Hi, I'm Muhammad Muneeb 👋

Computational Biologist • AI Researcher • Genomics & Biomedical NLP Developer

I build AI-assisted research tools for genomics, polygenic risk scoring, biomedical literature mining, variant interpretation, genotype–phenotype prediction, and scientific workflow automation.

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About Me

I am a PhD Candidate in Computational Biology at The University of Queensland, working at the interface of artificial intelligence, genomics, bioinformatics, statistical genetics, biomedical NLP, and translational discovery.

My research focuses on developing reproducible computational frameworks for:

• Genotype–phenotype prediction
• Polygenic risk score benchmarking
• AI-driven biomedical literature mining
• Variant interpretation and evidence extraction
• Phenotype-associated gene discovery
• Genetics-informed drug repurposing
• Multimodal biomedical data integration
• Research software and workflow automation

I enjoy building practical tools that turn complex biological, clinical, and literature-scale datasets into usable research outputs.

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Research & Technical Focus

AI + Genomics
├── Polygenic Risk Scores and genomic prediction
├── Genotype–phenotype modelling
├── Biomedical NLP and LLM-based evidence extraction
├── Variant interpretation and literature mining
├── Drug repurposing and target prioritisation
├── Heritability estimation and benchmarking
├── Reproducible bioinformatics pipelines
└── Research software, dashboards, and web tools

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Featured AI, Genomics & Research Software Projects

Project	Area	Description
PRSGPT	LLMs / PRS / Bioinformatics	Domain-adapted large language model workflow for polygenic risk score guidance and bioinformatics question answering.
BioStarsGPT	Biomedical NLP / LLMs	Fine-tuned LLM system for bioinformatics Q&A, scientific knowledge extraction, and specialised research support.
LitVarAI	Biomedical Literature Mining	AI-assisted pipeline for biomedical literature discovery, variant extraction, evidence annotation, and ClinVar-oriented validation.
PRSTools	Polygenic Risk Scores	Benchmarking and implementation-aware evaluation framework for polygenic risk score tools and genomic prediction workflows.
GWASPoker	GWAS / PRS QC	Automated tool for parsing, validating, harmonising, and assessing GWAS summary statistics before PRS analysis.
EFGPP	Genotype–Phenotype Prediction	Exploratory framework integrating PRS, phenotype-level signals, cross-trait features, and machine learning for genomic prediction.
G2DR	Drug Repurposing	Genotype-first framework for genetics-informed target prioritisation, drug repurposing, and translational evidence synthesis.
JobsDownloaderAndRanker	Applied AI / NLP	Local-first job discovery and resume-ranking system using semantic similarity, skill matching, and interactive dashboards.
PhenotypeToGeneDownloaderR	Disease-Gene Evidence	R pipeline for phenotype-to-gene evidence collection, database comparison, validation, and downstream translational analysis.
Automating Literature Review	AI Research Automation	AI-assisted system for literature retrieval, summarisation, evidence ranking, and biomedical research synthesis.

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Public Platforms & Web Tools

Platform	Description
MuhammadLab Tools	Browser-based tools for research, documents, images, data processing, learning, AI, security, forensics, and genetic file-format utilities.
Muhammad Lab	Educational and research technology platform covering AI, programming, cybersecurity, bioinformatics, and research workflows.
ResearchMate	Research-support platform for discovering supervisors, collaborators, and academic profiles using structured search and matching workflows.
SwiftConvertor	Web-based conversion platform for documents, images, PDFs, text, and productivity utilities.

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Selected Research Themes

mindmap
  root((My Research))
    AI for Genomics
      Genotype-Phenotype Prediction
      Deep Learning
      Multimodal Data Integration
    Polygenic Risk Scores
      PRS Benchmarking
      GWAS Summary Statistics
      Heritability Estimation
    Biomedical NLP
      Literature Mining
      Variant Extraction
      LLM Fine-Tuning
    Translational Genomics
      Drug Repurposing
      Target Prioritisation
      Disease-Gene Evidence
    Research Software
      Python Pipelines
      R Workflows
      Dashboards
      Web Tools

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Technical Skills

Programming, Data Science & Research Computing

Machine Learning, Deep Learning & LLMs

Genomics, Bioinformatics & Biomedical Data

Software Engineering & Deployment

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Academic Background

Degree	Institution	Focus
PhD in Computational Biology	The University of Queensland, Australia	AI-driven genomics, genotype–phenotype prediction, PRS benchmarking, translational genomics
MSc in Computer Science, Artificial Intelligence	Khalifa University, UAE	Genotype–phenotype prediction using artificial intelligence algorithms
BSc in Computer and Information Sciences	PIEAS, Pakistan	Computer science, AI, software engineering, blockchain, and applied computing

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Teaching & Mentoring

I also teach and develop learning resources across information technology, programming, cybersecurity, digital forensics, machine learning, and research computing.

Current and previous teaching areas include:

• Python programming
• Machine learning applications
• Cybersecurity
• Digital forensics
• Information networks
• Advanced programming
• IT project management
• Professional practice in IT

Teaching resources: Muhammad Muneeb Teaching Resources

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Current Research Direction

I am interested in building AI systems that can help researchers move from:

genetic data
   ↓
biological interpretation
   ↓
literature evidence
   ↓
disease-gene understanding
   ↓
therapeutic hypothesis generation
   ↓
reproducible research software

My long-term goal is to develop practical, transparent, and reproducible AI tools that support biomedical discovery and translational genomics.

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GitHub Analytics

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Connect With Me

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Building AI-assisted tools for genomics, biomedical discovery, and reproducible research.