What is he best known for?
The fields of study he is best known for:
- The Internet
- Artificial intelligence
- Computer network
His primary scientific interests are in Computer Aided Design, Engineering drawing, Virtual reality, CAD and Electric vehicle.
His study in Computer Aided Design is interdisciplinary in nature, drawing from both Concurrent engineering, Algorithm, The Internet and Feature.
His studies in Engineering drawing integrate themes in fields like Product design and Assembly modelling.
The various areas that he examines in his Virtual reality study include Design activities, Response time and Systems engineering.
Rajit Gadh combines subjects such as Design tool, Rendering, Geometric modeling and Component with his study of CAD.
His Electric vehicle research includes themes of Grid and Electrical engineering, Smart grid.
His most cited work include:
- Smart electric vehicle (ev) charging and grid integration apparatus and methods (420 citations)
- Distributed Optimal Energy Management in Microgrids (287 citations)
- Real-Time Energy Management in Microgrids (178 citations)
What are the main themes of his work throughout his whole career to date?
Electric vehicle, Smart grid, Grid, Computer Aided Design and Microgrid are his primary areas of study.
His Electric vehicle research is multidisciplinary, relying on both Automotive engineering, Real-time computing, Mathematical optimization, Scheduling and Electrical engineering.
His Smart grid study integrates concerns from other disciplines, such as Computer network, Embedded system, Demand response and Interoperability.
His biological study spans a wide range of topics, including Power, Scalability, Charging station, Optimization problem and Vehicle-to-grid.
Rajit Gadh has included themes like CAD, Engineering drawing, Virtual reality, Human–computer interaction and Feature recognition in his Computer Aided Design study.
His study focuses on the intersection of Microgrid and fields such as Distributed generation with connections in the field of Distributed computing.
He most often published in these fields:
- Electric vehicle (25.37%)
- Smart grid (14.43%)
- Grid (11.94%)
What were the highlights of his more recent work (between 2017-2021)?
- Electric vehicle (25.37%)
- Grid (11.94%)
- Mathematical optimization (8.46%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Electric vehicle, Grid, Mathematical optimization, Scheduling and Automotive engineering.
His Electric vehicle research includes elements of Kernel density estimation, Renewable energy, Smart grid, Electrical engineering and Computer simulation.
His Electrical engineering research incorporates themes from Charging station, Automation and Identification.
His work carried out in the field of Grid brings together such families of science as Power, Distributed generation, Optimization problem and Scalability.
The Mathematical optimization study combines topics in areas such as Smoothing and Minimum weight.
His Scheduling research integrates issues from Energy management and Machine learning, Statistical model, Cluster analysis, Artificial intelligence.
Between 2017 and 2021, his most popular works were:
- Real-time renewable energy incentive system for electric vehicles using prioritization and cryptocurrency (40 citations)
- Vehicle grid integration for demand response with mixture user model and decentralized optimization (21 citations)
- A Non-Cooperative Framework for Coordinating a Neighborhood of Distributed Prosumers (17 citations)
In his most recent research, the most cited papers focused on:
- The Internet
- Artificial intelligence
- Computer network
Rajit Gadh mainly focuses on Electric vehicle, Grid, Mathematical optimization, Scalability and Computer simulation.
His Electric vehicle study incorporates themes from Schedule, Automotive engineering and Kernel density estimation.
His research in Automotive engineering intersects with topics in Distributed generation, User modeling, Grid computing, Energy and Demand response.
Rajit Gadh focuses mostly in the field of Kernel density estimation, narrowing it down to matters related to Energy consumption and, in some cases, Algorithm and Support vector machine.
The concepts of his Mathematical optimization study are interwoven with issues in Scheduling and Load profile.
His research investigates the connection between Job shop scheduling and topics such as Photovoltaic system that intersect with problems in Smart grid.
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