Saurabh Sihag

I am a postdoctoral researcher working with Dr. Alejandro Ribeiro at the University of Pennsylvania. Broadly, I study statistical inference and machine learning approaches over graph models, both from theoretic and algorithmic perspectives with applications in network neuroscience. Previously, I received the PhD degree in Electrical Engineering at Rensselaer Polytechnic Institute in Dec., 2020, where I was advised by Dr. Ali Tajer. My PhD thesis on Statistical Learning and Inference over Networks can be accessed here.

My research is interdisciplinary and spans the domains of signal processing, machine learning, neuroscience, and information theory. I have worked on a variety of research problems that include statistical learning of graph models (AISTATS, NeurIPS), state estimation in signal processing (T-IT, JSTSP, SPL), graph signal processing analyses of multimodal brain imaging data (TSIPN) and association of neuroimaging features with blood biomarkers (NatCommsMed), and adaptive graph-constrained group testing (TSP). Currently, I am investigating statistical inference using graph neural networks (VNN), with brain age prediction as a recent application (VNN_Brain_Age). A complete list of my research publications is available here.