His paper titled, "Network Topology Inference from Spectral Templates," was co-authored with Antonio G. Marques, Gonzalo Mateos, and Alejandro Ribeiro. It was published in the IEEE Transactions on Signal and Information Processing over Networks magazine (Volume: 3, Issue: 3, Sept. 2017).
The award-winning paper focused on identifying the structure of an undirected graph from the observation of signals defined on its nodes. The paper leverages concepts from convex optimization and stationarity of graph signals to identify the graph shift operator and showcase the effectiveness of the proposed algorithms in recovering synthetic and real-world networks.
Segarra will be presented the award at the 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021) held in Toronto, Canada. He will be joined by fellow Rice ECE professors Kevin Kelly and Richard Baraniuk, who have been nominated for the 2020 IEEE SPS Signal Processing Magazine Best Paper Award for their paper "Single-Pixel Imaging via Compressive Sampling: Building simpler, smaller, and less-expensive digital cameras."
Santiago Segarra joined the Rice ECE department in 2018 after serving as a Postdoctoral Research Associate with the Institute for Data, Systems, and Society at the Massachusetts Institute of Technology (MIT). In 2017 he received the Penn’s Joseph and Rosaline Wolf Award for Best Doctoral Dissertation in Electrical and Systems Engineering. His current research focus area is data science for networks and modeling, analysis, and designing networked systems.