Professor Singh’s research sits at the intersection of consumer research, information systems, and data science, seeking to understand consumer behavior and marketing phenomena through advanced quantitative and computational approaches, including artificial intelligence, machine learning, and large language models.

A parallel strand of his work examines how emerging AI systems are transforming research methods and scientific inquiry. In particular, he studies the use and evaluation of generative AI, LLMs, and AI agents as tools for empirical research and knowledge discovery, with an emphasis on their reliability, validity, and methodological implications. His broader agenda is to develop and apply rigorous computational and AI-enabled methods that generate credible knowledge about consumers, markets, and increasingly AI-mediated modern society.

Singh also consults firms and policymaking organizations, helping them leverage untapped data to build AI-driven models for evidence-based decision-making.

An award-winning educator, Singh received the University of Glasgow’s Best Teacher Award in 2026 and is a Fellow of the UK Higher Education Academy. He teaches marketing analytics, AI and machine learning, text mining using LLMs, and data engineering, and his courses combine conceptual grounding with hands-on work in R and Python.