Our Vision

To emerge as a leading department providing competent mechanical engineers to fulfil everchanging needs of industry and society.

Our Mission

Educational Objectives

The integration of Artificial Intelligence (AI) and Machine Learning (ML) with Mechanical Engineering aims to equip students with the interdisciplinary skills needed to address modern engineering challenges. The primary educational objective is to develop graduates who are proficient in mechanical engineering fundamentals while being capable of leveraging AI and ML technologies to innovate and optimize engineering systems.

Students will acquire a solid foundation in core mechanical subjects such as thermodynamics, fluid mechanics, mechanics of materials, manufacturing processes, and design of machine elements. Alongside, they will learn the principles of AI/ML including supervised and unsupervised learning, neural networks, data analysis, and computational intelligence. This combined knowledge allows students to model, simulate, and control mechanical systems more efficiently using data-driven techniques.

Another key objective is to promote problem-solving, analytical thinking, and innovation. Students will be encouraged to apply AI/ML tools for predictive maintenance, smart manufacturing, automation, robotics, energy optimization, and system design. They will be trained to work with real-world datasets, interpret results meaningfully, and develop intelligent systems that adapt to dynamic environments.

Teamwork, communication, and ethical responsibility form an integral part of the program’s objectives. Graduates will be prepared to collaborate across disciplines, effectively communicate technical ideas, and consider ethical implications of deploying AI-based solutions in engineering contexts.

Ultimately, the program aspires to produce engineers who are not only technically competent but also capable of lifelong learning, adaptable to emerging technologies, and ready to contribute to the development of intelligent, efficient, and sustainable mechanical systems in industry and research.

Let me know if you'd like a version focused more on career outcomes, curriculum structure, or specific AI/ML tools used.

Program Educational Objectives (PEOs)

PROGRAM SPECIFIC OUTCOMES (PSO)

Career Opportunities

Graduates with expertise in Mechanical Engineering integrated with AI and ML are equipped for a wide range of cutting-edge roles across various industries. Their combined knowledge of physical systems and intelligent computing makes them highly valuable in sectors focusing on automation, smart manufacturing, and advanced system design.

Student Outcomes

Proficiency in mechanical system design enhanced with AI/ML techniques, including modeling, simulation, and optimization of complex engineering systems.

Integration of sensors, actuators, controllers, and intelligent algorithms to develop automated and adaptive mechanical or mechatronic systems.

Teamwork and collaboration in multidisciplinary settings, especially across mechanical, electronics, computer science, and data domains.

Competence in modern engineering and computational tools such as CAD, CAM, MATLAB, Python, ROS (Robot Operating System), PLC, SCADA, and AI/ML frameworks (e.g., TensorFlow, PyTorch).

Ethical decision-making and awareness of sustainability issues, considering the societal and environmental impact of intelligent mechanical systems.

Ability to design and conduct experiments, analyze real-time data, and draw meaningful inferences to improve system performance.

Effective communication skills for conveying technical information clearly to both technical and non-technical audiences through reports, presentations, and collaborative tools.

Preparedness for lifelong learning, research, and higher education, with the ability to independently adapt to evolving technologies in mechanical engineering, AI, and Industry 4.0.

Key Highlights

Campus Facilities

Software

Advanced Lab for Research, Innovation & Training