| CogNet: A network management architecture featuring cognitive capabilities L Xu, H Assem, IGB Yahia, TS Buda, A Martin, D Gallico, M Biancani, ... 2016 European Conference on Networks and Communications (EuCNC), 325-329, 2016 | 23 | 2016 |
| Can machine learning aid in delivering new use cases and scenarios in 5G? TS Buda, H Assem, L Xu, D Raz, U Margolin, E Rosensweig, DR Lopez, ... NOMS 2016-2016 IEEE/IFIP Network Operations and Management Symposium, 1279-1284, 2016 | 20 | 2016 |
| Wireless ion-selective electrode autonomous sensing system C Fay, S Anastasova, C Slater, ST Buda, R Shepherd, B Corcoran, ... IEEE Sensors Journal 11 (10), 2374-2382, 2011 | 20 | 2011 |
| View on 5g architecture S Redana, A Kaloxylos, A Galis, P Rost, V Jungnickel White paper of the 5G-PPP architecture WG, 2016 | 18 | 2016 |
| Spatio-temporal clustering approach for detecting functional regions in cities H Assem, L Xu, TS Buda, D O'Sullivan 2016 IEEE 28th international conference on tools with artificial …, 2016 | 17 | 2016 |
| ReX: Extrapolating relational data in a representative way TS Buda, T Cerqueus, J Murphy, M Kristiansen British International Conference on Databases, 95-107, 2015 | 13 | 2015 |
| Deepad: A generic framework based on deep learning for time series anomaly detection TS Buda, B Caglayan, H Assem Pacific-Asia Conference on Knowledge Discovery and Data Mining, 577-588, 2018 | 9 | 2018 |
| Machine learning as a service for enabling Internet of Things and People H Assem, L Xu, TS Buda, D O’Sullivan Personal and Ubiquitous Computing 20 (6), 899-914, 2016 | 9 | 2016 |
| Towards a better replica management for hadoop distributed file system HE Ciritoglu, T Saber, TS Buda, J Murphy, C Thorpe 2018 IEEE International Congress on Big Data (BigData Congress), 104-111, 2018 | 6 | 2018 |
| Investigation of replication factor for performance enhancement in the hadoop distributed file system HE Ciritoglu, L Batista de Almeida, E Cunha de Almeida, TS Buda, ... Companion of the 2018 ACM/SPEC International Conference on Performance …, 2018 | 6 | 2018 |
| VFDS: Very fast database sampling system TS Buda, T Cerqueus, J Murphy, M Kristiansen 2013 IEEE 14th International Conference on Information Reuse & Integration …, 2013 | 6 | 2013 |
| VFDS: An application to generate fast sample databases TS Buda, T Cerqueus, J Murphy, M Kristiansen Proceedings of the 23rd ACM International Conference on Conference on …, 2014 | 5 | 2014 |
| RCMC: recognizing crowd-mobility patterns in cities based on location based social networks data H Assem, TS Buda, D O’sullivan ACM Transactions on Intelligent Systems and Technology (TIST) 8 (5), 1-30, 2017 | 4 | 2017 |
| CoDS: A representative sampling method for relational databases TS Buda, T Cerqueus, J Murphy, M Kristiansen International Conference on Database and Expert Systems Applications, 342-356, 2013 | 4 | 2013 |
| Towards realistic sampling: generating dependencies in a relational database TS Buda, J Murphy, M Kristiansen Proceedings of the 7th International Conference on Ubiquitous Information …, 2013 | 4 | 2013 |
| ReX: Representative extrapolating relational databases TS Buda, T Cerqueus, C Grava, J Murphy Information Systems 67, 83-99, 2017 | 3 | 2017 |
| ADE: An ensemble approach for early Anomaly Detection TS Buda, H Assem, L Xu 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM …, 2017 | 3 | 2017 |
| Generation of test databases using sampling methods TS Buda Proceedings of the 2013 International Symposium on Software Testing and …, 2013 | 3 | 2013 |
| St-dennetfus: A new deep learning approach for network demand prediction H Assem, B Caglayan, TS Buda, D O’Sullivan Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018 | 2 | 2018 |
| Representative sampling of relational data TS Buda, MK Kristiansen, N Venkatraman US Patent App. 14/132,058, 2015 | 2 | 2015 |
Haytham AssemChief Scientist, Huawei ResearchVerified email at ucd.ie
