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Kenneth Brown

@kennethbrown1

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I am a mechanical engineer specializing in fluid dynamics, data science, and wind-energy optimization.

United States

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What I'm looking for

I'm seeking a senior engineering role applying fluid dynamics, data science, and ML to wind-energy or aero-propulsion problems, leading multidisciplinary teams on industry-collaborative projects with research translation and mentorship opportunities.

I am a mechanical engineer with a Ph.D. and more than a decade of experience in applied mechanics, turbulence research, and wind-energy systems. My work spans modeling, measurement, and data-driven analysis for complex fluid problems.

I have led multidisciplinary, federally funded projects totaling over $1M, collaborated with industry partners such as GE Vernova to demonstrate control strategies that increased predicted annual energy output, and developed parallelized data pipelines with uncertainty quantification. I am a Senior Member of the Technical Staff with 13 first-author publications, 450 citations, and a patent currently in review.

I specialize in fluid modeling and measurement, machine learning, verification/validation, and experimental design, working with Python, MATLAB, and modern ML toolkits. I mentor researchers and seek opportunities to translate rigorous, data-driven research into industry impact through collaboration and technical leadership.

Experience

Work history, roles, and key accomplishments

Current

Senior Member of the Technical Staff

Current

Sandia National Laboratories

Jan 2021 - Present (4 years 7 months)

Led multidisciplinary federally funded projects totaling >$1M on modeling and optimization of wind-turbine systems using physics-informed off-policy RL and POD/SVD, and collaborated with GE Vernova to demonstrate control strategies yielding several percentage points higher annual energy in CFD. Developed parallel Python/MATLAB data pipelines and implemented uncertainty quantification for large, co

Fluid Dynamics Reinforcement Learning POD SVD CFDs Python Matlab Uncertainty Quantification Data Pipelines Optimization

Postdoctoral Appointee

Sandia National Laboratories

Jan 2019 - Jan 2021 (2 years)

Designed a supervised ML pipeline to process large Doppler lidar datasets with contaminated features, increasing data availability by 4% and achieving >10x speed-up versus conventional methods while adding novel uncertainty quantification. Applied PCA and spectral analysis to LES data, revealing a 20% shortfall in a quantity of interest due to measurement effects that informed model validation.

Doppler Lidar Processing Spectral Analysis Uncertainty Quantification Python Matlab Data Processing

Research Engineer

Techsburg, Inc.

Jan 2016 - Jan 2019 (3 years)

Designed experiments and end-to-end processing for aero-propulsion projects for U.S. Army and NASA, building data reduction routines and ANOVA analyses across full-factorial wind tunnel tests that supported a client's downselect decision. Presented results to international gas-turbine stakeholders and supported test planning and statistical significance assessments.

Experimental Design Aero Propulsion Testing Wind Tunnel Testing ANOVA Matlab Statistical Analysis Test Reporting

Education

Degrees, certifications, and relevant coursework

Virginia Tech

Doctor of Philosophy, Mechanical Engineering

Activities and societies: Guest researcher at JAXA; dissertation: "Exploiting Wind Tunnels with Porous Flexible Walls."

Doctor of Philosophy in Mechanical Engineering with a dissertation titled "Exploiting Wind Tunnels with Porous Flexible Walls." Served as a guest researcher at the Japan Aerospace Exploration Agency (JAXA) focusing on applied mechanics and turbulence research.