Pre-university Computer Science student from Pakistan preparing for BS Computer Science (Fall 2026) with a long-term focus on Artificial Intelligence research, multilingual NLP, Retrieval-Augmented Generation, and low-resource language technologies.

I am building the mathematical, engineering, and research foundations required to contribute to the next generation of AI systems, with particular interest in Urdu language technology and knowledge-access systems.

My goal is to develop AI systems that improve access to information for underrepresented languages and communities.

I am particularly interested in:

• Natural Language Processing (NLP)
• Retrieval-Augmented Generation (RAG)
• Large Language Models (LLMs)
• Information Retrieval
• Low-Resource Language AI
• Multilingual Knowledge Systems
• Urdu Language Technology
• AI for Public Services
• AI for Education

PAKGOV-RAG is a bilingual Urdu-English Retrieval-Augmented Generation system designed to improve access to Pakistani government information.

Target sources include:

• Federal Board of Revenue (FBR)
• Higher Education Commission (HEC)
• National Database and Registration Authority (NADRA)
• Securities and Exchange Commission of Pakistan (SECP)
• Supreme Court documentation
• Public-sector regulations and policies

• Bilingual Question Answering
• Knowledge Retrieval
• Government Information Accessibility
• Urdu Language AI Resources
• Public-Interest AI Applications
• Retrieval-Augmented Generation Research

• Python
• PyTorch
• Hugging Face Transformers
• FAISS
• LangChain
• Vector Databases
• Multilingual Embeddings

• Python
• Git
• GitHub
• Linux

• Machine Learning
• Deep Learning
• Natural Language Processing
• Transformer Architectures
• Information Retrieval
• Retrieval-Augmented Generation

• Reproducible Experiments
• Model Evaluation
• Dataset Construction
• Research Documentation
• Open Source Development

Current focus:

• Algebra
• Pre-Calculus
• Calculus
• Linear Algebra
• Probability
• Statistics

Building a strong mathematical foundation before advanced machine learning and research work.

Current areas of study:

• Python Programming
• Data Structures & Algorithms
• Machine Learning
• Deep Learning
• NLP Systems
• Information Retrieval
• Academic Research Methods
• Scientific Writing

• HackerRank Python Certification
• HP LIFE Ambassador
• HP LIFE: Critical Thinking in the AI Era
• SoloLearn Python Certificate
• Kaggle Learning Certificates
• ADB Institute AI Coursework

I believe strong AI systems are built through:

• Mathematical rigor
• Reproducible research
• Consistent experimentation
• Open-source collaboration
• Long-term learning

This profile documents that journey publicly.

Bachelor of Science in Computer Science

Primary focus:

• Artificial Intelligence
• Natural Language Processing
• Retrieval-Augmented Generation
• Machine Learning Research

Research themes:

• Urdu NLP
• Multilingual Language Models
• Retrieval-Augmented Generation
• Knowledge Systems
• Information Access Technologies
• Low-Resource Language Research

Long-term objective:

Contribute to AI systems that make knowledge more accessible across linguistic and socioeconomic boundaries.

Planned professional research presence:

• GitHub
• LinkedIn
• Kaggle
• Personal Research Website
• Hugging Face Hub
• ORCID
• Google Scholar
• arXiv

github.com/salikhussain71-code

linkedin.com/in/salik-hussain-7822a1388

kaggle.com/salikhussain

x.com/salikhussain71

salikhussain71@gmail.com

Rawalpindi, Punjab, Pakistan

Building the foundations for impactful AI research through mathematics, engineering, and multilingual language technology.