People
Faculty
Muhammad Qasim Pasta
Muhammad Qasim Pasta is a Computational Social Scientist specializing in bibliometric extraction, network science, and data science to model collaboration and citation networks, particularly from the Global South. He co-founded Data Research Lab Pakistan, advancing contextual datasets to support evidence-based research and decolonize data production. He also co-leads the Forum for Research on Phenomenon-Oriented Science (FoRPhOS), building open tools and metrics for interdisciplinary research impact. His work bridges quantitative and social scientific methods to reveal patterns of knowledge production.
Asad Tariq
Asad is a Dean's Fellow in the department of Computer Science at Habib University. He recevied his masters in Computational Social Science from the University of California, San Diego as a Fulbright Scholar, and his bachelors in Computer Science from Habib University. His research interests include dynamically evolving human social networks which he studies using agent-based modeling, game theory and computational network graph based simulations.Speakers
Umberto Mignozzetti
Umberto Mignozzetti is an Assistant Teaching Professor of Political Science and Computational Social Sciences at the University of California, San Diego, where he teaches across the Department of Political Science and the Computational Social Sciences Program. His methodological research develops deep learning approaches that integrate tabular data with non-tabular sources such as images, video, audio, and GIS, and he leads The DeepVerse Lab. His substantive work draws on comparative politics and political economy, with a regional focus on Latin America, to study how developing democracies can improve the provision of public goods, combining formal modeling, field and survey experiments, and elite and popular surveys. His papers have contributed to debates on the nexus between legislature size and welfare, the failures of bottom-up accountability, the effects of elite capture, and elite preferences over climate change mitigation agreements. His work has appeared in the American Journal of Political Science, the British Journal of Political Science, the Journal of Experimental Political Science, Research and Politics, and Global Environmental Politics.
Shah Jamal Alam
Shah Jamal Alam is Professor of Computer Science and Associate Dean for Undergraduate Education at Habib University in Karachi, Pakistan, where he has been a founding faculty member since 2014. His research sits at the intersection of agent-based modeling, social network analysis, and computational social science, with applications spanning infectious disease dynamics, climate adaptation, and political discourse on social media. He completed his PhD at the Centre for Policy Modelling, Manchester Metropolitan University, where his doctoral work modeled the socioeconomic dynamics of HIV/AIDS in rural South Africa. He subsequently held postdoctoral appointments at the University of Michigan School of Public Health, where he worked on NIH-funded agent-based models of HIV risk dynamics and genetic transmission networks, and at the University of Edinburgh School of GeoSciences, where he contributed to EU-funded projects on land-use change and climate adaptation. His work has appeared in journals including Epidemiology, Landscape Ecology, PLOS One, and the Journal of Artificial Societies and Social Simulation, and he serves on the Editorial Board of PLOS Complex Systems. He recently served as Area Co-Chair for the Modelling and Simulation of Societies track at AAMAS 2026, and is a member of the European Social Simulation Association, the Association for Computing Machinery, and the Computational Modeling in Social and Ecological Sciences network.
Abdul Samad
Abdul Samad is an Associate Professor of Computer Science at Habib University in Karachi, Pakistan. He completed his PhD at the University of Georgia as a Fulbright scholar, where as part of the RNA-Informatics Lab his doctoral research modeled biomolecular structure prediction using maximum spanning-tree algorithms on backbone graphs. His research interests span machine learning, deep learning, and natural language processing, with a particular focus on the fine-tuning of large language models. His recent work in NLP includes projects on Urdu text generation and genre classification, reflecting a commitment to developing computational tools for South Asian languages and contexts. He has supervised numerous theses and published research across conferences and journals in the field.
Muhammad Bilal
Dr. Muhammad Bilal (SMIEEE) is an Assistant Professor in the School of Computing at FAST National University of Computer and Emerging Sciences (NUCES), Islamabad. He holds postdoctoral research experience from the University of Florida, USA. His work centers on computational social science with a strong emphasis on social media data analytics. His research includes social and political profiling, mobility behavior analysis, and assessing reviewer network strength on e-commerce platforms. He has further contributed to the study of social computing technologies for Society 5.0, leveraging digital trace data to understand human behavior and societal dynamics. His broader research interests include natural language processing, data mining, machine learning, information processing, social computing, and software engineering. Dr. Bilal is a recipient of Taylor’s Ph.D. Scholarship and a Bronze Medal in his undergraduate studies. He has also been awarded a Faculty Research Support Grant for his project titled 'Detecting Mis/Disinformation and Reducing Information Overload in Social Media Platforms Using Machine Learning.'
Muhammad Yaseen Khan
Muhammad Yaseen Khan is a Computer Scientist specializing in Natural Language Processing for low-resource languages and affective computing. He currently serves as an Assistant Professor in the Department of Artificial Intelligence and Data Science at FAST-NUCES, Karachi. His research focuses on enabling artificial intelligence systems to better understand human language, emotions, and behaviour, with particular emphasis on multilingual and underrepresented linguistic communities. Beyond academia, he brings industry experience from leadership and technical roles at Tyler Technologies (in collaboration with Microsoft), Alibaba Group, and Alexa Translations, where he has contributed to large-scale machine learning, data science, and software engineering initiatives.
Ihsan Ayyub Qazi
Dr. Ihsan Ayyub Qazi is a Professor of Computer Science at the Lahore University of Management Sciences (LUMS), where he co-leads two of Pakistan's most ambitious research initiatives: the National Center in Big Data & Cloud Computing and the National AI Hub. He also serves as the Director of LUMS’s Digital Health program and its online learning platform, LUMSx. He holds a Ph.D. from the University of Pittsburgh and has held research appointments at the University of California, Berkeley and institutions in Australia and Germany. His research sits at the intersection of clinical AI and digital health, information integrity, and trustworthy AI systems. He has published in top-tier venues spanning computer science, economics, and medicine including ACL, ACM SIGCOMM, CHI, Nature Health, the New England Journal of Medicine (NEJM) AI, and the Journal of Development Economics. His work has been supported by the World Bank Group, the Gates Foundation, a Google Faculty Research Award, and multiple Meta Integrity Research Awards. He has also been recognized with teaching and alumni achievement honors from LUMS and the University of Pittsburgh.
Tafseer Ahmed Khan
Dr. Tafseer Ahmed is professor at Mohammad Ali Jinnah University, Karachi. He is a computational linguist with over 25 years of experience in academia and industry. He received his PhD from the University of the University of Konstanz (Germany). His work bridges classical linguistic theory and modern machine learning, with a particular focus on South Asian languages and multilingual natural language processing (NLP). He has held academic roles at major universities in Pakistan , and contributed to industry. He has collaborated on international research projects, including with the University of Colorado and a DAAD-funded initiative, and has delivered talks at venues such as Yale University and ESSLLI.
Zain Ahmed Usmani
Zain Ahmed Usmani is a researcher whose work sits at the intersection of computational social science, agent-based modeling, and AI. He holds a B.S. in Computer Science from Habib University, with experience across data science, social simulation, reinforcement learning, and sustainability. His research applies agent-based models to complex social systems, with a focus on equity and water distribution — including an ongoing ABM project on Karachi in collaboration with Tufts University. He is passionate about interdisciplinary research and empowering others through teaching.
