Python · Mathematics · Artificial Intelligence

Where Mathematics Meets Intelligence

PMAI Lab is a multidisciplinary research and learning platform advancing artificial intelligence, deep learning, graph neural networks and data-driven technologies—grounded in mathematical strength and computational practice.

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Research-led Experiment-driven Interdisciplinary
∑ ∫ ∂ ∇ λ π Mathematics Foundations
f(x) → θ Algorithms Structure
Learning Adaptation
✦ Intelligence Discovery

Current activity

Latest from PMAI Lab

Recent events, ideas and research directions from our multidisciplinary community.

Event

Python for Beginners

A faculty development workshop introducing Python fundamentals and practical computational applications.

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Insight

Why Mathematical Thinking Still Matters in Modern AI

A PMAI Lab perspective on how mathematical reasoning supports the understanding of intelligent systems.

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Research Ongoing

Variants in Graph Neural Networks

Exploring graph-based mathematical representations for advancing learning in neural and graph neural networks.

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PMAI Foundations

Three disciplines, One connected ecosystem

The PMAI Perspective

Mathematics turns complexity into structure, data into insight, and computation into intelligence.

Connected scientific frontiers

  • System Intelligence
  • Data Science
  • Network Science
  • Robotics
  • Computational Biology
  • Quantum Technologies

People behind PMAI Lab

A community of mentors, researchers and builders.

Meet the full team
Dr. Hira BenishDr. Hira BenishMathematics · AI · Data Science↗M. Sohail AkhtarM. Sohail AkhtarAI · Autonomous systems · Python↗Dr. Muhammad Asad IqbalDr. Muhammad Asad IqbalMathematics · Algebra · AI↗

Research at PMAI Lab

From mathematical questions to intelligent systems.

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Established foundation

Graph Theory & Network Analysis

Studying mathematical structures, connectivity and relationships within complex networks.

Active exploration

Mathematical Foundations of AI

Exploring the linear algebra, probability and optimization underlying modern learning systems.

Emerging direction

Graph Learning & Intelligent Networks

Investigating connections between graph structures, network representations and machine learning.

Applied collaboration

Data Analytics & Computational Modelling

Applying mathematical and computational methods to data-driven problems across different fields.

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