+91 8100836863   |  admission@mckvie.edu.in
+91 8100836863   |  admission@mckvie.edu.in
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Course Overview
Computer Science and Engineering is a rapidly evolving field shaping modern technology. Foundational principles are taught rigorously, while advanced study explores cutting-edge areas such as AI, Generative AI, NLP, ML, IoT, Cloud Computing, Fullstack Development, Quantum Technology, and Cyber Security, ensuring a balanced blend of theory and practice. The department regularly seeks alumni feedback, enabling alignment with IT and ITeS industry demands. This ongoing process keeps the curriculum relevant, industry-focused, and future-ready. Students and faculty engage in lifelong learning via workshops, seminars, and collaborations. Involvement in IEEE, CSI, IETE, and IEI enriches exposure, while NPTEL/SWAYAM courses help strengthen domain knowledge and keep pace with emerging technologies.

The institution promotes holistic growth through developer clubs, internships, and hackathons. Collaborations with ISRO, DRDO, IITs, and top industries provide real-world experience, fostering innovation and keeping students and faculty ahead in technology.
Intake Capacity
120
Affiliated to
MAKAUT
Approved by
AICTE
Accredited by
NAAC
"A" grade Autonomous Institute under UGC Act. 1956
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Eligibility Criteria for Admission
  • Candidates must have valid WBJEE / JEE (Main) Score.
  • Candidates must have passed the qualifying examination (10+2) with Physics and Mathematics along with Chemistry / Biotechnology / Biology / Computer Science / Computer Applications / Technical Vocational subjects with individual pass marks (in both theory and practical, wherever applicable) in all three subjects as stated above in regular class mode.
  • Candidates must have obtained at least 45% marks (40% in case of SC, ST, OBC, PwD) in all the three subjects taken together. As mentioned in Table 8.4 in AICTE Approval Process Handbook-2024, and as annexed (Appendix-7).
  • Candidates must have passed English in “10+2” examination with at least 30% marks.
  • The board of qualifying examination must be recognized either by the Central or State Government.
  • Both B.Sc. Candidates and Diploma holders in Engineering & Technology will also be eligible for admission to the 1st year Engineering Degree Courses, subject to vacancies in the 1st year classes in case the vacancies as lateral entry at second year are exhausted. However, the admission shall be based strictly on the eligibility criteria as mentioned above.
Our Vision
To be a well-recognized department by providing students with an excellent environment for academics and research in the realm of Computer Science.
Our Mission
  • To provide a conducive atmosphere for the teaching learning process.
  • To make the students understand the role of Computer Science in social and global needs.
  • To develop theoretical knowledge of the students and make them skilled professionals by involving them in application oriented activities, project works and arranging workshops, seminars and industry oriented programs.
  • To facilitate the students in adapting to the changing technologies and to be successful in their professional and research works.
Programme Educational Objective
  • PEO-I: Graduates of the programme will be successful computing professionals.
  • PEO-II: Graduates of the programme will pursue higher education or continuously update their knowledge through lifelong learning.
  • PEO-III: Graduates of the programme will practice their profession by exhibiting effective communication and team work skills.
Programme Outcomes
POs describe what students are expected to know or will be able to do by the time they complete graduation from the program. The Program Outcomes of UG in Computer Science & Engineering are as follows:

  • PO-I: Engineering Knowledge: Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization as specified in WK1 to WK4 respectively to develop to the solution of complex engineering problems.
  • PO-II: Problem Analysis: Identify, formulate, review research literature and analyze complex engineering problems reaching substantiated conclusions with consideration for sustainable development. (WK1 to WK4)
  • PO-III: Design/Development of Solutions: Design creative solutions for complex engineering problems and design/develop systems/components/processes to meet identified needs with consideration for the public health and safety, whole-life cost, net zero carbon, culture, society and environment as required. (WK5)
  • PO-IV: Conduct Investigations of Complex Problems: Conduct investigations of complex engineering problems using research-based knowledge including design of experiments, modelling, analysis & interpretation of data to provide valid conclusions (WK8).
  • PO-V: Engineering Tool Usage: Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including prediction and modelling recognizing their limitations to solve complex engineering problems. (WK2 and WK6)
  • PO-VI: The Engineer and The World: Analyze and evaluate societal and environmental aspects while solving complex engineering problems for its impact on sustainability with reference to economy, health, safety, legal framework, culture and environment. (WK1, WK5, and WK7).
  • PO-VII: Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws. (WK9)
  • PO-VIII: Individual and Collaborative Team work: Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.
  • PO-IX: Communication: Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations considering cultural, language, and learning differences.
  • PO-X: Project Management and Finance: Apply knowledge and understanding of engineering management principles and economic decision-making and apply these to one’s own work, as a member and leader in a team, and to manage projects and in multidisciplinary environments.
  • PO-XI: Life-Long Learning: Recognize the need for, and have the preparation and ability for i) independent and life-long learning ii) adaptability to new and emerging technologies and iii) critical thinking in the broadest context of technological change. (WK8)
Programme Specific Outcomes
  • PSO – I: Demonstrate basic knowledge of modern technologies like Cloud Computing, Artificial Intelligence and Machine Learning, Web based application development and relate the idea of hardware and computation for career paths and zest for higher studies.
  • PSO – II: Design and develop efficient algorithms for engineering problems related to Database, Computer networks and System software by using suitable data structures and emerging tools for software development.
Faculty Members
Mr. Avijit Bose
Assistant Professor and HOD
Computer Science and Engineering
B.E., M.Tech, Ph.D (pursuing)
Teaching : 25 Yrs, Research : 5 Yrs, Industry : 1 yr
Mr. Prasenjit Das
Assistant Professor and Teacher In-charge
Computer Science and Engineering
B.Sc., MCA, M.Tech, Ph.D (pursuing)
Teaching : 18 Yrs, Research : 2 Yrs,
Mr. Puspen Lahiri
Assistant Professor and Teacher In-charge
Computer Science and Engineering
B.Tech, M.Tech, Ph.D (pursuing)
Teaching : 20 Yrs, Research : 1 Yrs,
Dr. Soma Bandyopadhyay
Associate Professor
Computer Science and Engineering
AMIE, M.E., Ph.D (Engg.)
Teaching : 18 Yrs, Research : 5 Yrs, Industry : 2 yr
Dr. Sumana Kundu
Associate Professor
Computer Science and Engineering
BE. M.Tech, Ph.D(Engg)
Teaching : 10 Yrs, Research : 6 Yrs,
Ms. Anwesa Naskar
Assistant Professor
Computer Science and Engineering
B.Tech, M.Tech, PhD (pursuing)
Teaching : 4 Yrs,
Mr. Chandan Roy
Assistant Professor
Computer Science and Engineering
B.Sc. (H), B.Tech, M.Tech
Teaching : 4 Yrs,
Mr. Kaushik Roy Choudhury
Assistant Professor
Computer Science and Engineering
M.Tech, Ph.D (pursuing)
Teaching : 20 Yrs, Research : 2 Yrs, Industry : 2 yr
Ms. Keya Bhattacharjee
Assistant Professor
Computer Science and Engineering
M.Tech (CSE), Ph.D (pursuing)
Teaching : 9 Yrs, Research : 1 Yrs,
Ms. Moumita Goswami
Assistant Professor
Computer Science and Engineering
B.Tech, M.Tech, Ph.D (pursuing)
Teaching : 15 Yrs, Research : 1 Yrs, Industry : 1 yr
Ms. Rachita Ghoshhajra
Assistant Professor
Computer Science and Engineering
B.Tech, M.Tech, Ph.D (pursuing)
Teaching : 22 Yrs, Research : 5 Yrs,
Mr. Sumit Majumdar
Assistant Professor
Computer Science and Engineering
B.Tech, M.E., Ph.D (pursuing)
Teaching : 15 Yrs, Research : 2 Yrs,
Mr. Surojit Bhattacharyya
Assistant Professor
Computer Science and Engineering
B.Tech, M.E., Ph.D (pursuing)
Teaching : 18 Yrs, Research : 3 Yrs,
Student Achievements
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Faculty Contributions
Research and Development Publications (Year 2025-26) Journal Publications
  • S. S. Thakur, S. Bandyopadhyay, M. Thakur, A. Laha, A. Singh, A. K. Singh, S. S. Singh, and S. Mishra, “EDNN-PCXR: Enhanced pediatric chest X-ray classification using fine-tuned deep neural networks,” International Journal of Combinatorial Optimization Problems and Informatics, vol. 16, no. 3, pp. 563–577, Jul. 2025. doi: 10.61467/2007.1558. 2025.v16i3.871.
  • D. De, M. N. Pal, and D. Hazra, “QROP: Quantum learning-based identification of retinopathy of prematurity,” IET Quantum Communication, vol. 6, no. 1, Aug. 2025, Art. no. e70008. doi: 10.1049/qtc2.70008.
  • M. N. Pal and D. De, “FedQCNN: A privacy-preserving federated quantum convolutional neural network for retinal image classification,” IET Quantum Communication, vol. 6, no. 1, Sep. 2025, Art. no. e70010. doi: 10.1049/qtc2.70010.
  • A. Bose, P. Sarkar, P.Jana “Quantifying cloud cost efficiency in federated learning: An empirical comparison with centralized training,” Advances in Artificial Intelligence and Machine Learning, 2026. doi: 10.54364/AAIML.2026.61270.
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