I am a network researcher and engineer with research experience in (a) applied machine learning to wireless networks, (b) network planning for ultra-reliable low-latency communication (URLLC) services, and, more recently, (c) applied reconfigurable intelligent surfaces (RIS) to cybersecurity; and with industry experience in technical support engineering (tiers 1-3) and mobile network data processing.
Key technical skills: Python, Linux, Bash scripting, networking, software-defined radios (USRP/Gnu radio), and applied machine learning to networking.
Education:
Ph.D. in computer engineering (2019-present)
Virginia Tech, US
Trinity College Dublin, Ireland (2019-2021, degree transferred to Virginia Tech)
Advisors: Prof. Luiz DaSilva and Prof. Jacek KibiłdaMS in computer science (2017-2019)
Universidade Federal de Minas Gerais, Brazil
Advisors: Prof. Daniel F. Macedo and Prof. Luiz Filipe M. VieiraBS in telecommunications engineering (2011-2016)
Universidade Federal de São João del-Rei, Brazil
The University of Adelaide (2014-2015, visiting student)
Professional experience:
Graduate research assistant (2019-present)
Commonwealth Cyber Initiative, US (2021-present)
CONNECT Centre, Ireland (2019-2021)
My research focuses on realizing ultra-reliable low-latency communication (URLLC) in the next generation of mobile networks, addressing network planning and resource dimensioning and allocation. To that end, I conducted research using real-world data analysis, system-level simulations, and stochastic process modeling. More recently, I've also studied the impact of reconfigurable intelligent surfaces (RISs) on mobile network security. The most relevant technical skills: Reliability engineering, Python, and machine learning.Graduate research assistant (2017-2019)
Winet research Lab., Belo Horizonte, Brazil
My research focused on applying machine learning to optimize the data-link layer of wireless networks using software-defined radios (SDRs). The most relevant technical skills: Python, C/C++, machine learning, and Gnu radio.Technical support engineer (2015-2017)
Bwtech, Belo Horizonte, Brazil
My work consisted of collecting and processing data from multi-vendor (e.g., Nokia, Huawei, and Ericsson) operations support systems (OSS) of several mobile network operators worldwide; assisting NetChart users; troubleshooting lack of data and OSS-related problems; and lastly, coordinating the activities of the support engineering team. The most relevant technical skills: Linux, Bash scripting, MySQL, and .NET.
Featured publications:
(co-author) J. Kibiłda et al., "Reconfigurable intelligent surfaces: The new frontier of next G security," available on arXiv, 2022. (Under review). [PDF].
A. Gomes, J. Kibiłda, Nicola Marchetti, and L. A. Da Silva, "Dimensioning spectrum to support ultra-reliable low-latency communication," IEEE Communications Standards Magazine, vol. 7, no. 1, pp. 88-93, 2023. [DOI] [PDF]
A. Gomes, J. Kibiłda, and L. A. Da Silva, "Capturing rare network conditions to dimension resources for ultra-reliable communication," IEEE Communications Letters, vol. 26, no. 11, pp. 2789-2793, 2022. [DOI] [PDF]
A. Gomes, J. Kibiłda, A. Farhang, R. Farrell, and L. A. DaSilva, "Multi-operator connectivity sharing for reliable networks: A data-driven risk analysis," IEEE Transactions on Network and Service Management, vol. 18, no. 3, pp. 2800–2811, 2021. [DOI] [PDF]
A. Gomes, J. Kibiłda, A. Farhang, R. Farrell, and L. A. DaSilva, “Network sharing for reliable networks: A data-driven study,” in IEEE International Conference on Communications (ICC), 2020, pp. 1–6. [DOI] [PDF]
A. Gomes, D. F. Macedo, and L. F. M. Vieira, "Automatic MAC protocol selection in wireless networks based on reinforcement learning," Computer Communications, vol. 149, pp. 312–323, 2020. [DOI] [PDF]