AI • Data • Research

AI Model Training & Evaluation Specialist

AI model training and evaluation specialist with four years of experience in prompt engineering, custom GPT development, AI model evaluation, structured AI workflows, and AI-assisted research. My work focuses on improving AI response quality through systematic evaluation, human validation, information quality, and evidence-based methodologies. I design structured workflows that evaluate model outputs, validate factual accuracy, identify inconsistencies, and iteratively refine prompts to develop accurate, reliable, and trustworthy AI-assisted solutions.

Before specializing in AI, I developed a strong foundation in enterprise technology spanning SQL development, enterprise data, business intelligence, data quality, systems administration, security administration, and analytical problem-solving. Those experiences continue to shape my approach to AI evaluation through structured reasoning, rigorous validation, and evidence-based methodologies.

Featured Areas

AI Model Training & Evaluation

Prompt engineering, AI response evaluation, custom GPT development, structured AI workflows, human-in-the-loop evaluation, information quality, AI-assisted research, and AI workflow optimization.

Data & Analytics

Enterprise SQL development, business intelligence, reporting and analytics, data quality, metadata validation, decision-support systems, analytical problem-solving, and information management.

Research & Publications

Published interdisciplinary research supported by Python scientific computing, observational analysis, structured evaluation methodologies, and public scientific datasets. My ORCID profile and 2025 CERN Zenodo research corpus document ongoing investigations into structured light phenomena and resonant field dynamics.

Citizen Science & Astronomy

Contributor to NASA-affiliated citizen science initiatives, AAVSO observations, ESA projects, Zooniverse image classification, satellite imagery, space telescope observations, photographic plates, and collaborative scientific research.

Current Focus

My current work centers on AI model training and evaluation, prompt engineering, AI-assisted research, and information quality. I design structured AI workflows, develop custom GPT applications, evaluate AI-generated responses, validate factual accuracy, identify inconsistencies, and iteratively refine prompts to improve model performance, response quality, and reliability.

I also volunteer with a multi-branch public library system, where I conducted an independent evaluation of contemporary nonfiction collections using AI-assisted information evaluation and a structured, evidence-based methodology. This work included developing nonfiction acquisition recommendations, collection weeding guidance, metadata validation, bibliographic verification, and an executive decision-support report supporting collection development and long-term planning.

Although my independent research culminated in a seven-paper publication corpus in 2025, the analytical methodologies developed throughout that work continue to inform my approach to AI model evaluation, information quality, structured classification, evidence-based decision-making, and technical problem-solving.

Throughout my career, from enterprise technology and business intelligence to AI evaluation and independent research, one principle has remained constant: transforming complex information into accurate, reliable, and evidence-based knowledge.

Featured AI Solutions

This portfolio showcases practical AI solutions developed across multiple large language model (LLM) platforms. These projects demonstrate prompt engineering, agentic workflow design, knowledge synthesis, research automation, and domain-specific AI applications. Representative outputs are included where appropriate, while proprietary prompt engineering methodologies and implementation details remain confidential.

OpenAI Custom GPTs

Interactive AI applications designed to support researchers, technologists, educators, and scientific exploration through specialized prompt engineering, structured AI workflows, and domain-specific expertise.

"Cosmic Quest Adventure": Interactive educational astronomy experience that combines scientific exploration with gamified learning.

"Cosmic Weaver": AI-assisted visualization tool for exploring conceptual models of a timeless, spatial universe.
"Astro Light Explorer:" Expert-level astronomy research assistant supporting observational analysis and scientific inquiry.

Agentic AI Workflows

xAI Grok Automations

Autonomous AI workflows that execute on a recurring schedule to synthesize scientific information, generate structured reports, and automate research-oriented tasks.

Designed and deployed autonomous xAI Grok workflows for scientific reporting and publication analytics.

Project 1: Daily Astronomical Sun & Moon Times

Overview

This automation workflow executes on a daily schedule, retrieves astronomical ephemeris information for a specified observing location, synthesizes the results into a human-readable observational summary, and delivers the report automatically by email. The underlying prompt architecture is proprietary.

Platform

• xAI Grok

Project Type

• Agentic AI Automation

• Scheduled AI Workflow

• Automated Scientific Information Delivery

Objective

Develop an autonomous AI workflow that generates and emails a daily astronomical observing report containing solar and lunar ephemeris information for a specified observing location.

Capabilities

• Executes automatically on a daily schedule.

• Retrieves current astronomical ephemeris data.

• Generates a structured natural-language summary.

• Calculates sunrise and sunset times.

• Reports moonrise, moonset, and lunar illumination.

• Includes observational context relevant to amateur astronomy.

• Delivers the report automatically by email.

Representative Results

The automation provides:

• Sunrise and sunset time

• Moonrise and moonset times

• Lunar illumination percentage

• Daylight duration

• Observing conditions

• Narrative interpretation suitable for planning observations

Skills Demonstrated

• Agentic AI workflow design

• Prompt engineering

• Workflow automation

• Structured data interpretation

• Technical communication

• Astronomy domain knowledge

• Automated report generation

The following representative screenshots demonstrate engineering and automation of the Astronomical Sun & Moon Times workflow.

Project 2: Daily Zenodo Publications Analytics 

Overview

This autonomous AI workflow monitors my published Zenodo research corpus on a recurring schedule, analyzes publication metadata, generates concise summaries of individual works, and compiles the results into a structured research report delivered automatically by email. The workflow streamlines ongoing publication monitoring while preserving proprietary prompt engineering and implementation details.

Platform

• xAI Grok

Project Type

• Agentic AI Automation

• Research Analytics

• Scholarly Publication Intelligence

Objective

Develop an autonomous AI workflow that monitors and summarizes a research publication corpus, transforming technical academic metadata into concise, readable research analytics delivered automatically.

Zenodo Publications Analytics Project Workflow

Autonomous workflow that analyzes a scholarly publication corpus and generates structured publication summaries for ongoing research monitoring.

Capabilities

• Executes on a recurring schedule.

• Reviews the current Zenodo corpus.

• Identifies publications and associated metadata.

• Generates concise summaries of each publication.

• Produces a structured research overview.

• Delivers the report automatically via email.

Technical Highlights

• Agentic AI workflow design

• Prompt engineering

• Scientific literature summarization

• Metadata interpretation

• Automated research analytics

• Structured report generation

• Technical communication

• Autonomous scheduled execution

Skills Demonstrated

• Agentic AI workflow design

• Prompt engineering

• Workflow automation

• Scientific literature summarization

• Research metadata analysis

• Knowledge synthesis

• Technical writing

• Automated analytics and reporting

Representative Results

The workflow produces a concise summary of published research, including publication titles, DOI references, and technical descriptions suitable for rapid review and portfolio monitoring.

Implementation Note

The underlying prompt architecture, workflow logic, and optimization techniques are proprietary. Screenshots are provided to demonstrate functionality and output quality while protecting implementation details.

The following representative screenshots demonstrate engineering and automation of the of Zenodo Publications Analytics project workflow.

Technologies & Platforms

OpenAI GPTs

xAI Grok

Prompt Engineering

Agentic AI

Workflow Automation

Research Analytics

Scientific Data Interpretation

Knowledge Synthesis

Technical Documentation

AI-Assisted Research