projects

Current Focus

My current professional focus centers on artificial intelligence, human-AI collaboration, and decision support, supported by AI model training and evaluation, prompt engineering, Human-in-the-Loop (HITL) evaluation, structured AI workflows, human validation, information quality, and AI-assisted analysis.

My formal independent research in structured light dynamics culminated in a seven-paper research corpus published through CERN's Zenodo repository in 2025. The analytical methodologies developed during that work continue to inform my approach to source and evidence evaluation, data and information quality, analytical reasoning, and evidence-based decision-making. 

The projects below reflect work across research and decision support, AI model training and evaluation, human-in-the-loop classification and validation, applied generative AI, enterprise technology, astronomical observation, scientific research, data analysis, and creative exploration.

OPENAI Custom GPT Applications 

Developed a collection of domain-specific GPT applications that combine prompt engineering, structured reasoning, and AI-assisted workflows to support research, analysis, education, and creative exploration. Each application demonstrates a different approach to applying large language models to specialized knowledge domains.

• • "Cosmic Quest Adventure": An interactive research simulation that combines deductive reasoning, scientific exploration, and problem-solving through virtual missions inspired by astronomy and astrophysics.

  • "Cosmic Weaver": A visual ideation assistant designed to explore field-based interactions, spatial relationships, and conceptual modeling through AI-assisted creative workflows and original artwork.

  • "Astro Light Explorer": An expert-level astronomy assistant that supports the interpretation of photometric observations, atmospheric optical phenomena, and structured light patterns through AI-assisted analysis and scientific reasoning.

Astronomy Background & Research Participation 

My astronomy work began in 1999 with independent telescopic observation and study and has since expanded to solar observation, scientific image and data classification, and participation in selected institutional and citizen-science research initiatives. This observational foundation preceded my participation in later citizen-science platforms and has informed how I analyze, classify, and validate complex astronomical imagery and scientific datasets.

I have contributed thousands of classifications and observations to projects involving NASA-funded or NASA-supported research, the American Association of Variable Star Observers (AAVSO), European Space Agency (ESA)-affiliated research, universities, and other scientific organizations. These contributions include projects hosted through CosmoQuest, CosmoQuestX Data Mappers, Zooniverse, and other research platforms.

I have performed more than 10 years of pre-generative-AI Human-in-the-Loop (HITL) scientific analysis on NASA-funded and academic research projects: Cosmoquest and CosmoquestX independently identifying, classifying, and validating phenomena missed by automated and machine-learning systems. Applied astronomical knowledge, observational judgment, and pattern recognition to supplement machine analysis, with human findings also used as training data to improve subsequent machine-learning detection and classification.

Collectively, this work supports research in astronomy, heliophysics, planetary science, scientific image and data classification, and scientific dataset development. The specialized astronomical imagery and datasets made available through these projects have also informed my independent research, pattern recognition, human validation, and analytical methodologies.

Participation and Affiliation Disclosure: My astronomical classifications for CosmoQuest and CosmoQuestX contributed to initiatives supported through a NASA cooperative agreement that funded team members at the Astronomical Society of the Pacific, InsightSTEM, Interface Guru, Lawrence Hall of Science, Johnson Space Center, McREL International, the Planetary Science Institute, McDonald Observatory, and Youngstown State University. CosmoQuest is produced by the Planetary Science Institute, a 501(c)(3) nonprofit dedicated to exploring our Solar System and beyond.

All contributions described here have been entirely unpaid and voluntary. I have never been employed by or received compensation from NASA, ESA, AAVSO, the Planetary Science Institute, or any other scientific organization associated with these projects. References to these organizations indicate participation in or contributions to projects they funded, sponsored, administered, supported, or conducted collaboratively—not employment, formal institutional affiliation, or compensation.

Selected Projects & Scientific Contributions

AAVSO Solar Research – Ongoing Field Contributions

As an unpaid volunteer with the AAVSO Solar Section, I contribute regular sunspot counts and solar classification data supporting solar-cycle monitoring, geomagnetic forecasting, and calculation of the American Relative Sunspot Number (Ra). This monthly solar metric serves as a global standard used extensively by international space agencies, NOAA space weather services, academic institutions, private industry, and the broader scientific community.

Recognition: AAVSO Solar Observer Award Recipient

 AAVSO Solar Observation featured by the Boston Museum of Science

Deep Sky Observations: Herschel 400, NGC, Messier & Beyond

Since 1999, conducted systematic, telescopic, observational studies of extragalactic and galactic deep sky objects catalogued in the Herschel 400, NGC, Messier, Abell, Barnard, Harvard, Perek-Kohoutek, Sharpless, Stephenson and Stock catalogues. These include structured observations and morphological documentation of galaxies, open and globular star clusters, emission and reflection nebulae, supernova remnants and dark nebulae.

Scientific Image & Data Classification 

Pre-Generative-AI Human-in-the-Loop Scientific Analysis & Machine Learning

I have performed more than 10 years of pre-generative-AI Human-in-the-Loop (HITL) scientific analysis on NASA-funded and academic research projects, independently identifying, classifying, and validating phenomena missed by automated and machine-learning systems. Applied astronomical knowledge, observational judgment, and pattern recognition to supplement machine analysis, with human findings also used as training data to improve subsequent machine-learning detection and classification.

CosmoQuest Mars Mappers feature identification & classification

Contributed to geospatial planetary analysis as an unpaid volunteer by identifying and classifying surface features in high-resolution Mars datasets. Focused on detecting dune-covered regions with potential volcanic activity to support the search for biosignatures and refine candidate zones for life detection missions under NASA-supported research.

CosmoQuest Moon Mappers feature identification & classification

Supported lunar science initiatives as an unpaid volunteer through systematic identification and classification of impact craters, domes, ejecta flows and anomalous surface formations in high resolution lunar imagery. Contributions aid in lunar geologic modeling and are integrated into topographic and morphological lunar atlases used in planetary geology research under NASA-supported research.

CosmoQuest Bennu Mappers feature identification & classification

Assisted the OSIRIS-REx mission as an unpaid volunteer by identifying and classifying rocks, boulders and craters in spacecraft-returned images of asteroid Bennu. These efforts supported site selection for sample return and mission safety. Participated in a collaborative dataset comprising over 14 million annotations contributed by 3,500+ volunteers under NASA-supported research.

Near-Earth Object Detection (Catalina Sky Survey)

Contributed to image classification and data validation as an unpaid volunteer to the NASA-funded Catalina Sky Survey (CSS) Minor Planet citizen science project by identifying and classifying minor planetary bodies in astronomical imagery. These contributions support NASA's Planetary Defense Coordination Office (PDCO) by improving asteroid detection, orbit confirmation, and machine learning datasets used to identify potentially hazardous near-Earth objects.

Solar Jet Hunter

Contributed to NASA’s heliophysics research as an unpaid volunteer by systematically identifying and classifying solar jet ejections in high-resolution Solar Dynamics Observatory (SDO) imagery. Collective classifications support the development of a comprehensive database of dynamic solar phenomena, advancing predictive modeling of solar-terrestrial interactions, space weather forecasting, and coronal mass ejection (CME) dynamics.

Planet Four: Ridges - NASA MRO/CTX Polygonal Ridge Classification

Contributed to planetary geomorphology research as an unpaid volunteer by identifying and classifying polygonal ridge networks in high-resolution Context Camera (CTX) imagery from NASA’s Mars Reconnaissance Orbiter. These spiderweb-like rectilinear ridge patterns, often located in Arabia Terra and Sinus Meridiani, provide insights into ancient Martian processes involving groundwater flow, volcanism, impact fracturing and erosion. Project classifications support mapping of inverted terrains and are used to investigate correlations with Noachian-aged surfaces, hydrated minerals and fine-grained deposits. This research informs planetary evolution models and guides high-priority target selection for future high resolution imaging missions.

NASA Globe Cloud Gaze

Engaged in atmospheric science classification as an unpaid volunteer by classifying cloud formations using Earth-based and satellite-derived imagery. Collective observational data contribute to research refining Earth system models including cloud-radiative forcing simulations and surface atmosphere energy balance calculations.

Recognition: NASA Globe Cloud Challenge Certificate Recipient 

Dark Energy and Galaxy Morphology (Galaxy Zoo/DECaLS)

Contributed as an unpaid volunteer to data classification and analysis of galaxies using DECaLS and SDSS datasets. Tasks included identifying and classifying spiral structure, merger signatures, bar formations and edge-on disk systems to support research into galaxy evolution and large-scale cosmological structure.

Human-AI Scientific Collaboration, Classification & Validation

Muon Hunter Classic

Contributed to astrophysics and particle detection research as an unpaid volunteer by identifying and classifying Cherenkov light patterns, specifically muon rings, in observational data from the VERITAS array (Very Energetic Radiation Imaging Telescope Array System). Human analysis and classification of ambiguous or overlapping rings helps distinguish background muon signals from gamma ray induced air showers and supports the refinement of algorithms used to filter and reconstruct high energy astrophysical events. These human-validated classifications contribute to improved machine learning model performance and the study of gamma-ray sources including supernova remnants, active galactic nuclei and potential dark matter annihilation regions.

Gravitational Lensing & Feature Classification and AI Training

Contributed to deep-field gravitational lensing surveys as an unpaid volunteer by identifying and classifying strong-lensing features, including arcs and Einstein rings in optical and near-infrared astronomical imagery. The human analysis and classifications support gravitational-lensing analysis and the study of cosmological parameters, including dark matter distribution, dark energy models and the Hubble constant. The work also contributed to human-AI collaboration by providing human-classified data to train and improve machine learning models for automated lens detection in support of ESA’s Euclid mission and the ASTERICS Horizon 2020 initiative.

Natural Science Observation & Classification

Botany & Geology Observations

As an unpaid volunteer contributor through iNaturalist, I document and classify native flora, lichens, ferns, seaweed and unique geological formations across diverse ecological zones. Research Grade observations become available to Smithsonian and academic databases, supporting studies in botany, geology and Earth science research.

Creative & Applied Exploration

Art, Light & Cosmic Form (Fine Art America storefront) 

An ongoing collection of original photography, digital artwork, and abstract visual compositions inspired by artificial intelligence, astronomy, natural systems, light, and the patterns found throughout nature. 

Many pieces originate from observations, concepts, and ideas explored through scientific research and AI-assisted creative workflows, while others are independent artistic interpretations of color, form, and texture.

Proceeds from artwork and other products purchased through the external Fine Art America storefront help support continued technology projects, scientific participation, equipment, and future independent research.

Independent Scientific Research and Publications

Alongside my AI and technology projects, I conducted independent scientific research combining field observation, photography, scientific data analysis, classification, computational methods, and theoretical modeling.

The research publications present a comprehensive analysis of Structured Light Phenomena (SLP) and Structured Light Dynamics (SLD) as reproducible macroscopic coherence structures formed under geomagnetically stable, low-turbulence conditions. It synthesizes several years of independent fieldwork (2022-2024) with rigorous theoretical modeling, integrating plasma physics, nonlinear optical field theory, quantum field dynamics and electromagnetic tensor principles. The work characterizes photonic formations exhibiting radial symmetry, quantized spectral banding and harmonic spatial coherence.

The research investigates Resonance-Restricted Actualization, a framework describing how coherent structures emerge across natural systems. Structured Light Phenomena serve as the empirical foundation, revealing how resonance and geometry constrain which physical outcomes persist. Extensions of this framework apply to quantum systems, architectural acoustics, and planetary-scale field dynamics.

Access all the published manuscripts or individually:

Delaney, S. (2025). Structured Light Phenomena: Resonant Fields in Natural Systems. Zenodo.

DOI: https://doi.org/10.5281/zenodo.15328111  (May 2, 2025)

Role: Foundational empirical corpus. Defines structured light phenomena (SLP) via field observation, photographic evidence, spectral analysis, and resonance framing. This is the empirical anchor for the entire body of work.

Delaney, S. (2025). Resonant Field Geometry in Nature: Structured Light Dynamics.Zenodo. 

DOI: https://doi.org/10.5281/zenodo.15620234 (June 6, 2025)

 (This version supersedes "Triadic Field Attractors and Resonant Symmetry in Nature")

Role: Mathematical and geometric formalization. Develops structured light dynamics (SLD) via resonance geometry, symmetry, attractors, and boundary-condition modeling.

Delaney, S. (2025). Acoustic-Photonic Resonance in Nature: Structured Light Dynamics. Zenodo.

DOI: https://doi.org/10.5281/zenodo.15665416 (June 15, 2025)

Role: Cross-modal empirical validation. Demonstrates phase-locked coupling between acoustic fields and photonic structure under natural conditions.

Delaney, S. (2025). Resonance-Restricted Quantum Actualization: Empirical and Theoretical Foundations. 

Zenodo. DOI: https://doi.org/10.5281/zenodo.15750986 (June 26, 2025)  

Role: Theoretical extension into quantum foundations. Introduces resonance as a constraint on quantum outcome realization, bridging classical field coherence with quantum actualization.

Delaney, S. (2025). Structured Light Phenomena and the Contemplative Dynamics of Consciousness. (Version 1.0) [Working paper]. Zenodo. 

DOI: https://doi.org/10.5281/zenodo.17508258 (November 2, 2025)

Role: Exploratory synthesis. Examines consciousness as a boundary or coupling condition in resonant field systems, without collapsing into reductionism.

Delaney, S. (2025). Planetary stability and biospheric dynamics: Within nonlocal intelligence frameworks (Version 1.0) [Working paper]. Zenodo.

DOI: https://doi.org/10.5281/zenodo.17778733 (December 1, 2025)

Role: Planetary-scale extension. Applies resonance and coherence principles to biospheric and geophysical stability regimes.

Delaney, S. (2025). Uxmal Pyramid of the Magician: Schumann-forced Alfvén Resonance.  (Version 1.0) [Working paper]. Zenodo.

DOI:. https://doi.org/10.5281/zenodo.17865354 (December 9, 2025)

 Role: Real-world architectural application. Demonstrates resonance geometry at human scale via Schumann-band forcing, Alfvénic coupling, and constructed boundary conditions.

Research Domains: Astrophysics, Quantum Field Theory, Nonlinear Optics, Plasma Physics, Electromagnetic Resonance, Mathematical Physics, Geophysics and Space Weather, Astronomy, Consciousness and Field Dynamics, Symbolic Systems and Geometry, Theoretical Cosmology

Keywords: structured light, field coherence, mesoscale resonance, nonlinear optics, quantum field theory, symbolic field encoding, resonance field theory, nonlocal interactions, spontaneous symmetry breaking, photonic coherence, quantum coherence, mesoscale resonance, prime-indexed structures, modular arithmetic, nonlinear optics, cymatics, self-organization, quantum field theory, plasma dynamics, electromagnetic resonance, field-induced pattern formation, environmental field interactions

Research Type: Independent theoretical modeling, structured light field observations and empirical resonance analysis
Research Lead: Susan Delaney (Independent, Self-funded)

Published In: CERN's Zenodo Research Repository (DOI registered)

Licensed: Creative Commons Attribution 4.0 International Content may be shared or adapted with attribution to Susan Delaney

Deployed Custom GPT Applications

Developed a collection of OpenAI domain-specific GPT applications that combine prompt engineering, structured reasoning, and AI-assisted workflows to support research, analysis, education, and creative exploration. Each application demonstrates a different approach to applying large language models to specialized knowledge domains.

• •  "Cosmic Quest Adventure": An interactive research simulation that combines deductive reasoning, scientific exploration, and problem-solving through virtual missions inspired by astronomy and astrophysics.

  • "Cosmic Weaver": A visual ideation assistant designed to explore field-based interactions, spatial relationships, and conceptual modeling through AI-assisted creative workflows and original artwork.

  • "Astro Light Explorer": An expert-level astronomy assistant that supports the interpretation of photometric observations, atmospheric optical phenomena, and structured light patterns through AI-assisted analysis and scientific reasoning.