01
Solver-guided reasoning
Reasoning that holds up.
Connecting language models with formal verification to make reasoning more reliable.
RESEARCHER · EDUCATOR · LAB DIRECTOR
Making AI
reason better.
And earn trust.
I’m Dr. Muhammad Asif Ali.
Assistant Professor at ITU Lahore and Director of FORTE Lab. Exploring the foundations of intelligent, explainable, and culturally aware AI.
INFORMATION TECHNOLOGY UNIVERSITY
Lahore, Pakistan ↗
THE QUESTION THAT DRIVES MY
WORK
How can we make AI
worthy of our confidence?
Foundation models
✳
Reasoning
✳
Trustworthy
AI
✳
Explainable AI
01 / A LITTLE CONTEXT
Curiosity.
With purpose.
Building a deeper understanding of how AI thinks, learns, and makes decisions.
My research brings together large language models, formal reasoning, and trustworthy AI. From a Ph.D. at UNSW Sydney to research roles at KAUST and QCRI, my work has explored how intelligent systems can become more reliable across languages and real-world contexts.
02 / RESEARCH DIRECTIONS
Big questions.
Focused exploration.
Four connected directions towards AI we can understand, evaluate, and improve.
02
Reasoning drift
Understanding the misstep.
Detecting, explaining, and repairing errors within a model’s reasoning process.
03
Preference & culture
Intelligence in context.
Exploring AI alignment through pluralistic, contextual, and culturally grounded judgments.
04
Multilingual & multimodal AI
Beyond one language.
Studying knowledge, interpretation, and reliability across languages and modalities.
03 / SELECTED WORK
Ideas into
contributions.
All publications →
TNNLS
2026 · ACCEPTED
Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models
A systematic review
IJCAI-ECAI
2026
From Multimodal Perception to Strategic Reasoning
A survey on AI-generated game commentary
ACM TWEB
2026
Generative Regularities in Multi-Layer Networks
A shared latent space representation approach
05 / A SPACE FOR DISCOVERY
Good questions.
Better together.
FORTE Lab explores foundation models, reasoning, trustworthy and explainable AI. A place for curious minds to investigate what comes next.
Explore research opportunities ↗
FORTE.
FOUNDATION MODELS · REASONING
TRUSTWORTHY & EXPLAINABLE AI
Undergraduate / FYP / MS / Ph.D.
06 / IN THE CLASSROOM
Sharing the foundations.
FALL 2026 · ITU
Probability and Statistics
Foundations for the next generation of computer scientists.
Explore the course →