- PhD in Computer Science and Engineering, University of South Florida, USA
- MSc in Computer Science, University of South Florida, USA
- MEng in Electrical and Computer Engineering, National Technical University of Athens, Greece
Nicolas Kourtellis is Head of the Systems AI Lab (SAIL) and Co-Director of Telefonica Research, a 25+ researcher team based in Barcelona, Spain. He holds a PhD in Computer Science & Engineering from the University of South Florida, USA (2012), a MSc in Computer Science from the University of South Florida (2008), and a Meng in Electrical and Computer Engineering from the National Technical University of Athens, Greece (2006).He has over 90 published peer-reviewed papers and 8 filed patents. Currently, he focuses on privacy-preserving AI and federated learning on the edge, modeling/detecting with AI user online privacy leaks, as well as inappropriate/fraudulent behavior on social media. He executed several research visits in ANL (USA), INRIA (France), Yahoo (Spain/USA), UCL (UK), CUT (Cyprus), AUTH (Greece), FORTH (Greece), and others. He has served in many technical committees of top conferences and journals, and presented his work in top academic and industrial venues including Mobile World Congress 2021 and 2023, Apache Foundation, etc. His work has been covered by major news outlets such as Nature, New York Times, The Atlantic, New Scientist, Washington Post, Wired, and others. In 2022, he was ranked among the World’s Top 2% Scientists (2021) in the list prepared by Elsevier BV, Stanford University, USA.
- C. Sandeepa, B. Siniarski, N. Kourtellis, S. Wang, M. Liyanage. A Survey on Privacy of Personal and Non-Personal Data in B5G/6G Networks. ACM Surveys, 2024.
- P. Leonidou, N. Kourtellis, N. Salamanos, M. Sirivianos. Privacy-Preserving Online Content Moderation with Federated Learning ACM CySoc, Collocated with WebConference (WWW), 2023.
- C. Sandeepa, B. Siniarski, N. Kourtellis, S. Wang, M. Liyanage. A survey on privacy for B5G/6G: New privacy challenges, and research directions. Elsevier Journal of Industrial Information Integration, 2022.
- F. Mo, H. Haddadi, K. Katevas, E. Marin, D. Perino, N. Kourtellis. PPFL: Enhancing Privacy in Federated Learning with Confidential Computing. ACM GetMobile: Mobile Computing and Communications, 25(44), 2022.
- D. Perino, K. Katevas, A. Lutu, E. Marin, N. Kourtellis. Privacy-preserving AI for future networks. Communications of the ACM, 65(4), 2022.
- D. Katare, N. Kourtellis, S. Park, D. Perino, M. Janssen, A.Y. Ding. Bias Detection and Generalization in AI Algorithms on Edge for Autonomous Driving. IEEE/ACM 7th Symposium on Edge Computing (SEC), 2022.
- K. Katevas, D. Perino, N. Kourtellis. FLaaS: Enabling Practical Federated Learning on Mobile Environments. ACM MobiSys, 2022
- F. Mo, H. Haddadi, K. Katevas, E. Marin, D. Perino, N. Kourtellis. Privacy-preserving Federated Learning with Trusted Execution Environments. ACM MobiSys, 2021. Best Paper Award.
Find the full list of Kourtellis’ publications here.
Selected Speaking Engagements:
- Powering the Next Gen Networks with Privacy-Preserving AI (Keynote, EdgeSys, Athens, Greece, 2024)
- Powering the Next Generation Networks with Privacy-Preserving Artificial Intelligence (Keynote, IFIP TC6, Barcelona, Spain, 2023)
- Privacy-Preserving AI for Future 5/6G Networks (Talk, Mobile World Congress, Barcelona, 2023)
- Will it be Privacy or Utility? Can I have both (with Privacy-Preserving ML) please? (Keynote, EMDL Workshop at ACM MobiSys, Portland, 2022)
- European Data Strategy from the IoT Market Perspective (Panel, AIOTI Signature Event, Online, 2021)
- Solving the Privacy-by-Design AI conundrum with Privacy-Preserving ML (Talk, Mobile World Congress, Barcelona, 2021)
Selected Press Coverage:
- “How will 6G change the world? This is what experts at Mobile World Congress think,” EuroNews (February 28, 2023)
- “Un servicio basado en IA permite detectar noticias falsas,” BlogThingBig (2022)
- “Building Machine Learning Models with Privacy by Design in Mind,” ConcordiaBlog (2020)
- “Conservative News Sites Track You Lots More Than Left-Leaning Ones,” Wired (February 11, 2020)
- “Algorithms Won’t Fix What’s Wrong With YouTube,” New York Times (June 14, 2019)
