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MS

McKetta Department of Chemical Engineering, The University of Texas at Austin

Chemical Engineering

PhD

McKetta Department of Chemical Engineering, The University of Texas at Austin

Chemical Engineering

BS

Department of Chemical Engineering, Brigham Young University

Chemical Engineering

Updating Data-Driven Models

Ph.D. Research (Jan. 2024 -- Present). Advisors: Michael Baldea, Brian A. Korgel.

• Developed the Subset Extended Kalman Filter for online updates of neural network parameters to accommodate systemic drift or discrete changes in the modeled system. Reduces update time 2-3× compared to retraining all parameters.
• Trained and maintained neural network models of parametrically drifting dynamical systems including a damped spring, CSTR, diabetic glucose-insulin, temperature control arduino, and fluidized catalytic cracking and fractionator system.
• Sim2Real transfer learning of neural network models from simulated to physical systems.
• Model hyperparameter optimization using Asynchronous Hyperband Search on Texas Advanced Computing Center's Lonestar 6 supercomputer. PyTorch implementation on GitHub: https://github.com/joshuaeh/Hyperband-PyTorch.

Solar Irradiance Forecasting with Deep Learning

Ph.D. Research (Oct. 2021 -- Present). Advisors: Michael Baldea, Brian A. Korgel.

• Developed a spatio-temporal deep learning model that forecasts solar irradiance up to two hours ahead using images of the sky and local meteorological measurements.
• Reduced input data requirements by 12× while improving forecast accuracy using Conv-LSTM architecture to forecast future sky images, polar transformations to correlate satellite and ground-based images, and multiple-camera inputs.
• Combined process systems engineering and machine learning by adding a novel-to-irradiance forecasting disturbance model to the forecasting model which decreased error when performing feature selection.

Computationally-aided Photovoltaic Design

Ph.D. Research (Sep. 2025 -- Present). Advisors: Michael Baldea, Brian A. Korgel.

• Used computational simulations to optimize the shape and size of groves in novel perovskite photovoltaic cells.

Renewable Power Integration in Energy Systems

Ph.D. Research (Oct. 2021 -- Present). Advisors: Michael Baldea, Brian A. Korgel.

• Developed a model-based net load forecasting framework that combines local building models in EnergyPlus, probabilistic weather forecasts from NOAA, and historical load data to forecast substation-level net load.
• Optimized residential battery charge/discharge schedules to minimize electricity costs and demand charges using Pyomo and IPOPT.
• Evaluated the effects of electric tariff policies on optimal battery sizing and operation.

UAV Path Planning for Structural Monitoring

Undergraduate Research (Aug. 2018 -- Aug. 2021). Advisor: John Hedengren.

• Flew UAVs to collect aerial imagery to evaluate and validate path-planning algorithms for 3D reconstruction of terrain and structures.
• Helped develop novel autonomous flight-path planning algorithm that identifies where to photograph next based on current 3D model quality.

Staying Alive: Online Neural Network Maintenance and Systemic Drift

Scientific Reports

Online neural network maintenance and systemic drift. Submitted to Scientific Reports June 2025.

Short-term solar irradiance forecasting under data transmission constraints

Renewable Energy

STELLAR: Spatio-Temporal Deep Learning for Solar Irradiance Forecasting

Shell Global Solutions International B.V.

Internal technical report.

Automated 3D reconstruction using optimized view-planning algorithms for iterative development of structure-from-motion models

Remote Sensing

Survey of 8 UAV set-covering algorithms for terrain photogrammetry

Remote Sensing

Sequential earthquake damage assessment incorporating optimized suav remote sensing at pescara del tronto

Geosciences (Switzerland)

Renewable Power Integration Engineer

Shell International Exploration & Production, Inc.

Peer Reviewer

Industrial & Engineering Chemistry Research

Reviewed 3 articles for Industrial & Engineering Chemistry Research.

Peer Reviewer

Journal of Open Source Software

Reviewed 4 articles for Journal of Open Source Software.

Student Representative -- Faculty Search

The University of Texas at Austin

Asked departmental questions and provided student feedback on faculty candidates.

Peer Mentor

The University of Texas at Austin

Mentored 1 incoming Ph.D. student each academic year (3 total).

Graduate Recruitment Committee Member

The University of Texas at Austin

Helped plan, organize, and run virtual and in-person recruitment events in Spring 2022 and Spring 2023. Served as a peer mentor to two accepted students each year.

Graduate Teaching Assistant

The University of Texas at Austin

Assisted in teaching undergraduate courses in chemical engineering, including leading discussion sections, grading assignments, and providing support to students.

Thomas Edgar Chemical Engineering Graduate Fellowship

The University of Texas at Austin

Awarded to support PhD students in chemical engineering who demonstrate excellence in research and academic performance.