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Dharini R

Designation : Assistant Professor
Nature of Employment : Regular
Qualification : B.E.,M.E.,Ph.D
Phone : +91 44 2275 1347,48,50 (Office)
Email ID : dharini@crescent.education

Education

Degree Discipline Year of Passing University
Ph.D Computer Science 2021 Vellore Institute of Technology, Chennai
M.E. Software Engineering 2011 Anna University, Chennai
B.Tech. Information Technology 2009 Anna University, Chennai

Work Experience

Designation Institution Duration No. of Years
Assistant Professor B.S. Abdur Rahman Crescent Institute of Science & Technology September 2021 to till date Till date
Assistant Professor Rajalakshmi Engineering College, Chennai June 2011 To December 2013 30 months

Lecture Courses

  • Full stack mobile application development – Back End
  • Gaming Technology
  • Usability Engineering

Area of Research Interest

  • Social Media Text Analytic
  • Artificial Intelligence

Publication

  • Dharini Ramachandran, and Parvathi Ramasubramanian. ”Event detection from Twitter– a survey.” International Journal of Web Information Systems 14.3 (2018): 262-280, Scopus Indexed (https://doi.org/10.1108/IJWIS-11-2017-0075)
  • Dharini Ramachandran, and R. Parvathi. ”Enhanced Event Detection in Twitter Through Feature Analysis.” International Journal of Information Technology and Web Engineering (IJITWE) 14.3 (2019): 1-15, Scopus Indexed (https://doi.org/10.4018/IJITWE.2019070101)
  • Dharini Ramachandran, and R. Parvathi. ”Analysis of Twitter Specific Preprocessing Technique for Tweets.” Procedia Computer Science 165 (2019): 245-251, Scopus Indexed(https://doi.org/10.1016/j.procs.2020.01.083)
  • Dharini Ramachandran, and R. Parvathi, ”Enhanced Classification of Crisis Related Tweets Using Deep Learning Models and Word Embeddings” in International Journal of Web Engineering and Technology, 16(2), pp.158-186. – Scopus Indexed (https://doi.org/10.1504/IJWET.2021.117773)
  • Dharini Ramachandran, and R. Parvathi. ”A Novel Domain and Event Adaptive Tweet Augmentation Approach for Enhancing the Classification of Crisis Related Tweets”, in Data & Knowledge Engineering (2021) – In Press- SCI and Scopus Indexed (https://doi.org/10.1016/j.datak.2021.101913)