IMDEA Networks
Aristide Tanyi Jong AKEM
Estudiante de doctorado
- Afiliación: IMDEA Networks Institute, Universidad Carlos III de Madrid
- BSc & MSc: Telecommunications Engineering - University of Yaounde I. Yaounde, Cameroon
- MSc: Electrical and Computer Engineering - Carnegie Mellon University Africa. Kigali, Rwanda
- Puesto anterior: Graduate Teaching Assistant, Carnegie Mellon University Africa, Kigali, Rwanda
- Fecha de incorporación: Marzo 2021
- Website: https://akemaristide.github.io/
- Email: aristide.akem@imdea.org
- Tel: +34 91 481 6948
Biografía
Akem hails from Cameroon in Central Africa. Prior to his master’s studies, he worked as intelligent video surveillance and optical fibre transmission engineer at Huawei Technologies Company Cameroon Ltd. Before joining IMDEA Networks, he was a Graduate Teaching Assistant at Carnegie Mellon University Africa where he had previously studied network technologies and applied machine learning. His research focuses on user-plane inference in programmable networks.
Publicaciones
Ultra-Low Latency User-Plane Cyberattack Detection in SDN-based Smart Grids
Aristide Tanyi Jong Akem, Michele Gucciardo, Marco Fiore
ACM International Conference on Future and Sustainable Energy Systems. Singapore, Singapore. Junio 2024
Jewel: Resource-Efficient Joint Packet and Flow Level Inference in Programmable Switches
Aristide Tanyi Jong Akem, Beyza Bütün, Michele Gucciardo, Marco Fiore
IEEE International Conference on Computer Communications. Vancouver, Canada. Mayo 2024
Evaluating the Impact of Flow Length on the Performance of In-Switch Inference Solutions
Michele Gucciardo, Beyza Bütün, Aristide Tanyi Jong Akem, Marco Fiore
IEEE International Conference on Computer Communications. Vancouver, Canada. Mayo 2024
Towards Data-Driven Management of Mobile Networks through User Plane Inference
Aristide Tanyi Jong Akem, Marco Fiore
IEEE Network Operations and Management Symposium. Seoul, South Korea. Mayo 2024
Encrypted Traffic Classification at Line Rate in Programmable Switches with Machine Learning
Aristide Tanyi Jong Akem, Guillaume Fraysse, Marco Fiore
IEEE/IFIP Network Operations and Management Symposium. Seoul, South Korea. Mayo 2024
Publicaciones previas
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A Machine Learning Approach to Temporal Traffic-Aware Energy-Efficient Cellular Networkscall_made
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2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), ONLINE, Fomerly New York, NY, USA, 28-31 Oct. 2020