UG/PG/PhD admissions open for 2025-26
Apply Now
Fee Payment (EMI)
Prof. (Dr.) Amrita

Prof. (Dr.) Amrita

Professor, Computer Science & Engineering (CSE)

amrita.prasad@sharda.ac.in

About

Dr. Amrita is an accomplished academic and researcher with over 24 years of experience spanning academia, industry, and research. She currently serves as a Professor in the Department of Computer Science & Engineering at the Sharda School of Computing Science & Engineering at Sharda University, Greater Noida. She is also a core member of the university's Center for Cyber Security and Cryptology. Her work actively contributes to teaching, research and training in the domains of cybersecurity and intelligent systems.

She holds a Ph.D. in Computer Science and Engineering from Sharda University, with her doctoral research focusing on developing an intelligent ensemble-based system for intrusion detection using advanced machine learning techniques. She also holds an M.Tech in Computer Science and an MCA from Banasthali Vidyapith.

Dr. Amritas professional experience includes roles in software development, where she worked as a Software Engineer involved in designing and implementing cross-platform solutions. These industry engagements provide a strong foundation for her applied teaching and research.

In her academic career, she has taught a diverse portfolio of undergraduate, postgraduate, and Ph.D. courses. She supervises research at the B.Tech, M.Tech, and Ph.D. levels, primarily in cybersecurity and machine learning.

Her research contributions include over 40+ papers published in reputed peer-reviewed journals and conferences indexed in Scopus and SCI. She is the author of a book, has contributed to several Scopus-indexed book chapters, and holds 13 innovation patents and one copyright. She currently serves as the Principal Investigator of a DRDO Funded Project, with a grant of INR 47.6 lakhs. In addition, she has successfully completed a Sharda University Seed Fund Project, with a grant of INR 1.95 lakhs.

Dr. Amrita is actively involved in academic leadership, curriculum development, and the organization of international conferences, faculty development programs, and training program, and technical workshops. She has served as a Session Chair, Reviewer, and Technical Program Committee Member for various international forums and has delivered several invited talks. She is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and lifetime member of the Cryptological Research Society of India (CRSI).

She is passionately committed to advancing the field of computer science through research, impactful teaching, and innovation. Her core interest lies in integrating cutting-edge research with real-world applications to foster an innovative, learner-centric academic environment.

Experience
  • 24 + years
Qualification
  • Ph. D. (Computer Science and Engineering), Sharda University
  • M. Tech (Computer Science), Banasthali Vidyapith
  • MCA, Banasthali Vidyapith
Award & Recognition

  • Ongoing DRDO Funded Project as PI, grant of INR 47.6 lakhs
  • Completed Seed Fund by Sharda University as Co-PI, grant of INR 1.95 lakh
  • Received best paper award in International Conference, EAMMIS 2021 held at Istanbul Medeniyet University, Turkey on 19-20 March 2021.
  • Member of the Technical Program Committee in International Conferences
  • Session Chair & Reviewer for International Conferences.

Research

  • Publications in SCIE/Scopus Indexed Journals: 16
  • Publications in other Journals: 4
  • Publications in Scopus International Conferences: 25
  • Patent: 13 Published
  • Copyright: 1 Published and Granted
  • Authored Book: 01
  • Publications as Book Chapters: 07

Certifications

  • The Dale Carnegie Certification for High Impact Teaching Skills.

Memberships

  • Senior Member of Institute of Electrical and Electronics Engineers (IEEE)
  • Lifetime member of the Cryptological Research Society of India (CRSI)

Area of Interest

  • Cyber Security
  • Machine Learning
  • Intrusion Detection System
  • Hybrid System
  • Feature Selection