Jitendra Subramanyam, PhD

Data and Analytics Practice Leader, Gartner
Jitendra Subramanyam is a data and analytics practice leader at Gartner, leading a research team that serves chief data officers in companies worldwide. Prior to joining Gartner in April of 2018, Subramanyam was the head of machine learning solutions at Synaptiq AI, a consultancy devoted to solving practical business problems through the power of machine learning. At Synaptiq AI, Subramanyam led engagements for a diverse group of clients in media, technology, healthcare, and government. Working closely with customers, he was responsible for scoping the machine learning solution, crafting the right performance measures (both business and technical), and working hands-on with small teams of data scientists to implement the machine learning solution. His projects spanned using machine learning to extract content from PDFs, matching similar but differently described vehicles across multiple automobile catalogs, improving customer engagement via personalization, and developing advanced anomaly-detection techniques to fight cybercrime. Prior to Synaptiq AI, Subramanyam led highly productive research teams at The Hackett Group, CAST Software, and CEB (now Gartner), being actively involved in every stage of the research lifecycle from idea to deliverable. He is the lead author of Hackett's 2012 Book of Numbers and produced research on defining and measuring technical debt, evaluating the success of technology business management (TBM) processes, quantifying software complexity, and improving the structural quality of large-scale software systems. He is a contributor to the industry standard specification for automated measurement of software application size. Subramanyam holds a bachelor's degree in electrical engineering from the University of Maryland and a PhD in philosophy of science from the University of Michigan. His doctoral thesis is on building a deterministic mathematical framework for quantum theory.


  • PhD University of Michigan