Research. Engineering.
Education. Built to ship.
INFERENCE Lab conducts reproducible AI research, builds production-grade systems, and trains engineers who can design, deploy, and scale AI in the real world. Evidence over hype. Engineering over branding.
- Largest
- ROMAN URDU LANGUAGE RESOURCE
- SOTA
- MODELS FOR LOW-RESOURCE LANGUAGE & HEALTH RESEARCH
- GLOBAL
- RESEARCH COLLABORATIONS & PUBLICATIONS
- 4+
- OPEN-SOURCE AI LIBRARIES
One organization, three reinforcing tracks.
INFERENCE Lab is an applied AI research and engineering organization founded by Muhammad Khubaib Ahmad. It operates as original research, AI/software engineering services, and structured engineering education — under one identity, each track reinforcing the others' credibility.
Our aim: close the gap between people who know AI concepts and engineers who can build, deploy and maintain AI systems.
Engineering discipline over hype
Real, deployed output — not demos that break the moment they leave a notebook.
Evidence over branding
Reproducible pipelines, proper evaluation, and a permanent DOI on every research release.
Output over certificates
You leave with systems on GitHub and models on HuggingFace, not a PDF.
Research, Engineering & Education
Explore how INFERENCE Lab combines academic research rigor with full-lifecycle software engineering and technical mentorship.
Explore our Research
Rigorous scientific output spanning vocal biomarkers, low-resource Roman Urdu corpora, human-centered cognitive sensing, and post-quantum encryption schemes.
Featured Work & Focus:
- Clinical-grade vocal fatigue screening
- RUEmoCorp & RUDaSA corpora
- Workstation cursor kinematics sensing
- Zenodo open data & DOI citations
Programs we Offer
Structured, deployment-focused engineering programs. Live weekend mentorship covering software fundamentals, classical ML, Transformers, RAG systems, and MLOps.
Featured Work & Focus:
- Applied AI Engineering Program (12.5 Mo)
- AI Builder Program (5.5 Mo)
- Weekly GitHub code deliverables
- Independent capstones per phase
Systems & Software Released
Production-grade software, reproducible model pipelines, and PyPI libraries built and released by lab engineers and fellows.
Featured Work & Focus:
- ECAPA-TDNN-VHE voice engine
- Deterministic image encryption
- RUEmoCorp Roman Urdu NLP
- FastAPI microservices & Docker repos
Join the Lab
Work alongside lab leadership on published research, build open-source tools, or join our Engineering Fellowship cohorts.
Featured Work & Focus:
- Engineering Fellowship Cohort
- Research Internships
- Open-Source Collaboration
- Academic & Industry Partnerships
Train as an engineer, collaborate on research, or build a system with us.
Currently running our online cohorts and preparing the Engineering Fellowship. Reach out about mentorship, research collaboration, or bespoke AI engineering services.