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About Faculty


Prof. Sudip Kumar Bhattacharya

Associate Professor

Experience in teaching programming courses in C/C++/Java, Databases and query languages like SQL and PL/SQL ,Data Structures, Algorithm Design, Web technologies like HTML/ JavaScript/CSS/ XML, Theoretical Computer Science subjects like Automata Theory/Compiler Design and Optimizations, management subjects like ERP. Acted as the faculty member of the Continuing Education Cell. Mentored teams for various level programming contests and acted as SPOC from the institute for Smart India Hackathon. Acted as NPTEL mentor for various courses. Experience of coaching for GATE (CS/IT).

Prof. Sudip Kumar Bhattacharya

Employee ID 10120
Date of Joining 18-07-2005
Nature of Association Regular
Department Computer Science and Engineering
Designation Associate Professor
Educational Qualification Ph.D. (Pursuing), M.Tech(CSE), M.Sc.(CS), B.Sc
Contact Number Extension No.: 513, Global Directory No.: 8204
Areas of Interest

Cloud Computing, Parallel Programming, Machine Learning, GPU Computing.

    1. “High Utility Itemset Mining” , Sudip Bhattacharya and Deepty Dubey,IJETAE, ISSN 2250-2459, Volume 2, Issue 8, Aug 2012.
    2. “Cooperative Diversity in Wireless Networks: A Survey”,Manju Lahare, Kauleshwar Prasad, Sudip Bhattacharya., IJSRD, ISSN 2321-0613, Vol 5,Issue 5, 2017.
    3. “A Literature Survey on Software Defined Networks” , Manju Lahare, Kauleshwar Prasad, Sudip Bhattacharya,JETIR,ISSN 2349-5162, Vol 4, Issue 6, June, 2017.
    4. "Comparitive analyisis on scheduling algorithm on cloud computing" in Journal of emerging technologies & innovative research Aug 2018 with Dr. Ramesh Kumar and Ms. Devyani Gunjan
Other Info.

Other Responsibilities:

    SPOC for Smart India Hackathon 2017 , 2018, 2019, 2020

    Co-Editor of  CSE Department magazine – Snapshots.

Felowship/Awards/Other recognitions:

    Qualified UGC-NET (LS) 2012 examinations.

    Internship experience at IIT Delhi on parallel programming with multi-core and multi-processor technologies like openMP, MPI and GP-GPU on NVidia CUDA.