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Adaeze Joy Nzeakor

AI Evaluation & Research Portfolio

Adaeze Joy Nzeakor

Overview

#Open to Remote Opportunities I bring a background in Mass Communication, corporate communications, research, professional writing, and digital technology support. I am interested in helping improve AI systems through structured evaluation, factual review, clear feedback, and careful analysis.

About Me

I hold a BSc in Mass Communication and have experience in corporate communications, website management, content development, presentation design, training support, digital tools, and administrative coordination. These experiences provide strong transferable skills for AI evaluation and research support, including: - Clear and objective written communication. - Research and information synthesis. - Critical review of written content. - Attention to detail and consistency. - Identifying unclear or unsupported claims. - Organising information and documenting findings.

  • Mass Communication
  • Corporate Communications
  • Content Development
  • Research Synthesis

AI Response Evaluation

Assessing accuracy, helpfulness, and safety

Research and Fact-Checking

Verifying claims against credible references

Instruction-Following Assessment

Checking multi-constraint adherence

Response Comparison

Side-by-side quality and tone analysis

Content Quality Review

Evaluating clarity, style, and structure

Rubric-Based Scoring

Applying systematic evaluation frameworks

Professional Writing and Editing

Refining text for precision and tone

Research Synthesis

Distilling complex data into clear briefs

Structured Feedback

Documenting actionable insights

Sample Case Study 01

AI Response Evaluation Demonstration

Evaluation · Rubric Scoring · Comparative Analysis

A systematic comparison of two AI-generated answers to a nuanced query about remote team communication tools, evaluating tone, completeness, and factual accuracy.

Focus
Response Comparison
Domain
Productivity Software

Challenge

Compare two distinct AI outputs for the same prompt to determine which better balances comprehensiveness and readability.

Stages

  1. Prompt Analysis
  2. Criteria Definition
  3. Scoring & Verdict

Prompt Analysis

Examined the original prompt for explicit and implicit constraints, including target audience and formatting requirements.

Criteria Definition

Established clear metrics: factual accuracy, adherence to structure, tone appropriateness, and clarity.

Scoring & Verdict

Applied a structured rubric to evaluate both outputs objectively, highlighting strengths and weaknesses.

Solution

Conducted a granular breakdown of Response A and Response B using a standard 5-point evaluation scale across four defined criteria.

Result

Demonstrated how structured rubrics eliminate subjectivity in AI performance grading.

Sample Case Study 02

AI Fact-Checking and Research Review

Fact-Checking · Research · Verification

An audit of an informational AI response concerning historical renewable energy milestones, verifying dates, figures, and attributions.

Focus
Fact-Checking & Research
Domain
Environmental Science

Challenge

Identify and rectify subtle factual inaccuracies and unverified claims within an AI-generated summary.

Stages

  1. Claim Extraction
  2. Source Verification
  3. Documentation

Claim Extraction

Isolated individual factual assertions from the generated text.

Source Verification

Cross-referenced claims against peer-reviewed journals and authoritative institutional databases.

Documentation

Compiled a correction report detailing unsupported statements and providing verified alternatives.

Solution

Systematically verified every quantitative claim and updated timelines with corroborated data sources.

Result

Produced a clean, fully verified document free of hallucinations or outdated metrics.

Sample Case Study 03

Instruction Following and Content Quality Assessment

Instruction Following · Quality Control · Constraint Check

Evaluating an AI model's capacity to follow a complex, multi-part prompt featuring negative constraints and specific formatting rules.

Focus
Constraint Adherence
Domain
Technical Writing

Challenge

Assess whether an AI response successfully managed competing instructions without omitting key requirements or introducing irrelevant padding.

Stages

  1. Constraint Mapping
  2. Gap Analysis
  3. Quality Improvement

Constraint Mapping

Deconstructed the prompt into an itemized checklist of mandatory and prohibited elements.

Gap Analysis

Audited the AI output against each checklist item to pinpoint omissions and extraneous additions.

Quality Improvement

Proposed targeted prompt refinements and output edits to enhance precision.

Solution

Identified two missed constraints and one instance of unsupported assumption, documenting specific corrective feedback.

Result

Highlighted actionable strategies for improving instruction-following compliance in LLM outputs.

Sample Case Study 04

Research Synthesis and Brief Writing

Research Synthesis · Executive Briefs · Information Design

Demonstrating how raw data points, user research notes, and market statistics can be condensed into a professional executive brief.

Focus
Synthesis & Briefs
Domain
Digital Communication

Challenge

Synthesize disparate qualitative notes into a coherent, structured research brief suitable for decision-makers.

Stages

  1. Information Sorting
  2. Synthesis
  3. Formatting

Information Sorting

Categorized raw source materials by thematic relevance and priority.

Synthesis

Distilled core takeaways while maintaining nuance and evidentiary backing.

Formatting

Structured the final output with clear headings, bullet points, and an executive summary.

Solution

Transformed dense, unstructured source material into an easily navigable, highly readable briefing document.

Result

Showcased rigorous information handling and clear professional communication standards.

Evaluation Process & Methodology

  1. 11. AnalysisCarefully review the prompt, instructions, and target output guidelines to establish complete alignment with expectations.
  2. 22. AssessmentEvaluate responses against rigorous criteria including factual correctness, tone, safety, and constraint adherence.
  3. 33. DocumentationProvide clear, structured feedback, scores, and actionable justifications to help improve system performance.
Digital Media Portfolio
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