| DICE: quality-driven development of data-intensive cloud applications G Casale, D Ardagna, M Artac, F Barbier, E Di Nitto, A Henry, G Iuhasz, ... 2015 IEEE/ACM 7th International Workshop on Modeling in Software Engineering …, 2015 | 66 | 2015 |
| An overview of monitoring tools for big data and cloud applications G Iuhasz, I Dragan Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2015 17th …, 2015 | 18 | 2015 |
| Neural network predictions of stock price fluctuations G Iuhasz, M Tirea, V Negru 2012 14th International Symposium on Symbolic and Numeric Algorithms for …, 2012 | 17 | 2012 |
| Neuroevolution based multi-agent system for micromanagement in real-time strategy games I Gabriel, V Negru, D Zaharie Proceedings of the fifth balkan conference in informatics, 32-39, 2012 | 17 | 2012 |
| Tuning logstash garbage collection for high throughput in a monitoring platform DN Doan, G Iuhasz 2016 18th International Symposium on Symbolic and Numeric Algorithms for …, 2016 | 11 | 2016 |
| Support services for applications execution in multi-clouds environments D Pop, G Iuhasz, C Craciun, S Panica 2016 IEEE International Conference on Autonomic Computing (ICAC), 343-348, 2016 | 10 | 2016 |
| Applying self-* principles in heterogeneous cloud environments I Drăgan, TF Fortiş, G Iuhasz, M Neagul, D Petcu Cloud Computing, 255-274, 2017 | 8 | 2017 |
| Architecture of a scalable platform for monitoring multiple big data frameworks G Iuhasz, D Pop, I Dragan Scalable Computing: Practice and Experience 17 (4), 313-321, 2016 | 8 | 2016 |
| Neuroevolution based multi-agent system with ontology based template creation for micromanagement in real-time strategy games I Gabriel, V Negru, D Zaharie Information Technology and Control 43 (1), 98-109, 2014 | 7 | 2014 |
| Data mining considerations for knowledge acquisition in real time strategy games G Iuhasz, VI Munteanu, V Negru 2013 IEEE 11th International Symposium on Intelligent Systems and …, 2013 | 7 | 2013 |
| On processing extreme data D Petcu, G Iuhasz, D Pop, D Talia, J Carretero, R Prodan, T Fahringer, ... Scalable Computing. Practice and Experience 16 (4), 467-489, 2016 | 4 | 2016 |
| Overview of machine learning tools and libraries D Pop, G Iuhasz Inst. e-Austria Timisoara, 0 | 4 | |
| Distributed platforms and cloud services: Enabling machine learning for big data D Pop, G Iuhasz, D Petcu Data Science and Big Data Computing, 139-159, 2016 | 3 | 2016 |
| Run-time adaptation policies G Casale, F Kalo, JF Pérez, W Wang, D Ardagna, M Ciavotta, G Iuhasz MODAClouds EU Project Deliverable, 2014 | 3 | 2014 |
| A scalable platform for monitoring data intensive applications I Drăgan, G Iuhasz, D Petcu Journal of Grid Computing 17 (3), 503-528, 2019 | 2 | 2019 |
| Load balancing for multi-cloud G Iuhasz, P Jamshidi, W Wang, G Casale Model-Driven Development and Operation of Multi-Cloud Applications, 53-58, 2017 | 2 | 2017 |
| Monitoring of Exascale data processing G Iuhasz, D Petcu 2019 IEEE International Conference on Advanced Scientific Computing (ICASC), 1-5, 2019 | 1 | 2019 |
| Perspectives on anomaly and event detection in exascale systems G Iuhasz, D Petcu 2019 IEEE 5th Intl Conference on Big Data Security on Cloud (BigDataSecurity …, 2019 | 1 | 2019 |
| An Architecture for a Management Agency for Cloud Resources M Erascu, G Iuhasz, F Micota 2018 20th International Symposium on Symbolic and Numeric Algorithms for …, 2018 | 1 | 2018 |
| Runtime environment final release G Iuhasz, S Panica, G Casale, W Wang Modaclouds Deliverable D 6, 2015 | 1 | 2015 |
Dana PetcuProf. West University of Timisoara; Researcher Institute e-Austria TimisoaraE-mail confirmado em e-uvt.ro
