| PPFL: privacy-preserving federated learning with trusted execution environments F Mo, H Haddadi, K Katevas, E Marin, D Perino, N Kourtellis MobiSys '21: Proceedings of the 19th Annual International Conference on …, 2021 | 380 | 2021 |
| DarkneTZ: towards model privacy at the edge using trusted execution environments F Mo, AS Shamsabadi, K Katevas, S Demetriou, I Leontiadis, A Cavallaro, ... MobiSys '20: Proceedings of the 18th International Conference on Mobile …, 2020 | 278 | 2020 |
| Machine Learning with Confidential Computing: A Systematization of Knowledge F Mo, Z Tarkhani, H Haddadi ACM Computing Surveys, 2022 | 60* | 2022 |
| Efficient and private federated learning using TEE F Mo, H Haddadi Proc. EuroSys Conf., Dresden, Germany, 2019 | 58 | 2019 |
| Towards battery-free machine learning and inference in underwater environments Y Zhao, SS Afzal, W Akbar, O Rodriguez, F Mo, D Boyle, F Adib, ... Proceedings of the 23rd Annual International Workshop on Mobile Computing …, 2022 | 45 | 2022 |
| Layer-wise characterization of latent information leakage in federated learning F Mo, A Borovykh, M Malekzadeh, H Haddadi, S Demetriou arXiv preprint arXiv:2010.08762, 2020 | 40 | 2020 |
| Usage patterns and social circles on Facebook among elderly people with diverse personality traits F Mo, J Zhou, M Kosinski, D Stillwell Educational Gerontology 44 (4), 265-275, 2018 | 36 | 2018 |
| Investigation of Chinese students' O2O shopping through multiple devices J Huang, J Zhou, G Liao, F Mo, H Wang Computers in Human Behavior 75, 58-69, 2017 | 36 | 2017 |
| Mitigating hallucinations in large language models via self-refinement-enhanced knowledge retrieval M Niu, H Li, J Shi, H Haddadi, F Mo arXiv preprint arXiv:2405.06545, 2024 | 27 | 2024 |
| Quantifying and Localizing Private Information Leakage from Neural Network Gradients F Mo, A Borovykh, M Malekzadeh, H Haddadi, S Demetriou arXiv preprint arXiv:2105.13929, 2021 | 18* | 2021 |
| Ppfl: Enhancing privacy in federated learning with confidential computing F Mo, H Haddadi, K Katevas, E Marin, D Perino, N Kourtellis GetMobile: Mobile Computing and Communications 25 (4), 35-38, 2022 | 17 | 2022 |
| Adapting the navigation interface of smart watches to user movements F Mo, J Zhou, S Yi International Journal of Human–Computer Interaction 33 (6), 460-474, 2017 | 15 | 2017 |
| Statistical analysis of surface texture performance with provisions with uncertainty in texture dimensions F Mo, C Shen, J Zhou, MM Khonsari IEEE Access 5, 5388-5398, 2017 | 15 | 2017 |
| Towards characterizing and limiting information exposure in DNN layers F Mo, AS Shamsabadi, K Katevas, A Cavallaro, H Haddadi arXiv preprint arXiv:1907.06034, 2019 | 14* | 2019 |
| Statistical analysis of the influence of imperfect texture shape and dimensional uncertainty on surface texture performance F Mo, C Shen, J Zhou, MM Khonsari IEEE Access 5, 27023-27035, 2017 | 14 | 2017 |
| Private delegated computations using strong isolation M Brossard, G Bryant, B El Gaabouri, X Fan, A Ferreira, EG Evans, ... IEEE Transactions on Emerging Topics in Computing 12 (1), 386-398, 2023 | 13 | 2023 |
| Effect of icon amount and visual density on usability of smartwatches F Mo, S Yi, J Zhou International Conference on Human Aspects of IT for the Aged Population, 466-477, 2016 | 10 | 2016 |
| How to enhance intergenerational communication? The influence of family orientation and generation when using social robots as an intermediary F Mo, J Zhou, S Yi International conference on human aspects of IT for the aged population, 348-359, 2017 | 9 | 2017 |
| Adapting smartwatch interfaces to hand gestures during movements: offset models and the C-shaped pattern of tapping F Mo, J Zhou Journal of Ambient Intelligence and Humanized Computing 12 (7), 8099-8117, 2021 | 7 | 2021 |
| Centaur: Federated learning for constrained edge devices F Mo, M Malekzadeh, S Chatterjee, F Kawsar, A Mathur arXiv preprint, 2022 | 6* | 2022 |
Hamed HaddadiImperial College London / Brave SoftwareVerified email at imperial.ac.uk
