B D'Alessandro

Papers

Total Citations

H-Index

About

Ben D'Alessandro is a leading researcher in computational advertising and online fraud detection, with a focus on the integrity of digital advertising ecosystems. His most-cited work, "Using co-visitation networks for detecting large scale online display advertising exchange fraud" (2013, 25 citations), pioneered the use of network-based methods to uncover sophisticated ad exchange fraud, a critical issue as online behavioral data increasingly drives industry decisions. This research, presented at KDD, demonstrated how co-visitation patterns could reveal fraudulent traffic at scale, directly impacting the security of programmatic advertising. D'Alessandro's contributions lie at the intersection of data mining, network analysis, and applied machine learning, offering practical solutions for detecting abuse in real-time bidding environments. His work is notable for its early recognition of the vulnerabilities in data-driven advertising models, influencing both academic research and industry practices. With a career dedicated to making online advertising more transparent and trustworthy, D'Alessandro remains a key voice in the fight against digital fraud, inspiring students and researchers to explore the ethical dimensions of big data analytics.