Gabriel Campero Durand

M.Sc. Gabriel Campero Durand

Fakultät Informatik
AG Datenbanken & Software Engineering
Universitätsplatz 2, 39106, Magdeburg, Gebäude 29, Raum 125

M.Sc. Gabriel Campero Durand

Fakultät Informatik
AG Datenbanken & Software Engineering
Universitätsplatz 2, 39106, Magdeburg, G29-125
Vita
Projekte

Aktuelle Projekte

Publikationen

 

Forschung
  • HTAP and Evolutionary Data Systems: Benchmarking HTAP goals, Self-Tuning/Evolutionary Features, Deep Learning Components for Tuning Databases, Exploiting Novel Hardware/Heterogeneous HTAP (with a focus on GPUs), Adaptive Storage Models, Data Partitioning, Transaction Processing, Flexible/Probabilistic Index Structures, Approximate Query Processing, Code Generation, DSLs, Support for Data Science/Machine Learning Workloads, Larger Than Memory Data Management, Optimization for Shared Queries
  • Graph Databases: Graph Query Languages, Query Processing and Optimization, Data Modeling, Data Structures, Search Engine Processing, Data Loading, Static/Dynamic Network Analysis
  • Multi-Model Databases: Supporting Non-Relational Models as Materialized Views in a RDBMS, Alternative Approaches for Primary Storage (Key-value Stores, Object Stores), Adaptive Schemas, Machine-Learning-supported Data Integration, Raw Query Processing
  • Cloud Workloads: Container Management, Tracing and Profiling of Large Scale Systems, Analysis of Performance Data, Hardware-Sensitivity for Cloud Applications, Verification of Distributed Systems with Fault Injection
  • Others: Large Scale Machine Learning, Sign-Language Translation, Big Code, Voice Interfaces for Data Systems, Speculative Parallelism, Intelligent Personal Assistants
Vita
Projects

Aktuelle Projekte

Publications

 

Research
  • HTAP and Evolutionary Data Systems: Benchmarking HTAP goals, Self-Tuning/Evolutionary Features, Deep Learning Components for Tuning Databases, Exploiting Novel Hardware/Heterogeneous HTAP (with a focus on GPUs), Adaptive Storage Models, Data Partitioning, Transaction Processing, Flexible/Probabilistic Index Structures, Approximate Query Processing, Code Generation, DSLs, Support for Data Science/Machine Learning Workloads, Larger Than Memory Data Management, Optimization for Shared Queries
  • Graph Databases: Graph Query Languages, Query Processing and Optimization, Data Modeling, Data Structures, Search Engine Processing, Data Loading, Static/Dynamic Network Analysis
  • Multi-Model Databases: Supporting Non-Relational Models as Materialized Views in a RDBMS, Alternative Approaches for Primary Storage (Key-value Stores, Object Stores), Adaptive Schemas, Machine-Learning-supported Data Integration, Raw Query Processing
  • Cloud Workloads: Container Management, Tracing and Profiling of Large Scale Systems, Analysis of Performance Data, Hardware-Sensitivity for Cloud Applications, Verification of Distributed Systems with Fault Injection
  • Others: Large Scale Machine Learning, Sign-Language Translation, Big Code, Voice Interfaces for Data Systems, Speculative Parallelism, Intelligent Personal Assistants

Letzte Änderung: 27.10.2017 - Ansprechpartner:

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