José Mairton Barros da Silva Júnior
Associate senior lecturer/Assistant Professor at Department of Information Technology; Division of Computer Systems
- Telephone:
- +46 18 471 12 27
- E-mail:
- mairton.barros@it.uu.se
- Visiting address:
- Hus 10, Lägerhyddsvägen 1
- Postal address:
- Box 337
751 05 UPPSALA
- ORCID:
- 0000-0002-4503-4242
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Short presentation
Jose Mairton B. da Silva, Jr. is an Assistant Professor in the Division of Computer Systems at Uppsala University in Sweden. My research interests include optimization and learning for future wireless networks, specifically federated learning, vehicular communications, communication efficiency for distributed learning, and full-duplex communications.
Check my Personal Webpage and Google Scholar for more info.
Keywords
- 5g wireless
- distributed machine learning
- distributed optimization
- federated machine learning
- machine learning
- optimization
- wireless communications
- wireless networks and communications
Biography
I am currently an Assistant Professor in the Division of Computer Systems at Uppsala University, Sweden. My current research focuses on optimization and learning for future wireless networks, specifically federated learning, vehicular communications, communication efficiency for distributed learning, and full-duplex communications.
In 2019, I earned a Ph.D. degree in Electrical Engineering and Computer Science from KTH Royal Institute of Technology in Stockholm, Sweden. Prior to that, I earned a BSc (with honors) and an MSc in Telecommunications Engineering from the Federal University of Ceará in 2012 and 2014, respectively. I worked as a research engineer at the Wireless Telecommunication Research Group (GTEL) in Fortaleza from July 2012 to March 2015. During the autumn/winter of 2013-2014, I completed an internship at Ericsson Research in Stockholm, Sweden. In Spring/Fall 2018, I was a visiting researcher at Rice University in Houston, Texas, USA. From 2019 to 2022, I worked as a Postdoctoral Researcher with the KTH Royal Institute of Technology. During 2022 and Spring 2023, I held a Marie Skłodowska-Curie Postdoctoral Fellowship at Princeton University in the Department of Electrical and Computer Engineering, USA, and at KTH Royal Institute of Technology in the Division of Network and Systems Engineering.
From 2018 to 2021, I served as Secretary for the Full-Duplex Wireless Communications Emerging Technologies Initiatives (FD-ETI), created by IEEE Communications Society to promote full-duplex communications. Additionally, I presented several tutorials on "Wireless for Machine Learning" at several flagship conferences sponsored by the IEEE Communications Society, including IEEE ICASSP'21, IEEE PIMRC'21, IEEE GLOBECOM'21, IEEE ICC'22, and IEEE GLOBECOM'22.
Publications
Recent publications
- FedCau (2024)
- A Federated Prototype-Based Model for IoT Systems: A Study Case for Leakage Detection in a Real Water Distribution Network (2024)
- Agent Selection Framework for Federated Learning in Resource-Constrained Wireless Networks (2024)
- ChannelComp (2024)
- SumComp: Coding for Digital Over-the-Air Computation via the Ring of Integers (2024)
All publications
Articles
- FedCau (2024)
- Agent Selection Framework for Federated Learning in Resource-Constrained Wireless Networks (2024)
- ChannelComp (2024)
- SumComp: Coding for Digital Over-the-Air Computation via the Ring of Integers (2024)
- On differential privacy for federated learning in wireless systems with multiple base stations (2024)
- Federated Learning Using Three-Operator ADMM (2023)
- Leakage detection in water distribution networks using machine-learning strategies (2023)