Bowei Xi

Bowei Xi is an Associate Professor at the Department of Statistics at Purdue University. He holds a Ph.D. in Statistics from the University of Michigan (2004) and has made significant contributions to adversarial machine learning, cybersecurity, and metabolomics.

• Education: Ph.D. in Statistics, University of Michigan (2004)

His research focuses on:

• Adversarial Machine Learning – Developing defenses against attacks on AI systems
• Cybersecurity – Integrating statistical methods with network security
• Metabolomics – Applying statistical analysis to biological data
• Big Data – Creating scalable analytical frameworks
• Differential Privacy – Balancing data utility with privacy preservation

Recent publications highlight:

• Advancements in causal inference under privacy constraints
• Novel cyber deception strategies for battlefield IoT
• Applications of graph neural networks with dropout techniques
• Statistical defense mechanisms against adversarial examples

Awards include:

• Faculty of 1000 Evaluation (2011)
• US Patents #7272707 and #7490234 for application server optimization

He teaches STAT 514: Design of Experiments with a focus on hands-on learning and statistical software (SAS) integration. His office hours and contact details are publicly listed for student engagement.