What is he best known for?
The fields of study he is best known for:
- Computer network
- The Internet
- Operating system
His main research concerns Distributed computing, Server, Computer network, Data mining and Anomaly detection.
His research integrates issues of Scheduling, Latency, The Internet and Distributed services in his study of Distributed computing.
His Server study incorporates themes from Workload, Scalability and Multicast.
His studies deal with areas such as Geolocation, Optimal stopping, Web server and File size as well as Computer network.
He interconnects Anomaly, Linear subspace and Network packet in the investigation of issues within Data mining.
Mark Crovella combines subjects such as Flow, Subspace topology and Traffic engineering with his study of Anomaly detection.
His most cited work include:
- Self-similarity in World Wide Web traffic: evidence and possible causes (2466 citations)
- Generating representative Web workloads for network and server performance evaluation (1391 citations)
- Method and apparatus for reliable and scalable distribution of data files in distributed networks (1244 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Computer network, Distributed computing, The Internet, Theoretical computer science and World Wide Web.
His work in Computer network addresses issues such as Scalability, which are connected to fields such as Data file and Node.
His Distributed computing research is multidisciplinary, incorporating perspectives in Routing, Path, Web server, Queueing theory and Server.
Mark Crovella has included themes like Network topology and Set in his The Internet study.
His Theoretical computer science study integrates concerns from other disciplines, such as Routing table, Graph theory, Graph and Matrix completion.
In most of his World Wide Web studies, his work intersects topics such as Self-similarity.
He most often published in these fields:
- Computer network (25.24%)
- Distributed computing (21.36%)
- The Internet (15.53%)
What were the highlights of his more recent work (between 2014-2021)?
- Recommender system (4.37%)
- Theoretical computer science (11.17%)
- Artificial intelligence (7.77%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Recommender system, Theoretical computer science, Artificial intelligence, Embedding and Set.
His Recommender system research also works with subjects such as
- Data science which connect with Profiling, Product and Variation,
- Matrix decomposition which is related to area like Deep learning, Imputation and Data mining,
- User experience design which connect with Web service, Web performance, Missing data and Information retrieval.
His study in Theoretical computer science is interdisciplinary in nature, drawing from both Biological network, Matrix, Matrix completion and Rank.
His study focuses on the intersection of Artificial intelligence and fields such as Machine learning with connections in the field of Classifier.
His Set research is multidisciplinary, relying on both Internet research and Measure.
His research on World Wide Web focuses in particular on The Internet.
Between 2014 and 2021, his most popular works were:
- Fighting Fire with Fire: Using Antidote Data to Improve Polarization and Fairness of Recommender Systems (20 citations)
- Matrix Completion with Queries (17 citations)
- One for all and all for One: Improving replication of genetic studies through network diffusion. (15 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- The Internet
- Operating system
His primary areas of investigation include Recommender system, Embedding, Theoretical computer science, Replication and Set.
His work in the fields of Recommender system, such as Collaborative filtering, overlaps with other areas such as Model system, Polarization and Risk analysis.
His Embedding research includes elements of Multidimensional scaling and Dimensionality reduction.
The study incorporates disciplines such as Interaction network, Biological network, Inference and Genomics in addition to Theoretical computer science.
His research in Replication intersects with topics in Disease gene, Genome, Gene prediction and Computational biology.
The concepts of his Set study are interwoven with issues in Service, IP forwarding, State, Object and The Internet.
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.
