Talks and presentations

Feature Selection for Network Intrusion Detection: An Information-Theoretic Approach

May 08, 2025

Talk, KDD 2025, Toronto, Canada

I will present my research on information-theoretic feature selection for network intrusion detection systems. This work introduces novel methods to identify minimal yet maximally discriminative features in cybersecurity datasets, significantly reducing computational overhead while maintaining state-of-the-art detection accuracy. The talk will include:

Partial Information Decomposition for Data Interpretability and Feature Selection

April 04, 2025

Talk, AiStats 2025, Splash Beach Resort, Mai Khao, Phuket, Thailand

I will present my work on Partial Information Decomposition (PIDF) as part of the opening session of AiStats 2025. This will cover novel methods for quantifying redundant, unique, and synergistic information in high-dimensional datasets, with applications to interpretable machine learning and feature selection.

Charles Westphal

Talks and presentations

Feature Selection for Network Intrusion Detection: An Information-Theoretic Approach

Partial Information Decomposition for Data Interpretability and Feature Selection