Hello, It's Me

Dr. M. Usman Ghani Khan

Sultan Qaboos IT Chair. Member, National AI Task Force (MOPDSI). Professor. CS Dept. UET Lahore , Director National Center of AI, UETL. Professor Trainer for AI and allied domains. Director Computer and IT Cell.

I have over 21 years of Research Experience
in
Download Resume

About Me

250 +

Publications

50 +

Research Grants

40 +

Foreign Experties

500 +

Trained Professors

I have over 21 years of Research Experience in

I am currently serving as the Sultan Qaboos IT Chair at the University of Engineering and Technology (UET), Lahore, and as a Professor in the Department of Computer Science. I completed my BS and Master’s degrees with distinction from UET Lahore and earned my PhD from the University of Sheffield, UK. I have also had the opportunity to serve as a visiting scholar at Toshiba, the University of Edinburgh, and the University of Oxford.

My doctoral research focused on statistical modeling for machine vision signals, particularly language-based descriptions of video streams. Over the years, my research has continued to evolve around image, video, speech, and text processing, with applications in information extraction, retrieval, summarization, and intelligent multimedia systems.

I previously completed a full tenure as Chairman of the Computer Science Department at UET Lahore. I am also serving as Director of the Computer & IT Cell and head the Repair and Maintenance Cell. In addition, I have served as Director of Financial Aid and Scholarships for more than five years. These academic and administrative roles have allowed me to contribute to teaching, research, institutional development, student support, and technology-driven transformation at the university level.

My core areas of expertise include Machine Vision, Natural Language Processing, Speech Technology, Bioinformatics, Machine Learning, Deep Learning, Generative AI, Agentic AI, and Expert Systems. I have extensive experience in teaching advanced computing courses and mentoring students in research theses, final year projects, and applied AI systems. I have also recorded freely available video lectures on YouTube for courses including Bioinformatics, Image Processing, Data Mining, Data Science, and Computer Programming.

I lead the National Centre of Artificial Intelligence (NCAI), where I have established and supervised seven research labs: Computer Vision and Machine Learning, Bioinformatics, Data Science, Information Dissemination, UET Game Studio, Software Systems Research Lab, Generative AI Research Lab, and AI-enabled Cyber Security and Quantum Computing. Through these labs, my focus has remained on building practical AI solutions for real-world challenges across healthcare, agriculture, education, judiciary, public policing, smart and safe cities, cybersecurity, and public-sector decision support.

I have published over 350 research papers in leading scientific journals and conferences, with more than 8,000 citations, an h-index of 50, and an i10-index of 180. My recent research is centered on integrated multimedia frameworks that combine text, audio, and visual processing into unified intelligent systems.

My broader mission is to strengthen local AI capacity, connect academic research with real-world deployment, and build technology that creates measurable impact for society.     

  • Explore My Work

    I actively work on research, development, and applied AI projects focused on solving real-world problems across healthcare, education, agriculture, public safety, judiciary, smart cities, cybersecurity, and intelligent multimedia systems.

    A complete list of my projects is available here:
    Projects Portfolio: View My Projects

    I also regularly write articles on Artificial Intelligence, emerging technologies, education, innovation, and practical digital transformation.
    Articles & Blogs: Read My Articles

    My academic publications, citations, h-index, and research impact can be viewed through my Google Scholar profile.
    Google Scholar: View Research Profile

    You can also connect with me through my official professional and social platforms:

    LinkedIn: Muhammad Usman Ghani Khan
    X / Twitter: @DrUsmanGhaniK
    YouTube: Digital Trainings by Usman
    Instagram: @dr_usmanghanikhan

Powered by Froala Editor

Download Resume More About Me

Citations per year

Citations: 8000

h-index: 50

i10-index: 180

Tool & Languages

C Language
100%
C Language
C++ Language
100%
C++ Language
C Sharp
100%
C Sharp
Java Language
100%
Java Language
JavaScript
100%
JavaScript
Python
100%
Python
HTML 5
100%
HTML 5
CSS 3
100%
CSS 3
Bootstrap
100%
Bootstrap
React
100%
React
Qt
100%
Qt
Microsoft SQL Server
100%
Microsoft SQL Server
SQLite
100%
SQLite
Oracle
100%
Oracle
MySQL
100%
MySQL
MongoDB
100%
MongoDB
PostgreeSQL
100%
PostgreeSQL
Firebase
100%
Firebase
Heroku
100%
Heroku
Amazon Web Services
100%
Amazon Web Services
Docker
100%
Docker
Google Cloud
100%
Google Cloud
Mircosoft Azure
100%
Mircosoft Azure
Django
100%
Django
Pocoo Flask
100%
Pocoo Flask
MATLAB
100%
MATLAB
Postman
100%
Postman
Adobe Photoshop
100%
Adobe Photoshop
Scikit-Learn
100%
Scikit-Learn
seaborn
100%
seaborn
OpenCV
100%
OpenCV
Pandas
100%
Pandas
Pytorch
100%
Pytorch
TensorFlow
100%
TensorFlow
GitSCM
100%
GitSCM
Linux
100%
Linux

Top 10 Research Papers

1

A deep learning approach for automated diagnosis and multi-class classification of Alzheimer’s disease stages using resting-state fMRI and residual neural networks

2

A realistic image generation of face from text description using the fully trained generative adversarial networks

3

Brain tumor segmentation in multi‐spectral MRI using convolutional neural networks (CNN)

4

Deep unified model for face recognition based on convolution neural network and edge computing

5

Deep learning model integrating features and novel classifiers fusion for brain tumor segmentation

6

Computer-assisted brain tumor type discrimination using magnetic resonance imaging features

7

Soft computing-based EEG classification by optimal feature selection and neural networks

8

Technologies and challenges in developing Machine-to-Machine applications: A survey

9

Microscopic abnormality classification of cardiac murmurs using ANFIS and HMM

10

GHS-NET a generic hybridized shallow neural network for multi-label biomedical text classification

Research Papers

My adventures from around the world
Cross-lingual transfer learning approaches by using pre-trained BERT models
Bidirectional Encoder Representation from Transformers (BERT)
Experimental evaluation reveal that the fine-tuned models of mBERT and roBERTa-urdu
A Multi-Genre Urdu Broadcast Speech Recognition System
Understanding and accurate information retrieval through search engines and task-oriented dialogue systems
Intent Detection in Urdu Queries using Fine-tuned BERT models

Our Staff

Bisma Saleem Research Team Lead of CVML Lab
Dr. Usman Ghani Khan Director
Umar Daraaz Lodhi Team Lead of CVML Lab
M Nauman Hanif Team Lead of IDL Lab