Ph.D in Information Technology

Overview

The Ph.D. program in Information Technology at Anurag University covers a wide range of topics, including data mining, artificial intelligence, computer networks, software engineering, and database systems. The program is research-oriented, and students are required to undertake an original research project under the guidance of a faculty advisor.

Research Areas

  • Machine Learning and Artificial Intelligence
  • Internet of Things, Cloud Computing
  • Big Data Analytics
  • Network Security, Cryptography
  • Distributed Systems and its Security
  • Computer Networks

Duration

For Full-Time PhD scholars - 3 Years

For Part-Time PhD scholars - 4 Years

Process

  1. Check Eligibility: The first step is to check if you meet the eligibility criteria for the program. You should have a Master’s degree in Information Technology or a related field with a minimum of 55% marks.
  2. Identify a Research Area: You should identify a research area in information technology that interests you and matches your academic and professional background. You can explore the research areas on the Anurag University
  3. website or consult with a faculty member in the Information Technology department.

Credits

0
Credits
0
No of Scholars
0
No of Supervisors

Faculty Guided Ph.D

S.No Name of the Supervisor & Designation / Date of Recognition Area of Interest & Specialization Date of Joining Ph.D Awarded Month & Year Nuber of scholars currently guiding Number of vacancies
1 Dr. K. Sudheer Reddy (11-12-2020)Professor Data Engineering, Software Engineering, Programming Languages, and Artificial Intelligence 06-07-2015 2012 (10-01-2013) 1 7
2 Dr. A. Prasantha Rao (11-12-2020)Professor RTS, Internet of Things, Cloud Computing, Big Data Analytics, Machine Learning 04-05-2012 May-14 2 6
3 Dr. Y V Reddy (11-12-2020) Associate Professor Network Security, Cryptography, Distributed Systems and its Security, Computer Networks 16-11-2020 Jul-18 0 6
4 Dr. D. L. Padmaja (11-12-2020)Associate Professor Data mining, Machine Learning and Allied topics 02-09-2002 Dec-19 0 6
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