Rate My Professor Hafiz Asif

Hafiz Asif serves as Assistant Professor of Information Systems and Business Analytics in the Frank G. Zarb School of Business at Hofstra University. He holds a PhD from Rutgers University and a BS from Lahore University of Management Sciences. Following his doctoral studies, he undertook a postdoctoral position at the Institute of Data Science, Learning, and Applications. His academic career centers on developing methodologies and systems to realize Safe AI and Analytics, prioritizing security, privacy, algorithmic transparency, fairness, and equity in high-stakes decision-making areas including loan eligibility, job candidate recommendations, parole determinations, and healthcare resource allocation.

Dr. Asif employs techniques from cryptography, differential privacy, federated learning, secure multiparty computation, statistics, machine learning, and optimization to devise safe algorithms such as efficient data mining processes, outlier analysis, spatiotemporal queries, and synthetic data generation, as well as practical safe systems like privacy-protecting platforms and the COVID Nearby tool for pandemic tracking. He spearheaded the Scarlet PETs project, securing victory in the 2023 US-UK Privacy Enhancing Technologies Prize Challenge for anomaly detection through privacy-enhanced federated learning. Notable publications encompass "Differentially Private Range Counting: Where Asymptotically Better Fails, Integer Covering Prevails" (2025), "Cafe: Improved Federated Data Imputation by Leveraging Missing Data Heterogeneity" (IEEE, 2025), and the IEEE Computer Society 2022 Best Paper Award recipient "Intelligent Pandemic Surveillance via Privacy-Preserving Crowdsensing." He also contributed to an IEEE Spectrum article on risks of AI-generated software in 2023. Among his honors are the Zarb School of Business Innovation Research Fellow Grant for privacy enhancements in large language models. Dr. Asif has presented at the Future of Privacy Forum, Inpher, INRIA France, and IBM, and teaches AI & its Applications, Ethical AI, and Statistics at Hofstra.