Uzafir A. Rafaq

Mathematician and Computer Scientist

Research Profile

Electrical and software engineer pursuing research in Physics Informed Machine Learning and Human-Computer Interaction. Research deals with statistical mechanics, probabilistic modeling, dynamical systems, and human participant experiments. Experienced in turning models into deployed, reproducible software systems.

Statistical mechanicsArtifical IntelligenceHuman-Computer InteractionHigh Performance Computing

Education

  • MSc Software Engineering2025 to 2026
    Heriot-Watt UniversityDubai, United Arab Emirates
    Dubai, United Arab Emirates•2025 to 2026
    • Dissertation: Thermodynamic Human-Computer Interaction.
    • Developed a target prediction model using Hamiltonian, Lagrangian and statistical mechanics; implemented and evaluated the model across desktop and mobile interaction.
    • Derived the 70 year old empirical Fitts' Law and Schmidt's Law from thermodynamics.
    CodeDemo
  • BSc Electrical Engineering2018 to 2022
    Institute of Space TechnologyIslamabad, Pakistan
    Islamabad, Pakistan•2018 to 2022
    • Dissertation: Sign language glove using machine learning and the Google Translate API to convert hand gestures into speech in multiple languages.
    • Gold Medal for Best Final Year Project.
    CodeDemo

Awards and Honours

  • Gold Medal for Best Final Year Project2022
    Institute of Space TechnologyIslamabad, Pakistan
    Islamabad, Pakistan•2022

Invited Talks

  • Thermodynamic aspects of Computer Science13 October 2026
    National Autonomous University of MexicoOnline, Mexico
    Online, Mexico•13 October 2026

    Invited to speak in the Complexity Theory seminar on the thermodynamic aspects of artificial intelligence at Mexico’s best university

Skills

Languages

Python
JavaScript
TypeScript
SQL

Frameworks

React
Next.js
Django
Express
NestJS
Docker
WebRTC

Databases

PostgreSQL
MongoDB
Redis

Cloud

Google Cloud Platform
AWS
Azure
DigitalOcean

Projects

  • Intent Link2026
    intentlink.dev

    A thermodynamics based target prediction and prefetching library achieving 98% accuracy and a fetch to click ratio of 1.37 in the reported evaluation.

    npm package
  • Beep2024
    beep.gov.pk

    Implemented WebRTC with a MediaSoup signaling server to create audio and video calling for the government.

Experience

  • Ordion.ioRemote, United States
    Software EngineerDecember 2024 to August 2025
    Remote, United States•December 2024 to August 2025

    Worked on ecommerce performance and cloud infrastructure across frontend and backend systems, including caching, prefetching, load balancing, and automated deployment.

  • Linter LabsIslamabad, Pakistan
    Software EngineerOctober 2023 to December 2024
    Islamabad, Pakistan•October 2023 to December 2024

    Worked on a live messaging and video conferencing platform across frontend and backend systems, including real time communication infrastructure.

  • ML Sense SolutionsIslamabad, Pakistan
    Software EngineerMarch 2022 to October 2023
    Islamabad, Pakistan•March 2022 to October 2023

    Worked on cloud cost reduction, chatbot development, and data analytics projects across frontend, backend, and cloud systems.

Publications

  1. [1]Uzafir Ahmad Rafaq, Muaz Hassan, and Ali Muzaffar. 2026. Thermodynamic Human-Computer Interaction. arXiv:2608.07123 [cs.HC]. Under review at ACM CHI.