Joel Sotelo Flores

Honors Thesis:PyRo-FOAMS: An open-source workflow for automated vesicle segmentation and stereological analysis.

Study Abroad:Big Science in 21st Century Europe, including CERN and VIRGO Gravitational Wave Detector; Korean language study at Yonsei University.

• Developing a computer vision pipeline to segment Kīlauea lava fountain video and support quantitative extraction of eruption parameters from field footage.
• Trained U-Net segmentation models to identify lava-fountain regions across changing lighting, viewing geometry, and field conditions.
• Built a Python-based labeling and dataset-preparation system for selecting frames, generating masks, tracking video metadata, and organizing model-ready training data.
• Collected field footage for Kīlauea Episodes 49 and 50 and documented camera settings, viewing conditions, and observational notes.

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• Conduct computational volcanology research on pyroclastic micro-CT volumes to quantify vesicularity, pore connectivity, permeability, and eruption-related textural characteristics of the 1817 Kawah Ijen eruption to reconstruct eruptive history.
• Train and evaluate U-Net-based deep learning models for 3D pore-space segmentation of volcanic clasts, enabling quantitative analysis of connected pore networks.
• Built PyRO-FOAMS, a Python-based stereometric analysis program inspired by Shea et al. (2010), to support automated vesicle analysis from 2D thin-section imagery through classical and machine learning computation.
• Used Dragonfly and OpenPNM to quantify porosity, permeability, pore connectivity, and anisotropy from segmented pyroclast volumes.
• Integrated electron microprobe and scanning electron microscope data to connect textural observations with mineral chemistry, fractionation trends, and pressure-temperature constraints.

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• Conducted multi-band observational analysis of the RR Lyrae variable star V0499 Centauri.
• Analyzed robotic telescope data from the Las Cumbres Observatory global telescope network to construct folded light curves and measure pulsation behavior.
• Contributed to period determination using multiple algorithms, including phase dispersion minimization, string length minimization, harmonic analysis of variance, and Lomb-Scargle periodograms.
• Supported photometric distance analysis using period-luminosity-metallicity relations, extinction corrections, and comparison with Gaia DR3 parallax measurements.

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• Conducted astrometric analysis of the binary star system WDS 03575-0110 using robotic telescope observations from Las Cumbres Observatory.
• Used AstroImageJ to measure separation and position angle from observational image data.
• Compared new measurements with historical observations and Gaia DR3 data to evaluate common proper motion and refine orbital parameter estimates through novel techniques.

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• Assisted with laboratory research on electric-field-driven self-assembly of nanoparticles and magnetic dipole systems.
• Investigated how dipoles interact, align, and form larger-scale structures under applied electric fields.
• Designed experimental apparatuses to observe, measure, and record magnetic dipole interactions.

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• Developed an algorithm in R to identify Riesel-Sierpiński numbers within recursive sequences.
• Applied computational methods to explore problems in number theory and mathematical pattern recognition.

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