Speakers

Yaser Daanial Khan

Place of Birth : Lahore, Pakistan
Position : Professor of Computer Science, University of Management and Technology (UMT)
Field of study : Computer Science, Bioinformatics, Machine Learning, and Artificial Intelligence

Dr. Yaser Daanial Khan is an internationally acclaimed Professor of Computer Science at the University of Management and Technology (UMT), Lahore, renowned for his groundbreaking contributions to bioinformatics, artificial intelligence, machine learning, and computational biology. With over two decades of distinguished service in both academia and the software industry, Dr. Khan has seamlessly bridged theoretical innovation with real-world application, developing intelligent systems for biomedical discovery, surveillance, and national infrastructure. He has authored numerous high-impact publications in leading JCR-indexed journals, advancing the frontiers of genomic data analysis, protein function prediction, and AI-driven biomarker discovery. As an affiliate scholar at George Mason University, USA, and a recipient of prestigious international research grants, Dr. Khan has led and collaborated on multidisciplinary projects across the USA, Saudi Arabia, and Europe. In addition to his prolific research, Dr. Khan has held key academic leadership roles including Dean and Chairperson of Computer Science, spearheading curriculum innovation, faculty development, and research excellence. He also serves on the editorial boards of leading journals and is a trusted reviewer for publishers like Springer, Elsevier, IEEE, and Oxford University Press. Blending visionary research, academic leadership, and software engineering expertise, Dr. Khan is a thought leader driving the next generation of computational intelligence in life sciences and beyond.

• PhD in Computer Sciences
• Affiliate Scholar: George Mason University, USA

• Professor of Computer Science, University of Management and Technology (UMT), Lahore (Present)
• Dean and Chairperson of Computer Science (Past)
• 29 years of Industry, Teaching, and Research Experience

• Computer Science
• Bioinformatics
• Machine Learning
• Artificial Intelligence
• Computational Biology
• Genomic Data Analysis
• Protein Function Prediction
• AI-driven Biomarker Discovery