Research in an academic environment provides a unique opportunity to solve problems and vision the technology of the future. It is my desire to utilize my computer science research background to originate and assess novel technologies for computer science learning. I am concerned about computer science education in broad-spectrum, both because of personal proficiency and to the increasing significance of teaching computational thinking as a primary kind of literacy parallel to reading, writing, and mathematics. As a computer science professional and researcher, I am in a distinctive situation to make essential advances across areas such as web mining, software engineering, energy-aware scheduling and meta-heuristic optimization techniques, all directed by a motivation to enhance computer science education. My current research interests are concerned with the development of methods and algorithms for web mining, software engineering, energy-aware scheduling and meta-heuristic optimization techniques. In the past two decades, there have been many advances in these fields. Despite numerous technological advances in software and hardware as well as algorithms, there are many challenging problems that still limit realism and effectiveness. My main research goal is to create techniques and algorithms for the efficient utilization of these fields.
My Research Background: I do believe that a strong understanding of the problem is extremely important. My M.Tech. thesis work was on the generation of metrics for the effective selection of automatic software testing tools. Although there is a wide range of testing tools available in the market and they vary in approach, quality, usability and other characteristics. To select the appropriate testing tool, there is a requirement of a way to prioritize them on the basis of characteristics. This project proposes a set of metrics for measuring the characteristics of the testing tools for examination and selection of automated testing tools.
My Ph.D. dissertation aims to develop a general framework to make use of structure and graph information along with vendor’s modifications on websites, to attain the better search results. To this purpose, a new concept of page ranking and search engine architecture was developed. A detailed study of the web mining, its type, scope and working was performed to decide the way to move to a selected path as Web Structure Mining research field. The outcome of empirical analysis helped to decide the factors affecting the page ranking methods. A new page ranking methodology named VDNM, having one of the factors as modifications count was proposed. A search engine architecture NAO-BSSE, where the importance of ontology is shown as well as the advantage of ontology is used at a different place in searching activity. By applying the VDNM and using search engine architecture NAO-BSSE the efforts required by the user is minimized as well as the quality of the result is improved in the form of pages with high relevancy appears first in the search result.
Current research: As energy conservation has become a prime objective due to excess use and huge demand of energy in data centres and battery based computing devices. One solution is to use efficient job scheduling algorithms. Although the practical importance of non-clairvoyant scheduling problem is higher than clairvoyant scheduling, in the past few years the non-clairvoyant scheduling problem has been studied lesser than clairvoyant scheduling. My co-authors and I have worked on the energy-aware online non-clairvoyant scheduling algorithms, where the scheduler has to maintain the machine’s state balance to obtain efficient job schedule and avoid unnecessary energy consumption.
My current research also includes a project of renewable energy sources integration using micro-grid technology for demand-side management. Optimization of MG provides enhanced generation from RES at minimum operating cost. The micro-grid optimization problem involves a large number of variables and constraints; therefore, it is complex in nature and various existing algorithms are unable to handle them efficiently. We have explored nature as an inspiration to adopt the problem-solving behaviour. We proposed an artificial shark optimization method to remove the limitation of existing algorithms for solving the economical operation problem of MG. In this work, EVTs incorporated grid-connected smart micro-grid system is introduced.
Future research: My future work will primarily focus on nature-inspired meta-heuristic algorithms and its utilization in the software engineering. The quantum computers are the future trend of hardware technologies. My future research will be focused on Quantum-behaved nature inspired meta-heuristic algorithms.