Ph.D. in Computer Science
The Department of Computer Science and Applications offers a highly research-intensive full-time and part-time Doctorate programme and provides students with excellent facilities and expert guidance to support their research endeavors. The programme is designed to help postgraduate students develop research skills and prepare for careers in academia or research. The programme provides specialised training in research components such as hypothesis creation, research questions, literature review, research ethics, and the use of online tools and resources. The programme has a strong focus on interdisciplinary research and encourages students to pursue innovative and entrepreneurial ideas in their chosen areas of study. The students are encouraged to find the solution to the problems faced by society and different domains of technology in computer science and other fields.
Ph.D. in Computer Science
The following candidates are eligible to seek admission to the Ph.D. programme
Candidates who have completed:
i) A 1-year/2-semester master’s degree programme after a 4-year/8-semester bachelor’s degree programme or a 2-year/4-semester master’s degree programme after a 3-year bachelor’s degree programme or qualifications declared equivalent to the master’s degree by the corresponding statutory regulatory body, with at least 55% marks in aggregate or its equivalent grade in a point scale wherever grading system is followed or equivalent qualification from a foreign educational institutions accredited by an assessment and accreditation agency which is approved, recognized or authorized by an authority, established or incorporated under a law in its home country or any other statutory authority in that country to assess, accredit or assure quality and standards of the educational institutions.
A relaxation of 5% marks or its equivalent grade may be allowed for those belonging to SC/ST/OBC (non-creamy layer)/differently-abled, Economically Weaker Section (EWS) and other categories of candidates as per the decision of the commission from time to time.
Provided that a candidate seeking admission after a 4-year/8-semester bachelor’s degree programme should have a minimum of 75% marks in aggregate or its equivalent grade on a point scale wherever the grading system is followed. A relaxation of 5% marks or its equivalent grade may be allowed for those belonging to SC/ST/OBC (non-creamy layer)/Differently-abled, Economically Weaker Section (EWS) and other categories of candidates as per the decision of commission from time to time.
ii) Candidates who have completed the M. Phil programme with at least 55% marks in aggregate or its equivalent grade in a point scale. A relaxation of 5% marks or its equivalent grade may be allowed for those belonging to SC/ST/OBC (non-creamy layer)/Differently abled, Economically Weaker Section (EWS) and other categories of candidates as per the decision of commission from time to time.
Reservation is applicable only to Maharashtra domicile candidates provided they submit the necessary documents for reservation before interview. Outside Maharashtra candidates will be considered in open category.II. Selection Process for the admission to the Ph.D. program
1. Candidates satisfying eligibility criterion shall be called to appear for the Ph.D. entrance test conducted by MITWPU.
The exemption will be given from Ph.D. entrance test for those students who qualify UGC-NET /UGC-CSIR NET /GATE (valid score)/CEED/GPAT (valid score)and similar national tests.
2. PhD entrance test shall be qualifying with qualifying marks as 50% provided that relaxation from 50% to 45% shall be allowed for the candidates belongs to SC/ST/OBC (Non creamy layer)/Differently abled category, Economically Weaker section (EWS) and other category of candidates. The syllabus of entrance test shall consist of 50% of research methodology and 50% shall be subject specific.
3. The interview/viva-voce will be conducted by the university for test qualifying candidates. For selection of candidates a weightage of 70% to the entrance test and 30% to the performance in the interview/Viva-voce shall be given. For GATE/NET/JRF /SET/GPAT/CEED qualified students, the selection will be based on Interview/Viva Voce
4. The recommended candidates will be intimated through email about their selection and the candidates will be offered Ph.D. provisional admission.
5. The eligibility of a candidate is provisional as per information provided by the candidate in his/her application form and is subject to verification of minimum eligibility conditions for admission to the program, educational documents and reservation documents (if any).
6. University keep rights to cancel admission of the Ph.D. scholars in the case of misconduct by the scholar, unsatisfactory progress/absent for consecutive two progress seminars, failure in any examination related to Ph.D., fabrication found in educational and reservation documents, candidate is found ineligible, involved in plagiarism in paper publications and thesis.
7. Provisional eligibility to appear in the selection process is no guarantee for admission to the program.
8. Candidates who will join PhD program full time, they will be provided with the stipend as per MITWPU norms.
9. PhD admission will be confirmed after successful completion of the course work with 55% or more as per UGC norms. Ph.D. programme should be minimum of three years including course work and maximum of six years from the date of admission to the Ph.D. programme.
10. A maximum of an additional two years (2) years can be given through the process of re-registration provided, however, that the total period for completion of a Ph.D. programme should not exceed eight (8) years from the date of admission in the Ph.D. programme.
11. Provided further that, female Ph.D. scholars and persons with Disabilities (having more than 40% disability) may be allowed an additional relaxation of two years(2) ; however the total period for completion of a Ph.D. program in such cases should not exceed ten (10) years from the date of admission of the programme.
12. Female candidates may be provided Maternity Leave/Child Care Leave for up to 240 days in the entire duration of Ph.D. programme.
|S.No||Name of Research Supervisor||Areas of research||Personal website link|
|1||Dr. Prof. Shubhalaxmi Joshi||Information Security||https://scholar.google.co.in/citations?user=-2oVyngAAAAJ&hl=en|
|2||Dr. Shankar M. Mali||Digital Image Processing, Pattern Recognition||https://www.shankarmali.com/|
|3||Dr. C. H. Patil||Digital Image Processing, Remote Sensing||https://chpatil.com/|
|4||Dr. Rajeshree Khande||Information Security||https://scholar.google.co.in/citations?user=Jfx5-tYAAAAJ&hl=en|
|5||Dr. Gufran Ansari||Software Engineering, ML, AI, Data mining||https://scholar.google.com/citations?hl=en&user=w8jf5bsAAAAJ|
|6||Dr. Anuradha Kanade||Data Mining, AI, ML||https://scholar.google.com/citations?user=Kmy27SUAAAAJ&hl=en|
|7||Dr. Sumegh Tharewal||Biometrics, Blockchain, Machine Learning, Artificial Intelligence, pattern recognition||https://scholar.google.com/citations?hl=en&user=1dfdWf8AAAAJ|
|S.N.||Name of the scholar||Name of the supervisor,||Title|
|1||Purohit Neha M||Dr. Shubhalaxmi Joshi||Design and Development of Elliptic Curve Cryptography based Security Framework for Health Care System|
|2||Patil Nishit Bhaskar||Dr. Shubhalaxmi Joshi||Design and Analysis of the Blockchain Model to Assess the Impact on Seed Distribution Ecosystem|
|3||Railkar Dipali Nilesh||Dr. Shubhalaxmi Joshi||Design and Development of Automated Penetration Testing Model for Network Efficacy|
|4||Katyare Poonam Prashant||Dr. Shubhalaxmi Joshi||Productivity Analysis of Construction Equipment using IoT System|
|5||Kamble Nisha Nitin||Dr. Shankar Mali||Design and Analysis of the Blockchain Model to Assess the Impact on Seed Distribution Ecosystem|
|6||Bapat Mayuri Manoj||Dr. Shankar Mali||Towards an automatic early stress detection system based on multimodal measurements|
|7||Meenal Jabade||Dr. C. H. Patil||Air-Written Real Time Multilingual Numeral String Recognition system|
|8||Atiya Khan||Dr. C. H. Patil||Seasonal Crop classification using remote sensing data : An ANN/CNN approach|
|9||Archana Mulapudi||Dr. C. H. Patil||Machine Learning Modeling for Agricultural Drought Assessment using Multisensor Remote Sensing Data|
|10||Idris Khan||Dr. Rajeshree Khande||Title finalization seminar in progress|
|11||Vinay Supekar||Dr. Rajeshree Khande||Title finalization seminar in progress|