image: César A. Uribe
Credit: Rice University
HOUSTON – (April 30, 2025) – César A. Uribe, the Louis Owen Assistant Professor of Electrical and Computer Engineering at Rice University, has won a Faculty Early Career Development (CAREER) Award from the National Science Foundation (NSF)to advance the mathematical foundations of decentralized learning, a critical area for the future of artificial intelligence (AI), data science and distributed systems.
The highly competitive grants awarded to early career faculty across the country each year recognize emerging leaders in research and education.
The award will support Uribe’s investigation into how to enable faster, more efficient learning across a number of computing units connected over sparse networks that process massive amounts of data without relying on a single centralized coordinator. His work will lay the theoretical groundwork on large scale data processing for improving fields such as digital health monitoring and environmental data analysis, where traditional centralized approaches can no longer keep up with the scale and complexity of modern data.
“We are now in a regime where the data is so large no single computer can handle the storage and processing part of machine learning by itself,” Uribe said. “Instead, what most companies are doing now is instead of having a single computer, you have networks of computers connected to each other with each doing a bit of the data crunching and talking to the other computers in the network in a coordinated manner.”
Uribe’s research focuses on developing new mathematical tools to solve the core challenges that arise in these decentralized systems. His projects are organized around three key thrusts: structure, models and methods.
The first thrust addresses how computers or processing units should be connected to balance efficient communication with strong performance.
“If you try to connect every computer to every other computer, it becomes too expensive in terms of communication and also storage and computation to sustain,” Uribe said. “So the first part of this project involves figuring out how to design these types of networks in such a way that you can still guarantee good performance with a minimal amount of communication.”
The second thrust focuses on what types of computation individual computers should perform to improve systemwide outcomes, specifically exploring nonclassical information aggregation methods. The third thrust advances new algorithmic strategies, moving beyond first-order methods like gradient-based algorithms to higher-order methods that can significantly boost the speed and reliability of decentralized learning.
Although Uribe’s work is highly theoretical, the impacts could be far-reaching. In collaboration with partners at Texas Children’s Hospital and Baylor College of Medicine, his team is applying decentralized learning techniques to the challenge of diagnosing congenital heart disease from massive electrocardiogram datasets containing hundreds of millions of data points. In a separate collaboration with Michigan State University, he is exploring the use of decentralized algorithms to process ecological data for conservation efforts, helping to map and understand complex food chains in ecosystems across Africa. Other collaborating partners of the Uribe lab include Google, Rice’s Baker Institute for Public Policy and the Network of Internet & Society Centers at Harvard University.
“This project is about developing the mathematical strategies for effective teamwork in these types of distributed systems,” Uribe said. “The kinds of advances we are working toward could make it possible to process and learn from massive datasets that today seem impossible to handle.”
Beyond research, Uribe’s CAREER Award also supports a robust educational and outreach plan centered on broadening participation in STEM fields. His efforts include offering new undergraduate research experiences, strengthening his graduate course on decentralized learning and mentoring initiatives through partnerships with organizations such as Cientifíco Latino and INFORMS.
“We want to create a strong training pipeline and a supportive community for students from a wide range of backgrounds,” Uribe said.
His broader outreach efforts will include expanding INFORMS en Español, a webinar series on operations research and AI, and continuing the Texas Colloquium on Distributed Learning, or TL;DR, a Rice-hosted workshop that brings together researchers and industry leaders to discuss the latest advances in decentralized systems, distributed computing and large-scale machine learning.
“We have now reached a point where modern engineering systems are no longer composed of single, monolithic machines,” Uribe said. “The way to scale up now and in the future will involve having many computers and components working with each other. This project is about tackling this coordination challenge to enable next-generation performance in decentralized systems.”
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Award information:
Award Abstract # 2443064
CAREER: Enabling Next-Generation Decentralized Learning: Structure, Models, and Methods
About Rice:
Located on a 300-acre forested campus in Houston, Texas, Rice University is consistently ranked among the nation’s top 20 universities by U.S. News & World Report. Rice has highly respected schools of architecture, business, continuing studies, engineering and computing, humanities, music, natural sciences and social sciences and is home to the Baker Institute for Public Policy. Internationally, the university maintains the Rice Global Paris Center, a hub for innovative collaboration, research and inspired teaching located in the heart of Paris. With 4,776 undergraduates and 4,104 graduate students, Rice’s undergraduate student-to-faculty ratio is just under 6-to-1. Its residential college system builds close-knit communities and lifelong friendships, just one reason why Rice is ranked No. 1 for lots of race/class interaction and No. 7 for best-run colleges by the Princeton Review. Rice is also rated as a best value among private universities by the Wall Street Journal and is included on Forbes’ exclusive list of “New Ivies.”