Vishvak Murahari
PhD researcher
Princeton University
Vishvak Murahari is a PhD researcher at Princeton University and a co-author of GEO: Generative Engine Optimization, the KDD 2024 paper that named the field and released GEO-bench. His work covers NLP systems and information discovery, including how content changes show up inside generative answers.
Language Research at Princeton
Murahari's Princeton PhD work focuses on natural language processing systems that have to find and use information under real retrieval conditions.
He co-authored GEO with Pranjal Aggarwal, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan, and Ameet Deshpande. Equal-contribution notes on the preprint list him with an affiliation at Princeton.
The KDD Paper That Named GEO
The KDD 2024 paper formalizes generative engines as systems that synthesize answers from multiple sources, then introduces generative engine optimization as a black-box framework for improving creator visibility inside those answers. The authors argue that creators otherwise have little control as generative engines replace classic result lists.
GEO-bench ships as a public query set across domains with associated sources, so strategies can be compared instead of argued from anecdote. The paper reports that certain optimization strategies can raise visibility substantially in their evaluation setting, while also stressing that effects vary by domain.