Santiago Segarra awarded Army Early Career Program (ECP) Award

The ECP award is among the most prestigious honors granted by the Army to outstanding scientists beginning their careers.

Santiago Segarra

Santiago Segarra, W. M. Rice Trustee Assistant Professor of electrical and computer engineering (ECE) at Rice has been awarded the Early Career Program (ECP) Award for his research on "Information Fusion from Unaligned Networks" by the Army Research Office, a directorate of the U.S. Army Combat Capabilities Development Command Army Research Laboratory (DEVCOM ARL).

The ECP award is among the most prestigious honors granted by the Army to outstanding scientists beginning their careers. The purpose of the ECP is to draw outstanding new university faculty members to pursue research in areas related to the Army. The program also encourages and supports these faculty members in their endeavors to teach and continue research in these areas.

DEVCOM ARL manages the Army’s extramural research program. It funds research proposals from educational institutions, nonprofit organizations and private industry to raise fundamental knowledge and understanding in the sciences that have an impact on enabling new and improved Army operational capabilities and related technologies beneficial to national security needs.

The objective of Segarra’s proposal is to “derive a comprehensive theory and efficient algorithms to jointly learn from unaligned networks.” In order to “further equip the data-driven and network-centric Army of the future by enabling fast and autonomous extraction of actionable knowledge across all networked systems.”

“The ability to rapidly and continuously integrate all domains of warfare in multi-domain operations is key to deterring and fighting against near-peer adversaries. Such integration requires the fusion and processing of data from diverse sources to extract critical and actionable intelligence.” Segarra said.

Many data sources are relational in nature and can be represented as networks, e.g., interconnected sensors, communication between soldiers, networked manned and unmanned platforms, and human-machine collaboration in tactical scenarios. Hence, in order to aid the decision-making of human and artificial intelligence (AI) agents, one needs to combine information from multiple networks and make it available at the right time and at the right place.

Segarra received his M.Sc. in Electrical Engineering and his Ph.D. in Electrical and Systems Engineering from the University of Pennsylvania, Philadelphia, in 2014 and 2016 respectively.

He joined the George R. Brown School of Engineering ECE Department of Rice University in July of 2018 and was awarded the Rice’s School of Engineering Research + Teaching Excellence Award in 2021. Before joining Rice, he served as a postdoctoral research associate at the Institute for Data, Systems, and Society at the Massachusetts Institute of Technology from 2016 to 2018.

His research focuses on network theory, data analysis, machine learning, and graph signal processing.