|
Size: 117
Comment:
|
Size: 3066
Comment:
|
| Deletions are marked like this. | Additions are marked like this. |
| Line 1: | Line 1: |
| #acl EditorsGroup:read,write,delete,revert,admin All:read | = Research Center in Computer Science = The center groups researchers and PhD students working in one of the following directions: |
| Line 3: | Line 4: |
| = Research Center in Informatics = | === Cloud Computing, High Performance Computing, and Internet of Things === * Exascale Data Processing * Monitoring data-intensive applications * Portability in Clouds and open source Platform as a Service * Cloud resources management and self-organization in heterogeneous cloud * Data-intensive applications * Ontologies for Cloud services * Cloud governance * HPC service exposure in the Cloud * Empirical software engineering for cloud-based applications === Big Data Applications and Data Analysis === |
| Line 5: | Line 17: |
| ... | * Accelerating applications on clouds and HPC * Graph processing * Astronomy image processing and object detection * Satellite-based image processing * Smart grids |
| Line 7: | Line 23: |
| InfraGrid | * Hybrid processing on clouds, IoT, and HPC * Mixing GPUCPU, edge devices, and clouds for optimizing execution of large scale distributed applications * Scheduling algorithms for distributed systems * Optimal and suboptimal heuristics with energy, cost and execution constraints === Artificial Intelligence and Machine Learning === * Multi-agent approaches and recommender systems: * health monitoring and healthcare systems * customer-relationship management * Machine learning techniques for: * knowledge extraction from data (medical, biological, financial) * intrusion and anomaly detection * prediction for auto-scaling of resources in distributed systems * Metaheuristic algorithms for: * scalable cloud resource allocation * model inference and parameter estimation in biological systems * Explainable Artificial Intelligence * Signal and image processing using deep neural networks ([[http://staff.fmi.uvt.ro/~darian.onchis/simtresearch.html|Group - Signal, Image and Machine Learning]]) * Uncertainty in deep neural networks === Applications of Machine Learning in Earth Observation === ([[https://sage.ieat.ro/|EO+ML Research Group]]) * Application of advanced computational techniques for Earth Observation problems * Big Data Processing platforms (processing of massive Earth observation data) * Machine Learning algorithms in Remote Sensing === Theory of Computing === ([[http://tcs.ieat.ro/|TCS Research Group]]) * Algorithms and Computational Complexity * Agent-based models, game theory and complex networks * Symbolic computation * Unification and matching * Constraint logic programming * Proof-based algorithm synthesis === Computational and Applied Mathematics === * Qualitative and quantitative aspects of Dynamical Systems (time-delayed systems, impulsive systems, fractional-order systems) * Simulation of fractional-order systems using HPC * Analysis of nonlinear and chaotic phenomena in: fractional-order neural networks models, complex-valued neural networks * Applications of the theory of dynamical systems to: medicine, neuroscience, aerodynamics, economy |
Research Center in Computer Science
The center groups researchers and PhD students working in one of the following directions:
Cloud Computing, High Performance Computing, and Internet of Things
- Exascale Data Processing
- Monitoring data-intensive applications
- Portability in Clouds and open source Platform as a Service
- Cloud resources management and self-organization in heterogeneous cloud
- Data-intensive applications
- Ontologies for Cloud services
- Cloud governance
- HPC service exposure in the Cloud
- Empirical software engineering for cloud-based applications
Big Data Applications and Data Analysis
- Accelerating applications on clouds and HPC
- Graph processing
- Astronomy image processing and object detection
- Satellite-based image processing
- Smart grids
- Hybrid processing on clouds, IoT, and HPC
- Mixing GPUCPU, edge devices, and clouds for optimizing execution of large scale distributed applications
- Scheduling algorithms for distributed systems
- Optimal and suboptimal heuristics with energy, cost and execution constraints
Artificial Intelligence and Machine Learning
- Multi-agent approaches and recommender systems:
- health monitoring and healthcare systems
- customer-relationship management
- Machine learning techniques for:
- knowledge extraction from data (medical, biological, financial)
- intrusion and anomaly detection
- prediction for auto-scaling of resources in distributed systems
- Metaheuristic algorithms for:
- scalable cloud resource allocation
- model inference and parameter estimation in biological systems
- Explainable Artificial Intelligence
Signal and image processing using deep neural networks (Group - Signal, Image and Machine Learning)
- Uncertainty in deep neural networks
Applications of Machine Learning in Earth Observation
- Application of advanced computational techniques for Earth Observation problems
- Big Data Processing platforms (processing of massive Earth observation data)
- Machine Learning algorithms in Remote Sensing
Theory of Computing
- Algorithms and Computational Complexity
- Agent-based models, game theory and complex networks
- Symbolic computation
- Unification and matching
- Constraint logic programming
- Proof-based algorithm synthesis
Computational and Applied Mathematics
- Qualitative and quantitative aspects of Dynamical Systems (time-delayed systems, impulsive systems, fractional-order systems)
- Simulation of fractional-order systems using HPC
- Analysis of nonlinear and chaotic phenomena in: fractional-order neural networks models, complex-valued neural networks
- Applications of the theory of dynamical systems to: medicine, neuroscience, aerodynamics, economy