What is she best known for?
The fields of study she is best known for:
- Operating system
- Database
- Programming language
Anastasia Ailamaki focuses on Database, Parallel computing, Scalability, Online transaction processing and Multi-core processor.
Her Database research also works with subjects such as
- Cache which connect with Cloud computing,
- Distributed computing and related Cloud management and Data management.
Her research in Parallel computing intersects with topics in Virtual machine, Bottleneck and Processor scheduling.
The study incorporates disciplines such as Synchronization and Workload in addition to Scalability.
Her biological study spans a wide range of topics, including Transaction processing system, Thread, Concurrency, Database tuning and Distributed transaction.
Her Multi-core processor research is multidisciplinary, incorporating elements of Die, Computer architecture, Server and Benchmark.
Her most cited work include:
- Reconstruction and Simulation of Neocortical Microcircuitry (782 citations)
- Clearing the clouds: a study of emerging scale-out workloads on modern hardware (668 citations)
- Reactive NUCA: near-optimal block placement and replication in distributed caches (357 citations)
What are the main themes of her work throughout her whole career to date?
Her scientific interests lie mostly in Database, Distributed computing, Scalability, Online transaction processing and Parallel computing.
Her studies deal with areas such as Raw data and Overhead as well as Database.
As a part of the same scientific family, Anastasia Ailamaki mostly works in the field of Distributed computing, focusing on Workload and, on occasion, Database administrator.
Her Scalability research is multidisciplinary, relying on both Theoretical computer science, Data mining, Synchronization, Software and Multi-core processor.
Her study explores the link between Multi-core processor and topics such as Server that cross with problems in Computer hardware, Cloud computing and Key.
Her Online transaction processing research focuses on Thread and how it connects with Database transaction.
She most often published in these fields:
- Database (24.02%)
- Distributed computing (21.40%)
- Scalability (21.40%)
What were the highlights of her more recent work (between 2017-2021)?
- Distributed computing (21.40%)
- Online transaction processing (19.65%)
- Online analytical processing (3.93%)
In recent papers she was focusing on the following fields of study:
Anastasia Ailamaki spends much of her time researching Distributed computing, Online transaction processing, Online analytical processing, Query plan and Cache.
Her work carried out in the field of Distributed computing brings together such families of science as Data access, Join, Software deployment and Reinforcement learning.
Her study in Online transaction processing is interdisciplinary in nature, drawing from both Hypervisor and Operating system.
Her Operating system research also works with subjects such as
- Test, which have a strong connection to Data management,
- Data structure most often made with reference to Concurrency control.
Her Cache study introduces a deeper knowledge of Parallel computing.
Her CUDA research is multidisciplinary, incorporating perspectives in Multi-core processor and Server.
Between 2017 and 2021, her most popular works were:
- The Seattle Report on Database Research (20 citations)
- Bridging the Latency Gap between NVM and DRAM for Latency-bound Operations (15 citations)
- HetExchange: encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines (12 citations)
In her most recent research, the most cited papers focused on:
- Operating system
- Database
- Programming language
The scientist’s investigation covers issues in Spatial analysis, Algorithm, Process, Query plan and Server.
The concepts of her Spatial analysis study are interwoven with issues in Scalability, Overhead, Minimum bounding box, Clipping and Bounding overwatch.
She has researched Process in several fields, including Distributed computing, Workload, Probabilistic logic, Dirty data and Constraint.
Her Server research includes themes of Computer hardware, Task parallelism, High memory, Hash function and Multi-core processor.
Her Multi-core processor study combines topics from a wide range of disciplines, such as Compiler, Memory hierarchy, Cache, Shared memory and CUDA.
Her work in Dram covers topics such as Parallel computing which are related to areas like Exploit.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
