Max Russo

Max Russo is an Assistant Professor of Statistics at the Ohio State University, where he focuses on developing advanced statistical methodologies for biomedical research and healthcare data analysis.

• PhD from the University of Padova (2019)
• Research spans computational statistics, Bayesian modeling, and clinical trial design
• Key applications: drug safety profiling, high-dimensional data analysis, electronic health records (EHR)

Russo's research combines Bayesian statistics with computational innovation, particularly for challenges in clinical trial design and real-world evidence generation. He specializes in:

• Variational Bayes techniques for scalable inference
• Signal detection in high-dimensional healthcare databases
• Bayesian decision theory for adaptive clinical trials
• Electronic health records (EHR) analysis
• Pharmacoepidemiology and medication safety

His recent publications highlight cross-disciplinary impacts in biostatistics and public health, with a focus on:

• Drug safety surveillance using claims data
• Comparative effectiveness of pharmaceutical interventions
• Algorithmic approaches for complex healthcare datasets
• Policy implications of clinical trial design

Contact: Russo.325@osu.edu