What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Machine learning
Dipankar Dasgupta spends much of his time researching Artificial immune system, Artificial intelligence, Field, Machine learning and Anomaly detection.
His Artificial immune system study combines topics from a wide range of disciplines, such as Artificial neural network, Immune system and Artificial life.
The concepts of his Artificial intelligence study are interwoven with issues in Data mining and Pattern recognition.
His Machine learning study incorporates themes from Telecommunication computing, Relation and Pattern recognition.
His Anomaly detection research integrates issues from Computer security, Computer virus and Constant false alarm rate.
Dipankar Dasgupta interconnects Evolutionary algorithm and Software engineering in the investigation of issues within Evolutionary computation.
His most cited work include:
- New Ideas In Optimization (1303 citations)
- Artificial Immune Systems and Their Applications (923 citations)
- Genetic and Evolutionary Computation - GECCO 2004 (887 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Artificial intelligence, Computer security, Artificial immune system, Machine learning and Data mining.
In the subject of general Artificial intelligence, his work in Artificial neural network, Evolutionary computation and Evolutionary algorithm is often linked to Field, thereby combining diverse domains of study.
The study incorporates disciplines such as Security information and event management and Cloud computing security in addition to Computer security.
The various areas that Dipankar Dasgupta examines in his Artificial immune system study include Anomaly detection, Computational intelligence, Immune system and Pattern recognition.
In his research, Detector is intimately related to Algorithm, which falls under the overarching field of Anomaly detection.
His Data mining research is multidisciplinary, relying on both Cluster analysis and Fuzzy logic.
He most often published in these fields:
- Artificial intelligence (33.49%)
- Computer security (22.79%)
- Artificial immune system (21.86%)
What were the highlights of his more recent work (between 2014-2021)?
- Computer security (22.79%)
- Artificial intelligence (33.49%)
- Authentication (5.58%)
In recent papers he was focusing on the following fields of study:
Computer security, Artificial intelligence, Authentication, Multi-factor authentication and Data mining are his primary areas of study.
He works mostly in the field of Computer security, limiting it down to topics relating to Cloud computing and, in certain cases, Intrusion detection system.
His Artificial intelligence research incorporates elements of Machine learning, Ransomware and Pattern recognition.
Dipankar Dasgupta conducted interdisciplinary study in his works that combined Machine learning and Field.
His Multi-factor authentication study integrates concerns from other disciplines, such as Exploit and Distributed computing.
His Data mining research includes themes of CURE data clustering algorithm, Determining the number of clusters in a data set, Local binary patterns, Entropy and Euclidean distance.
Between 2014 and 2021, his most popular works were:
- Privacy and security issues in mobile health: Current research and future directions (31 citations)
- A survey of blockchain from security perspective (28 citations)
- Apache Hama: An Emerging Bulk Synchronous Parallel Computing Framework for Big Data Applications (27 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Machine learning
The scientist’s investigation covers issues in Distributed computing, Authentication, Multi-factor authentication, Computer security and Data mining.
In his study, Dipankar Dasgupta carries out multidisciplinary Distributed computing and Field research.
His work on Authentication protocol as part of general Authentication research is frequently linked to Single factor, thereby connecting diverse disciplines of science.
His Authentication protocol research incorporates themes from Computer access control and Selection.
His work on Access control and Security system as part of general Computer security research is frequently linked to Risk analysis, Short paper and Insider threat, bridging the gap between disciplines.
His studies deal with areas such as Exploit, Hacker and Code as well as Data mining.
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