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Dr. Miguel Mosteiro, Associate Professor at the Seidenberg School of Computer Science and Information Systems, successfully presented two of his experimental research papers at the 2024 conference.

This selective and high-level conference aims to bring together researchers and engineers from the theory and practice of distributed and networked systems. The program committee includes many scholars who are ranked top of the field in distributed computing worldwide.

When talking about his presentations at the conference, Dr. Mosteiro said that he was “particularly proud because both papers are coauthored by some of my students, and the topic of both papers is exciting for different reasons, which is reflected in the interest shown by the reviewers. Both works triggered interest and were followed up by great questions that leave room for further development of the projects.”

The first paper, titled "Distributed Station Assignment through Learning", was co-written by Dr. Mosteiro, Lu Dong, and Michelle Wang, both of whom are ������� PhD students. Their work is an experimental study of a scheduling problem called Station Assignment, where mobile users of a wireless network need to upload data to static base stations, while minimizing energy consumption in various aspects. This was done by applying machine learning approaches developed by OpenAI, which are at the forefront of AI research.

"Privacy Preserving Vehicular Adhoc Network Computations: A NYC Taxi Trips Evaluation", the second paper presented at the NETYS conference, is an experimental study of algebraic computations in vehicular networks which was carried out on data extracted from a huge public database of New York City taxi trips. This work was co-authored by Dr. Mosteiro, Austin Powlette (undergraduate Seidenberg student), and Dariusz R. Kowalski (external colleague from Augusta University).

Congratulations to Dr. Mosteiro, as well as his students and collaborators, on this fantastic achievement!