基本信息
浏览量:151
职业迁徙
个人简介
My main research interests are summarized as follows:
Big Data Management
data storage/replication/movement, analytics workflows, execution optimization, deployment optimization, computation-intensive queries, scientific data management, integration and handling of intermediate results, consolidation of heterogeneous data sources, data navigation, query calibration, workflow recalibration techniques, deployment on hybrid infrastructures, time-series data management
Big Data Analytics
business and scientific analytics, creation and support of analytics applications: on web data, sensor data, cell data, time-series data, combinations of unstructured and structured data, support of analytics for users of variable expertise, approximate querying, dynamic and agile schema mappings, dynamic and agile data integration and analysis, large data graphs, exploration and visualization, community detection, conversational data analysis
Machine Learning
large-scale resource management based on machine learning techniques, adaptations of reinforcement learning techniques, employment of machine learning for using large data on resource management, machine and deep learning techniques for time-series data management, machine and deep learning techniques for time-series data management for query optimization
Cloud Computing
data services, cloud economy, cost-aware data management, database-as-a-service, metadata management, data placement, data privacy and reliability, data and process consolidation, cost and time efficiency, service level agreements
P2P Systems
P2P overlays structured and unstructured, multidimensional data sharing, peer data management systems, data and processing heterogeneity, query processing, query answering and rewriting, continuous queries, mobile peer environments, data privacy
Semantic Web
semantic query processing, semantic similarity, ontology mapping, semantic annotation, semantic clustering, semantic integration
Distributed Systems
distributed and federated databases, grid computing, massive information sharing, P2P systems, distributed query processing, query optimization, distributed triggers, distributed data coordination, cloud computing, social networks
Databases
query languages, active mechanisms, query optimization, querying on semi-structured and unstructured data, data and schema heterogeneity and integration, schema mapping and data exchange, graph data models
General
spatial data and queries, information integration and exchange, mobile databases, data streams, privacy and security, sensor networks, querying and processing graphs, location-based services
Big Data Management
data storage/replication/movement, analytics workflows, execution optimization, deployment optimization, computation-intensive queries, scientific data management, integration and handling of intermediate results, consolidation of heterogeneous data sources, data navigation, query calibration, workflow recalibration techniques, deployment on hybrid infrastructures, time-series data management
Big Data Analytics
business and scientific analytics, creation and support of analytics applications: on web data, sensor data, cell data, time-series data, combinations of unstructured and structured data, support of analytics for users of variable expertise, approximate querying, dynamic and agile schema mappings, dynamic and agile data integration and analysis, large data graphs, exploration and visualization, community detection, conversational data analysis
Machine Learning
large-scale resource management based on machine learning techniques, adaptations of reinforcement learning techniques, employment of machine learning for using large data on resource management, machine and deep learning techniques for time-series data management, machine and deep learning techniques for time-series data management for query optimization
Cloud Computing
data services, cloud economy, cost-aware data management, database-as-a-service, metadata management, data placement, data privacy and reliability, data and process consolidation, cost and time efficiency, service level agreements
P2P Systems
P2P overlays structured and unstructured, multidimensional data sharing, peer data management systems, data and processing heterogeneity, query processing, query answering and rewriting, continuous queries, mobile peer environments, data privacy
Semantic Web
semantic query processing, semantic similarity, ontology mapping, semantic annotation, semantic clustering, semantic integration
Distributed Systems
distributed and federated databases, grid computing, massive information sharing, P2P systems, distributed query processing, query optimization, distributed triggers, distributed data coordination, cloud computing, social networks
Databases
query languages, active mechanisms, query optimization, querying on semi-structured and unstructured data, data and schema heterogeneity and integration, schema mapping and data exchange, graph data models
General
spatial data and queries, information integration and exchange, mobile databases, data streams, privacy and security, sensor networks, querying and processing graphs, location-based services
研究兴趣
论文共 110 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
CoRR (2024)
引用0浏览0EI引用
0
0
35TH INTERNATIONAL CONFERENCE ON SCIENTIFIC AND STATISTICAL DATABASE MANAGEMENT, SSDBM 2023pp.21:1-21:4, (2023)
CASCON '23: Proceedings of the 33rd Annual International Conference on Computer Science and Software Engineeringpp.251-253, (2023)
引用0浏览0EI引用
0
0
Ning Wang,Amin Kamali,Verena Kantere,Calisto Zuzarte, Vincent Corvinelli, Brandon Frendo, Steve Donoghue
2023 IEEE Sixth International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)pp.133-138, (2023)
DaWaKpp.340-355, (2023)
引用0浏览0EI引用
0
0
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn