Haq Nawaz

Haq Nawaz

NLP Researcher • AI & Data Science Consultant • Developer of Quranic and Classical Arabic Educational Systems

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About Me

I am Haq Nawaz — an Islamic scholar and an AI and NLP researcher specializing in the intersection of Arabic linguistics, Qur’anic studies, and computational language modeling. My work bridges classical Islamic scholarship with modern artificial intelligence, focusing on digitization, morphology, and cross-lingual natural language processing. Over the years, I have led multiple national and international projects on Qur’anic data analysis, machine translation, and educational technology.

I currently serve as a Consultant AI Strategist at ILI.DIGITAL AG (Germany) , working from the Lahore office. My role involves designing and implementing AI-driven strategies for business transformation, developing large language model workflows, and leading automation initiatives that bridge enterprise operations with modern machine intelligence.

Alongside my professional work, I teach Arabic grammar and morphology at Jamia Ashrafia Lahore, and supervise advanced research on Arabic NLP and digital Qur’anic education. My broader goal is to create AI systems that preserve and enhance access to classical Arabic knowledge.

Technical Expertise

My technical focus integrates AI, Natural Language Processing, and Arabic–Urdu linguistics. Each domain reflects a blend of academic insight and practical experience in deploying intelligent systems for linguistic and Qur’anic research.

Artificial Intelligence & Machine Learning

  • Large Language Models (GPT-4, Claude 3.5, LLaMA, Mistral).
  • Retrieval-Augmented Generation (RAG) and vector databases (FAISS, Chroma, Pinecone).
  • Fine-tuning (LoRA, QLoRA), Reinforcement Learning, and Model Evaluation.
  • Recommendation Systems, Semantic Search, and Generative AI Application Design.

Natural Language Processing & Linguistics

  • Specialization in Arabic–Urdu NLP: Building rule-based and neural systems for Qur’anic text understanding and translation.
  • Altasreef Engine: A rule-based Arabic morphology generator with 200+ classical verb and noun templates.
  • QTest Translation Pipelines: Cross-lingual Arabic–Urdu–English mapping with morphological context awareness.
  • Corpus Development: Uthmani–Indo-Pak script alignment and linguistic annotation for Arabic NLP research.

Cloud & MLOps

  • AWS: SageMaker, Textract, Bedrock, and S3 for scalable AI deployment.
  • Azure OpenAI Services: Model hosting, orchestration, and fine-tuning integration.
  • Docker & CI/CD: Automated pipelines for ML model packaging and deployment.
  • MLflow: Experiment tracking, version control, and A/B testing for models.

Programming & Frameworks

  • Python (Expert): FastAPI, Flask, TensorFlow, PyTorch, Hugging Face Transformers.
  • Databases: SQL, PostgreSQL, MongoDB, and JSON-based corpus structuring for linguistic data.
  • Frontend Integration: RESTful APIs and JavaScript for interactive web-based educational systems.

Highlighted Projects

A glimpse into my ongoing and completed projects that combine AI, Arabic linguistics, and digital education. Each system represents a milestone in Islamic NLP, digitization, and modern learning innovation.

QTest — AI-Powered Qur’anic Learning Ecosystem

A modular Qur’anic NLP platform integrating quizzes, exams, teaching dashboards, and translation modules in Arabic, Urdu, and English — bridging madrasah learning with AI-assisted pedagogy.

Visit QTest

Altasreef — Classical Arabic Morphology Engine

A rule-based engine for generating and analyzing Arabic verb and noun patterns according to Ilm-us-Sarf. Supports 10+ Abwaab and 25+ grammatical variations with Urdu and English translations.

Visit Altasreef

Mohaddis.com — The Largest Urdu Hadith Encyclopedia

A comprehensive Hadith repository hosting major collections in searchable Unicode Urdu, enabling advanced cross-referencing, thematic exploration, and access to authentic narrations.

Visit Mohaddis

Tanzeem Islami Digital Library

A large-scale Urdu digitization platform preserving the works of Dr. Israr Ahmad and Tanzeem-e-Islami publications, featuring searchable Unicode text, author filters, and a user-friendly interface.

Visit Library
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Research Focus

My research lies at the intersection of computational linguistics, Arabic NLP, and AI-assisted Islamic studies. I focus on developing rule-based and deep-learning models that enhance Arabic morphology analysis, cross-lingual text reuse detection, and digital Qur’anic interpretation tools.

View Research Publications