Rama Sushil

MCA Gorakhpur University, PhD IIT Roorkee

Professor, Academic Head CSE

  •  0135-7144000, 7144300
  • Specialisation

    Artificial Intelligence, Cloud Computing, Wireless Sensor Network

  • Research Interest

    Image processing with Machine Learning & Deep learning for disease  prediction, ML &  BlockChain for IoT security, Prolonging WSN Lifetime, Cloud virtualization & Fault tolerance techniques

  • Brief Profile

    Dr. Rama Sushil, joined School of Computing in July 2013 as a professor. Dr. Sushil received her PhD degree in the area of Mobile Computing from IIT Roorkee in 2010 after one year research work in Hirosaki University, Japan as a research student in 1998-99. She has presented her research work in many international conferences held in USA, Italy, Japan, Taiwan & Singapore. She has received full financial support by ictp Italy for presenting her research work on “Web Enabling Technologies” in 2005. AICTE fully sponsored her visit to USA in 2007 for presenting her research work. There are many government supports for research activities in her credit.

    She has published a book on “Artificial Intelligence” and contributed two chapters in two different books; in IGI Global for Application of Cloud Computing in Library Information Service Sector and other chapter on M-Commerce. She has published her research papers in SCI/Scopus/WOS/journals and in National/ International Conference proceedings of IEEE and Springer can be seen at Google scholar. Her area of interest includes: Machine Learning, Algorithms, WSN and Cloud Computing, Image segmentation.

    One patent published & one copyright registered are in her credit. Patent: Rama Sushil, Diwaker, Anurag Shrivastava, Ankit Agarwal, “IoT Based Emergency Healthcare System” Copyright: Anurag Srivastava & Dr. Rama Sushil, copyright registered for "AN ANDROID APP FOR DETERMINATION OF MELTING POINT OF CHEMICAL SUBSTANCES", 21June2021,

    In the field of image segmentation recently worked for development of an improved cooperative quantum behaved PSO based multilevel thresholding scheme applied on color image segmentation. Further extended the work for Hyper-Spectral Image Segmentation using an Improved PSO Aided with Multilevel Fuzzy Entropy. An innovative objective function based image segmentation technique is also developed which used Mutual-inclusive learning-based multi-swarm PSO algorithm. In the field of Cloud computing A New Approach for VM Failure Prediction using Stochastic Model in Cloud is developed and published in a Taylor and Francis Journal.