What is he best known for?
The fields of study he is best known for:
- Operating system
- Artificial intelligence
- Database
Tim Kraska mainly focuses on Scalability, Artificial intelligence, Information retrieval, Benchmark and Machine learning. His research integrates issues of Cloud computing, Distributed computing, Semantic analytics and Big data in his study of Scalability. His Artificial intelligence study combines topics in areas such as Liveness and CUDA.
In his study, which falls under the umbrella issue of Information retrieval, Spatial query, Online aggregation, View, Set and Data integration is strongly linked to Crowdsourcing. His Benchmark research incorporates elements of Data model and Aggregate. The various areas that he examines in his Machine learning study include Sorted array, Key, Data management and Implementation.
His most cited work include:
- CrowdDB: answering queries with crowdsourcing (576 citations)
- CrowdER: crowdsourcing entity resolution (388 citations)
- The Case for Learned Index Structures (295 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Machine learning, Data mining, Benchmark and Database. The concepts of his Artificial intelligence study are interwoven with issues in Column and Query optimization. Tim Kraska has included themes like Variety, Set, Data management and Implementation in his Machine learning study.
His studies examine the connections between Data mining and genetics, as well as such issues in Key, with regards to Index and Data exploration. His Database study frequently links to other fields, such as Cloud computing. The Cloud computing study combines topics in areas such as Scalability, Analytics and World Wide Web.
He most often published in these fields:
- Artificial intelligence (26.26%)
- Machine learning (21.72%)
- Data mining (15.66%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (26.26%)
- Machine learning (21.72%)
- Benchmark (14.14%)
In recent papers he was focusing on the following fields of study:
Tim Kraska spends much of his time researching Artificial intelligence, Machine learning, Benchmark, Data mining and Data management. His Artificial intelligence research focuses on subjects like Computer vision, which are linked to Global Positioning System and Process. His work deals with themes such as Relational database and Query optimization, which intersect with Machine learning.
His studies in Benchmark integrate themes in fields like Data exploration and Data set. His Data management study combines topics from a wide range of disciplines, such as Memory footprint and Data science. As a part of the same scientific study, Tim Kraska usually deals with the Data science, concentrating on Data visualization and frequently concerns with Analytics and Big data.
Between 2019 and 2021, his most popular works were:
- ALEX: An Updatable Adaptive Learned Index (26 citations)
- Learning Multi-Dimensional Indexes (25 citations)
- The Seattle Report on Database Research (20 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Artificial intelligence
- Database
Tim Kraska focuses on Artificial intelligence, Machine learning, Benchmark, Key and Single pass. His research on Artificial intelligence frequently connects to adjacent areas such as Computer vision. His biological study spans a wide range of topics, including Cardinality, Relational database and Query optimization.
His Benchmark study frequently draws connections between related disciplines such as Implementation. His research in Key intersects with topics in Baseline, Real-time computing, Search engine indexing and Index. His work carried out in the field of Search engine indexing brings together such families of science as Computer data storage, Block, Field and Dimension.
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