An educational and ethical AI research repository by Tawana Mohammadi (توانا محمدی).

🧠 Tawana Mohammadi | توانا محمدی

AI Researcher • Data Strategist • Educator

🌍 Ethical AI | Data Transparency | Human-Centered Technology


🎯 Overview

This repository represents part of my ongoing research and writing work as Tawana Mohammadi (توانا محمدی) — an AI Researcher and Educator working at the intersection of ethics, intelligence, and data strategy.
My goal is to make artificial intelligence transparent, inclusive, and educational, transforming AI from a black box into a bridge between technology and humanity.

“AI should remain transparent, inclusive, and grounded in empathy.”


🔬 Research Focus

  • Ethical AI Systems – Developing frameworks for responsible model design and deployment.
  • Prompt Engineering Education – Building educational tools for transparent prompt design.
  • Data Strategy & Governance – Creating ethical foundations for data-driven systems.
  • AI Literacy – Promoting awareness and accessibility of AI education.

Each model, dataset, and space here contributes to this mission — to empower ethical, open, and explainable intelligence.


📚 Current Projects

1️⃣ PromptCraft Framework

🧭 A modular educational toolkit for transparent prompt engineering and responsible AI design.
Includes examples, templates, and guidelines for interpretability and fairness.

2️⃣ AI Transparency Docs

📑 Templates and policy structures for building transparent AI systems.
Inspired by governance best practices and data ethics standards.

3️⃣ PanbehNet AI Portal

🌐 A data transparency experiment for public AI literacy in Farsi and English.
Demonstrates explainable models for education and analysis.


🧮 Technical Stack

Layer Technologies
Core Python • PyTorch • TensorFlow • Pandas • NumPy
Ethical Modeling SHAP • LIME • Explainable AI Toolkits
Interface Gradio • Streamlit • Hugging Face Spaces
Visualization Matplotlib • Seaborn • Plotly
Documentation Markdown • YAML • JSON Schema

🧭 Methodology

  1. Transparency-First Design: Every experiment includes ethical notes and interpretability goals.
  2. Human-Centered Evaluation: Metrics include qualitative assessment of AI fairness.
  3. Open Collaboration: All datasets and models are open-source and educationally oriented.
  4. Cross-Cultural AI Research: Emphasis on multilingual inclusivity and accessibility.

📈 Publications & References

  • Ethical Data Strategy in the Age of Generative AI — forthcoming whitepaper, 2025.
  • Transparent Prompt Engineering for Responsible Systems — educational series, Medium.
  • AI Governance & Literacy in Emerging Contexts — ongoing research series.

📘 Google Scholar – Tawana Mohammadi
🪪 ORCID Profile


🌐 Ethical AI Vision

The future of AI is not about automation — it’s about augmentation, understanding, and accountability.
Every dataset, model, and notebook should tell a story about human values and shared intelligence.

“Where ethics meets intelligence, innovation becomes empathy.”

My research explores how education and design can bring that principle to life.


🧩 Connect with Me

🔗 Website – tawana.online
🔗 GitHub – Open Projects
🔗 Kaggle – Data Ethics Notebooks
🔗 Medium – AI Transparency Essays
🔗 Substack – Research Letters
🔗 LinkedIn – Professional Network
🔗 Reddit – Community Dialogues
✉️ [email protected]


🪶 Signature

Tawana Mohammadi | توانا محمدی
AI Researcher • Data Strategist • Educator
Last updated: October 2025

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