Dr. Petar M. Djuric Serves as Lead Guest Editor for IEEE Signal Processing Magazine Special Issue

Dr. Petar M. Djuric

 

 

 

 

 

Dr. Petar M. Djurić, Distinguished Professor in the Department of Electrical and Computer Engineering at Stony Brook University and Fellow of IEEE, EURASIP, AAIA, and AIIA, is serving as Lead Guest Editor of a special issue of IEEE Signal Processing Magazine focused on methodological advances in causal inference.

IEEE Signal Processing Magazine is the most influential and widely read publication in the signal processing community. The special issue highlights emerging research that advances the theory, methodology, and applications of causal inference within signal processing and related fields.

For more context: https://www.stonybrook.edu/commcms/ceas/faculty/highlights.php

Advancing causal inference for next-generation AI

Causal inference plays a critical role in the development of next-generation artificial intelligence systems. Unlike purely data-driven approaches that rely on pattern recognition, causal methods enable AI systems to reason about why events occur. This capability is essential for building AI that is more trustworthy, explainable, and robust when adapting to new or changing environments.

The special issue curated by Dr. Djurić brings together leading contributions that address fundamental challenges in causal modeling, learning, and inference. These advances are expected to influence a wide range of applications, including machine learning, decision-making systems, and data-driven scientific discovery.