupyter, R\Shiny, Tableau, Spotfire, @Risk
Relevant Coursework
Petroleum Engineering
Data Science for Engineering Systems, Subsurface Optimization, Numerical Reservoir Simulation, Flow Fluid and Transport Processes, Advanced Petrophysics, Subsurface Machine Learning, Multi-Well Formation Evaluation, Subsurface Energy Storage.
Rock & Fluid Properties, Integrated Reservoir Modeling, Unconventional Resources, Formation Evaluation, Reservoir Eng I & II, Production Eng I & II, Drilling Eng I & II, Well Completions; Seismic Data Processing, Structural Geology.
Applied Mathematics / Computer Science
Machine Learning, Data Science, High-Performance Computing; Numerical Methods for IBVP, Partial Differential Equations, Adv. Differential Equations, Dynamical Systems, Linear Algebra, Stochastic Modeling & Simulation, Statistical Learning, Numerical Optimization, Engineering Analysis.