Alex Gittens
About
I am an associate professor of computer science at Rensselaer Polytechnic Institute. My research focuses on designing algorithms with provable performance guarantees, with an emphasis on tensor factorization, trustworthy machine learning, and randomized numerical linear algebra for large-scale machine learning applications. I have advanced scalable methods for tensor decomposition, developed robust techniques for scalable and fair machine learning, and explored randomized algorithms to optimize computational and communication efficiency in data-intensive and distributed problems. My work has been published in top-tier venues and applied across domains, from scientific computing to real-world machine learning systems. Before joining RPI, I earned my PhD in applied and computational mathematics from CalTech and held research positions at eBay, the International Computer Science Institute, and UC Berkeley’s AMPLab.
Research Performance Summary
First Recorded Paper
Synthesis, structure and characterization of two new antimony oxides–LaSb 3 O 9 and LaSb 5 O 12: Formation of LaSb 5 O 12 from the reaction of LaSb 3 O 9 with Sb 2 O 3
Year: 2004
Citations: 23
Venue: Journal of Materials Chemistry 14 (1)
Latest Recorded Paper
Utility-privacy tradeoff in federated learning
Year: 2025
Citations: 0
Venue: Federated Learning for Medical Imaging
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.