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Ty Roman

Ty Roman

Key Skills

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Freelancer Overview

I am an Electrical Engineering student with hands-on experience in data annotation, technical content curation, and AI training data processes, particularly for STEM and engineering domains. My background includes evaluating AI-generated solutions for correctness and clarity, providing Reinforcement Learning from Human Feedback (RLHF), and designing structured prompts to assess reasoning accuracy in technical topics like circuit theory and signal processing. I am skilled in Python for data analysis, MATLAB, SPICE simulation tools, and technical documentation. My work involves delivering qualitative feedback on AI outputs, annotating technical datasets, and translating complex engineering concepts into structured, actionable data for model improvement. I am passionate about contributing to projects focused on technical reasoning, structured feedback pipelines, and advancing AI systems’ understanding of engineering content.

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Labeling Experience

AI Training & Data Annotation (Independent Practice and LLM Technical Reasoning Evaluation)

TextEvaluation Rating
I evaluated AI-generated technical and STEM solutions for correctness, clarity, and logical consistency in independent and academic projects. My work included providing Reinforcement Learning from Human Feedback (RLHF)-style feedback and conducting qualitative model assessments. I curated and annotated technical datasets to support improved AI performance in engineering problem-solving tasks. • Designed and structured prompts to assess Large Language Model (LLM) reasoning accuracy. • Delivered detailed, rubric-based evaluations of AI-generated explanations. • Annotated and organized engineering content for training data purposes. • Performed qualitative analysis to enhance AI-driven technical solutions.

I evaluated AI-generated technical and STEM solutions for correctness, clarity, and logical consistency in independent and academic projects. My work included providing Reinforcement Learning from Human Feedback (RLHF)-style feedback and conducting qualitative model assessments. I curated and annotated technical datasets to support improved AI performance in engineering problem-solving tasks. • Designed and structured prompts to assess Large Language Model (LLM) reasoning accuracy. • Delivered detailed, rubric-based evaluations of AI-generated explanations. • Annotated and organized engineering content for training data purposes. • Performed qualitative analysis to enhance AI-driven technical solutions.

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Education

A

Arizona State University

Bachelor of Science, Electrical and Electronic Engineering

Bachelor of Science
2021

Work History

A

Arizona State University

Electrical Engineering Student Researcher

Denver
2022 - Present