My research focuses on developing scalable and efficient data analysis methods for large-scale complex datasets. I have designed state-of-the-art methods for complex problems in natural language processing, bioinformatics, energy informatics, neuroimaging, social and communication network analysis, sports, and human-sourced data analytics. My work employs tools from streaming algorithms, randomized and approximation algorithms, graph theory, machine learning, linear algebra, and deep learning. My research is characterized by its solid algorithmic and mathematical underpinning, providing theoretical justifications and analytical bounds for algorithm complexity. https://web.lums.edu.pk/~imdad/https://scholar.google.com/citations?user=aMwi6UwAAAAJ&hl=en