Ph.D ( Computer Science and Engineering )

  • Course Level

    Course Level

  • Course Fee

  • Scholarship



Ph.D in Computer Science & Engineering offers candidates a prospect to contribute to academia in their chosen area of study. The candidates are also provided with an opportunity to teach or participate in ongoing research at MRIIRS.

Key Features

  • The key features of a Ph.D. program in Computer Science & Engineering (CSE) typically include:
  • Research Emphasis: A strong focus on original and innovative research, allowing candidates to make significant contributions to the body of knowledge in their specific area of study within CSE.
  • Advanced Coursework: Rigorous coursework that provides candidates with a deep understanding of foundational and cutting-edge concepts in computer science and engineering, ensuring a solid academic foundation.
  • Interdisciplinary Opportunities: Opportunities for interdisciplinary research, allowing candidates to explore connections between computer science and other fields, fostering a holistic approach to problem-solving.
  • Teaching Opportunities: Provision for candidates to gain teaching experience, preparing them for academic roles and enhancing their ability to communicate complex concepts effectively.
  • Mentorship: Access to experienced faculty mentors who guide and support candidates throughout their research journey, providing valuable insights and expertise.
  • Research Facilities: Access to state-of-the-art laboratories, computing resources, and research facilities to facilitate experimental and theoretical research endeavors.
  • Publication Expectations: Encouragement and support for candidates to publish their research findings in reputable conferences and journals, contributing to the dissemination of knowledge in the academic community.
  • Seminars and Workshops: Regular seminars, workshops, and conferences that create opportunities for candidates to present their work, exchange ideas, and stay updated on the latest advancements in CSE.
  • Collaborative Research Culture: Fostering a collaborative research environment that encourages candidates to work with peers, faculty, and industry professionals, promoting a diverse and enriching research experience.
  • Thesis Defense: Culmination of the program with a comprehensive thesis defense, where candidates present and defend their research findings before a panel of experts, demonstrating mastery in their chosen area of study.

Areas of expertise available in the department

S No Faculty Name Designation Thrust Areas
1 Dr. Brijesh Kumar Professor Simulation and Modelling, Web Technologies
2 Dr. Rashima Mahajan Professor Signal Processing, Machine Learning, IoT
3 Dr. Kamlesh Sharma Professor Natural Language Processing, Data Mining, Machine Learning
4 Dr. Tapas Kumar Professor Digital Image processing, Artificial Intelligence & Machine Learning
5 Dr. Mamta Dahiya Professor Data Science, ML, GeoAI
6 Dr. Suresh Kumar Professor Artificial Intelligence
7 Dr. Supriya Panda Professor Soft Computing, Optimization & Algorithms
8 Dr. Deepa Bura Professor Data Mining, Software Engineering, Data Science
9 Dr. Meeta Singh Professor Data Mining, Data Science, Cloud Computing
10 Dr. Poonam Tanwar Professor Machine Learning, Medical Imaging, Data Science, Natural Language Processing, Computational Intelligence, Knowledge Representation & Retrieval
11 Dr. Poonam Nandal Professor Machine Learning, Data Science, Information Retrieval
12 Dr. Indu Kashyap Professor Machine Learning, Artificial Intelligence, Wireless Networks
13 Dr. Mahboob Alam Associate Professor Data Analytics, Machine Learning, Big Data, Cloud Computing
14 Dr. Nitasha Soni Associate Professor Artificial Intelligence, Cloud Computing
15 Dr. Savita Associate Professor IOT, Wireless Communication, Microprocessor

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