IMDEA Networks
Aristide Tanyi Jong AKEM
PhD Student
- Affiliation: IMDEA Networks Institute, Universidad Carlos III de Madrid (U3CM)
- BSc & MSc: Telecommunications Engineering - University of Yaounde I. Yaounde, Cameroon
- MSc: Electrical and Computer Engineering - Carnegie Mellon University Africa. Kigali, Rwanda
- Former position: Graduate Teaching Assistant, Carnegie Mellon University Africa, Kigali, Rwanda
- Joining date: March 2021
- Email: aristide.akem@imdea.org
- Phone: +34 91 481 6948
Biography
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 the data-driven management of networks.
Publications
Fast Detection of Cyberattacks on the Metaverse through User-plane Inference
Beyza Bütün, Aristide Tanyi Jong Akem, Michele Gucciardo, Marco Fiore
International Conference on Metaverse Computing, Networking and Applications. Kyoto, Japan. June 2023
Showcasing In-Switch Machine Learning Inference (Demo)
Aristide Tanyi Jong Akem, Beyza Bütün, Michele Gucciardo, Marco Fiore
IEEE International Conference on Network Softwarization. Madrid, Spain. June 2023
Demonstrating Flow-Level In-Switch Inference (Demo)
Michele Gucciardo, Aristide Tanyi Jong Akem, Beyza Bütün, Marco Fiore
IEEE International Conference on Computer Communications. New York, United States. May 2023
Flowrest: Practical Flow-Level Inference in Programmable Switches with Random Forests
Aristide Tanyi Jong Akem, Michele Gucciardo, Marco Fiore
IEEE International Conference on Computer Communications. New York, United States. May 2023
Henna: hierarchical machine learning inference in programmable switches
Aristide Tanyi Jong Akem, Beyza Bütün, Michele Gucciardo, Marco Fiore
International Workshop on Native Network Intelligence. Rome, Italy. December 2022
Previous publications
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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