Mateo Diaz

Mateo Diaz is an Assistant Professor in the Department of Applied Mathematics and Statistics at Johns Hopkins University with a secondary appointment in the Department of Computer Science, and is affiliated with both the Data Science and AI Institute and the Mathematical Institute for Data Science.

His educational background includes:

• PhD in Applied Mathematics from Cornell University
• MSc in Mathematics from Universidad de los Andes
• BS in Mathematics from Universidad de los Andes
• BS in Systems and Computing Engineering from Universidad de los Andes

Diaz's research centers on the interplay between optimization, geometry, and statistics, developing highly effective large-scale algorithms for data science, machine learning, and signal processing applications. His work addresses complex challenges in healthcare, energy, and finance through scalable computational methods.

His notable scientific awards include:

• NSF CAREER Award (2025) for advancing optimization tools in data science
• Beale-Orchard-Hays Prize (2024) for groundbreaking work in Primal-Dual Linear Programming

Diaz actively mentors graduate students:

• Pedro Izquierdo Lehmann (PhD candidate, 2023-)
• Abdel Ghani Labassi (PhD candidate, 2024-)
• Daniel Lopez-Castaño (PhD candidate, co-advised with Soledad Villar, 2024-)
• Jonas Elmerraji (DEng candidate, co-advised with James C. Spall, 2024-)
• Shengtai Yao (MSE candidate, 2025-)
• Haoruo Zhang (Research Fellow, 2024-)

Recent alumni include Fengsheng Lin (Master's, 2025) and Yun You (Master's, 2024). His research is primarily funded by the NSF CAREER grant.

He co-organizes the Statistics and Data Science Workshop in Colombia and maintains active collaborations through Johns Hopkins' data science institutes.