What is she best known for?
The fields of study she is best known for:
- Operating system
- Database
- Programming language
Her primary areas of study are Distributed computing, Stream processing, Scalability, The Internet and World Wide Web.
Her Distributed computing research includes themes of Theoretical computer science, Class, Directed acyclic graph, Node and Key.
Magdalena Balazinska interconnects Fault tolerance, High availability, Set and Data stream management system in the investigation of issues within Stream processing.
In her study, Cache and Very large database is inextricably linked to Task, which falls within the broad field of Scalability.
Her work on Web navigation as part of general The Internet research is frequently linked to Web application security, thereby connecting diverse disciplines of science.
Her World Wide Web study incorporates themes from Control and Software deployment.
Her most cited work include:
- The Design of the Borealis Stream Processing Engine (1264 citations)
- HaLoop: efficient iterative data processing on large clusters (651 citations)
- Building the Internet of Things Using RFID: The RFID Ecosystem Experience (535 citations)
What are the main themes of her work throughout her whole career to date?
Her main research concerns Data mining, Database, Data management, Distributed computing and Data science.
Her Data mining research is multidisciplinary, incorporating perspectives in Event, Probabilistic logic, Theoretical computer science and Search engine indexing.
Her work carried out in the field of Data management brings together such families of science as Sensor web, Wireless sensor network and World Wide Web.
Her Distributed computing research is multidisciplinary, relying on both Skew, Scalability and Cloud computing.
The study incorporates disciplines such as Computer architecture, Data stream mining, Data processing and Relational database in addition to Scalability.
Magdalena Balazinska has included themes like High availability and Set in her Stream processing study.
She most often published in these fields:
- Data mining (17.42%)
- Database (16.85%)
- Data management (15.73%)
What were the highlights of her more recent work (between 2016-2021)?
- Artificial intelligence (8.99%)
- Analytics (12.36%)
- Sampling (3.37%)
In recent papers she was focusing on the following fields of study:
Artificial intelligence, Analytics, Sampling, Machine learning and Database are her primary areas of study.
Her Analytics study combines topics from a wide range of disciplines, such as Cloud data, Cloud computing, Codec and World Wide Web.
Her work in Cloud data addresses subjects such as Provisioning, which are connected to disciplines such as Distributed computing.
Her Distributed computing research includes elements of Telecommunications network, Overhead and Data stream management system.
Her biological study spans a wide range of topics, including Stream processing, Orientation, Computer graphics and Virtual reality.
She combines subjects such as Set and Data management with her study of Clustering high-dimensional data.
Between 2016 and 2021, her most popular works were:
- Learning State Representations for Query Optimization with Deep Reinforcement Learning (68 citations)
- The Myria Big Data Management and Analytics System and Cloud Services. (49 citations)
- Comparative evaluation of big-data systems on scientific image analytics workloads (28 citations)
In her most recent research, the most cited papers focused on:
- Operating system
- Database
- Programming language
Magdalena Balazinska spends much of her time researching Analytics, Query optimization, World Wide Web, Data science and Artificial intelligence.
Her studies deal with areas such as Representation, State, Relational algebra and Reinforcement learning as well as Query optimization.
Her work carried out in the field of World Wide Web brings together such families of science as Cloud data, Cloud computing, myria- and Big data management.
She combines subjects such as Use case, Image and Big data with her study of Data science.
Her Artificial intelligence research incorporates elements of Cardinality, Machine learning and Estimation.
Magdalena Balazinska works mostly in the field of Estimation, limiting it down to topics relating to Cardinality and, in certain cases, Parameterized complexity, Hash function and Foreign key.
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