Claudia Perlich
Papers
1
Total Citations
25
H-Index
1
About
Claudia Perlich is a leading researcher in computational advertising, machine learning, and data science, with a focus on the intersection of online behavior, fraud detection, and predictive modeling. Her work has significantly advanced the understanding of large-scale data generated by web interactions, particularly in detecting fraud in display advertising exchanges. In her highly cited 2013 paper, "Using co-visitation networks for detecting large scale online display advertising exchange fraud," Perlich introduced innovative network-based methods to identify fraudulent activity, leveraging co-visitation patterns to uncover systematic abuses in real-time bidding systems. This contribution has been foundational for the advertising industry, helping to protect billions of dollars in digital ad spend. With over 25 citations on this work alone, her research has shaped how practitioners approach data integrity and model robustness in online environments. Perlich is also known for her role as Chief Data Scientist at Media6Degrees and later at Dstillery, where she applied her expertise to build scalable, data-driven solutions. Her work continues to inspire students and researchers tackling the challenges of big data, fraud, and algorithmic fairness.
Research Focus
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Top Papers
- 1