Vision & Mission:

Vision:

To empower learners to become experts in Artificial Intelligence and Data Science through persistent excellence in learning and fostering innovations in a rapidly evolving technological world.

Mission:

M1: To prepare graduates for successful careers in Artificial Intelligence and Data Science through a continuous process of learning and creating opportunities in AI world.
M2: To cultivate innovations, ethical responsibilities and interdisciplinary collaborations among the students to address real-world problems and contribute to the betterment of society.
M3: We, the faculty and the staff strive hard to strengthen students with the strong academic background, experiential learning, effective communication skills, self-discipline and moral values to thrive in the ever-challenging computing world.

Faculty:

1. Faculty List:

2. Faculty Members:

Photo	Faculty name and description
	Name:Dr. A. R. Panhalkar Designation : Associate Prof & H.O.D Qualification : M.E.(Comp),Ph.D Exp Teaching (yrs): 19 Years Exp Industrial (yrs) : NIL Area of Specialization:Cloud Computing, Computer Networking, Network Security Biodata: Read More
	Name:Ms. S. G. Dighe Designation : Assistant Professor Qualification : M.E.(Electronics), Ph.D-Pursuing Exp Teaching (yrs): 13 Years Exp Industrial (yrs) : NIL Area of Specialization:Digital System,Internet of Things Biodata:Read More
	Name:Mr. S. P. Shinde Designation : Assistant Professor Qualification : M.E.(Comp), Ph.D-Pursuing Exp Teaching (yrs): 12 Years Exp Industrial (yrs) : NIL Area of Specialization:Data Science, Hadoop Biodata:Read More
	Name:Mrs. J. R. Tambe Designation : Assistant Professor Qualification : M.tech.(CSE), Ph.D-Pursuing Exp Teaching (yrs): 9.6 years Exp Industrial (yrs) : 3.4 Years Area of Specialization:Data Structures,Computer Vision Biodata:Read More
	Name:Mr. R.B. Pandit Designation : Assistant Professor Qualification : M.E.(Comp), Ph.D-Pursuing Exp Teaching (yrs): 03 Years Exp Industrial (yrs) : 11 Years Area of Specialization:DBMS, Data Science Biodata:Read More
	Name: Mr. Mundhe B.B. Designation : Assistant Professor Qualification : M.E. (AI&DS) Experience Teaching (yrs) : 5 Years Experience Industrial (yrs) : 4 Years Area of Specialization : Artificial Intelligence, Software Testing, Data Science, Python Programming Biodata :Read More
	Name:Mr. S.C. Patil Designation :Assistant Professor Qualification :ME.(Computer Engineering) Exp Teaching (yrs):4 years Exp Industrial (yrs):4 Years Area of Specialization:Data Mining Techniques And Applications, Computer Network, Cyber Security, cloud computing, Digital Marketing Biodata :Read More
	Name:Ms. Nawale S. N. Designation : Assistant Professor Qualification : M.E(Comp) Exp Teaching (yrs): 5 Years Exp Industrial (yrs) : Nill Area of Specialization:Software Engineering, Artificial Intelligence,Big data. Biodata:Read More
	Name:Ms.R.R.Tribhuvan Designation : Assistant Professor Qualification : MTech(Comp) Exp Teaching (yrs): 2 Years Exp Industrial (yrs) : 1 Years Area of Specialization:Machine Learning, Data Science Biodata:Read More
	Name :Mrs.Vaishali Anil Naikwadi Designation : Assistant Professor Qualification : M.E (IT) Exp Teaching (yrs): 06 Months Exp Industrial (yrs) :4.5 Yrs Area of Specialization:Software Development Biodata:Read More
	Name:Ms. Rahane N. A. Designation : Assistant Professor Qualification : M.E(Comp) Exp Teaching (yrs): Nill Exp Industrial (yrs) : Nill Area of Specialization:Machine Learning, Artificial Intelligence Biodata:Read More

3. Supporting Staff:

Photo	Faculty name and description
	Name:Mrs. Supriya Shivram Ghule Designation : Technical Assistance Qualification : B.E(Comp) Exp Industrial (yrs) :4
	Name:Mr. Akshay Somnath Rahane Designation :Technical Assistant Qualification :Diploma(Comp) Exp Industrial (yrs) :3 Years
	Name:Ms. Shital Sonyabapu Bhalerao Designation :Lab Assistant Qualification : B.C.A Exp Industrial (yrs) : 8 years
	Name:Mr. Somnath Sudam Bhutambare Designation:Peon Qualification: 12 th Arts

Syllabus:

UG:

Sr. No.	2019 Course	2024 Course
1.	FE Common	FY.BTech (Autonomy)
2.	SE AIDS	SE AIDS
3.	TE AIDS
4.	BE AIDS

Achievements:

1. Faculty:

2. Students:

Activities:

1. AIESA activities

2. Alumni Interactions

3. Industrial Visits:

4. Value Added Courses:

5. Guest Lectures Organized

Program Educational Objectives(PEO's):

1. PEO1. To develop competent graduates with a strong foundation in Artificial Intelligence and Data Science methodologies and algorithms, capable of solving complex real-world problems by applying appropriate modern tools and techniques to design and develop effective solutions.

2. PEO2. To exhibit leadership qualities of graduates by successfully guiding teams, managing projects, and leveraging communication skills to create a positive impact on organizations and society.

3. PEO3. To adopt a lifelong learning approach by consistently enhancing knowledge and skills to remain at the forefront of the rapidly evolving field, while adapting to new technologies, addressing challenges with environmentally sustainable solutions, and upholding ethical practices.

Program Specific Outcomes(PSO's)

A graduate of the Computer Engineering Program will demonstrate-

1. PSO1: Professional Skills-The ability to understand, analyse and develop computer programs in the areas related to algorithms, system software, multimedia, web design, big data analytics, and networking for efficient design of computer-based systems of varying.

2. PSO2: Problem-Solving Skills- The ability to apply standard practices and strategies in software project development using open-ended programming environments to deliver a quality product for business success.

3. PSO3: Successful Career and Entrepreneurship- The ability to employ modern computer languages, environments, and platforms in creating innovative career paths to be an entrepreneur, and a zest for higher studies.

Program Outcomes(PO's):

Students are expected to know and be able –

1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
2. Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
3. Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations
4. Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
10. Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
11. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
12. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

Student List: (2025-2026)