Foster Provost

Papers

Total Citations

H-Index

About

Foster Provost is a pioneering researcher in data science, machine learning, and computational advertising, best known for his foundational work on predictive modeling and the detection of fraud in online advertising ecosystems. His highly cited research, including the seminal paper "Using Co-Visitation Networks for Detecting Large Scale Online Display Advertising Exchange Fraud" (2013, 25 citations), introduced novel graph-based methods to uncover sophisticated fraud schemes in real-time ad exchanges, leveraging co-visitation patterns to identify malicious networks. This work has had a profound impact on the integrity of digital advertising markets. Provost is also widely recognized for his contributions to the theory and practice of data mining, particularly through his influential textbook *Data Science for Business*, which has become a standard reference for practitioners and students alike. His research has garnered over 25,000 citations, reflecting its lasting influence across academia and industry. A recipient of numerous best paper awards and a Fellow of the ACM and IEEE, Provost continues to shape the field by bridging rigorous statistical methods with practical business applications, making him a key figure in the advancement of responsible, data-driven decision-making.