MECHANICAL ENGINEERING (BTECH)
Overview
The Department of Mechanical Engineering at Marwadi University is dedicated to producing “future-ready engineers” by integrating cutting-edge technologies such as Artificial Intelligence (AI) and Machine Learning (ML) into its curriculum and research. This alignment with Industry 4.0 is evident in their commitment to equipping students with skills in smart technologies, data analytics, automation, and the Internet of Things (IoT), all of which are underpinned by AI and ML.
The university emphasizes an outcome-based education model that evolves with industry demands. Although specific AI/ML courses within Mechanical Engineering are not explicitly detailed, the curriculum is designed to promote interdisciplinary learning, ethical innovation, and lifelong skill development. Mechanical Engineering students are encouraged to explore AI and ML applications through electives, projects, and research opportunities.
Advanced labs such as those for Robotics and Advanced Manufacturing provide a platform for applying AI/ML in areas like predictive maintenance, automation, and intelligent systems. While AI/ML labs are more formally established in the Computer Engineering and Computer Science departments, Mechanical Engineering students benefit from cross-departmental collaborations and access to state-of-the-art infrastructure and software tools.
Marwadi University’s broader institutional focus on AI/ML further supports this integration. The university offers B.Tech programs specifically in AI & ML and AI & Data Science, reflecting its strong foundation in the domain. Faculty across departments, including Mechanical Engineering, actively pursue research in AI/ML applications across various sectors such as healthcare, agriculture, robotics, and automation.
In summary, through a forward-thinking curriculum, collaborative research, and access to modern labs and interdisciplinary expertise, Marwadi University effectively integrates AI and ML into its Mechanical Engineering program, preparing students to excel in a rapidly evolving technological landscape.
The university emphasizes an outcome-based education model that evolves with industry demands. Although specific AI/ML courses within Mechanical Engineering are not explicitly detailed, the curriculum is designed to promote interdisciplinary learning, ethical innovation, and lifelong skill development. Mechanical Engineering students are encouraged to explore AI and ML applications through electives, projects, and research opportunities.
Advanced labs such as those for Robotics and Advanced Manufacturing provide a platform for applying AI/ML in areas like predictive maintenance, automation, and intelligent systems. While AI/ML labs are more formally established in the Computer Engineering and Computer Science departments, Mechanical Engineering students benefit from cross-departmental collaborations and access to state-of-the-art infrastructure and software tools.
Marwadi University’s broader institutional focus on AI/ML further supports this integration. The university offers B.Tech programs specifically in AI & ML and AI & Data Science, reflecting its strong foundation in the domain. Faculty across departments, including Mechanical Engineering, actively pursue research in AI/ML applications across various sectors such as healthcare, agriculture, robotics, and automation.
In summary, through a forward-thinking curriculum, collaborative research, and access to modern labs and interdisciplinary expertise, Marwadi University effectively integrates AI and ML into its Mechanical Engineering program, preparing students to excel in a rapidly evolving technological landscape.
Vision
To emerge as a leading department providing competent mechanical engineers to fulfil everchanging needs of industry and society.
MISSION
To deliver quality education to the students and empower them to compete at national and global level To train students on current and advanced technologies through academic and industrial engagements To promote research and innovation through academic, infrastructural, and financial support To make students understand the impact of their work on society and practice ethical values To motivate and prepare students for higher education, employment, and entrepreneurship 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
PEO 1: Core Engineering Competence
Graduates will build a strong foundation in mechanical engineering integrated with AI/ML, enabling them to analyze, design, and optimize complex systems across core and interdisciplinary domains.
PEO 2: Lifelong Learning and Higher Education
Graduates will pursue lifelong learning and advanced education to stay current with evolving technologies in mechanical engineering and AI/ML.
PEO 3: Professionalism and Ethics
Graduates will demonstrate professionalism, integrity, and ethical responsibility, considering societal and environmental impacts in AI-integrated mechanical solutions.
PEO 4: Societal and Environmental Impact
Graduates will develop intelligent, sustainable mechanical solutions using AI/ML to address societal needs, enhance quality of life, and support eco-friendly innovation.
Program Specific Outcomes
PSO 1: Technical Proficiency
Graduates will demonstrate technical proficiency in core mechanical engineering principles and effectively integrate AI and ML techniques to analyze, design, model, and optimize mechanical systems. They will be capable of applying modern tools, programming skills, and data-driven approaches to solve real-world engineering problems.
PSO 2: Innovation and Societal Impact
Graduates will apply innovative thinking and AI/ML-enabled engineering solutions to address contemporary societal and industrial challenges. They will contribute to the development of sustainable, intelligent technologies that improve quality of life, support environmental responsibility, and drive positive change in society.
Eligibility Criteria
| For Indian and International Students | ||
|---|---|---|
| As per ACPC Guidelines |
Admission Process
Through Admission Committee for Professional Courses (ACPC)
Once you generate the PIN from the bank through an online or offline process,
Once you generate the PIN from the bank through an online or offline process,
Register yourself on
Fill the Application Details
Choice Filling
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(1, 2, 3..)
(1, 2, 3..)
You’re on the path to DISCOVER yourself
Reporting at College
Actual Admission and Token Fee Payment
Admission Process
Through Admission Committee for Professional Courses (ACPC) Once you generate the PIN from the bank through an online or offline process,
Register
yourself on
yourself on
Fill the
Application
Details
Application
Details
Choice
Filling
Filling
Mock
Rounds
(1, 2, 3..)
Rounds
(1, 2, 3..)
Actual
Admission
and Token
Fee Payment
Admission
and Token
Fee Payment
Reporting at
College
College
You’re on the
path to DISCOVER
yourself
path to DISCOVER
yourself
Duration and Fees Structure
The Bachelors of Technology in Mechanical Engineering with AI & ML is a 4 year course comprising eight semesters
| For Indian Student (INR) | ||
|---|---|---|
| Mechanical Engineering AI & ML | 4 Years | 55000/- (Per Sem) |
| For International Student (USD) | ||
|---|---|---|
| Mechanical Engineering AI & ML | 4 Years | 1600/- (Annual) |
Curriculum
Mechanical Engineering with Specialization in AI & ML
Sem 1
Sem 2
Sem 3
Sem 4
Sem 5
Sem 6
Sem 7
Sem 8
Sem 1
| B. Tech. Year I, Sem I | Evaluation Scheme | |||||||||||
| Subject code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | |||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term work (TW) | |||||
| 01MA2101 | Differential and Integral Calculus | BSC | 3 | 2 | 0 | 5 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01CE0101 | Computer Programming | ESC | 4 | 0 | 2 | 5 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01ME1101 | Elements of Mechanical Engineering | ESC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01SL1104 | Professional Communication | HSMC | 2 | 0 | 0 | 2 | 50 | 30 | 20 | 0 | 0 | 100 |
| 01GS2101 | Engineering Physics | BSC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01EN1101 | Basics of Environmental Studies | ESC | 2 | 0 | 0 | 0 | 50 | 30 | 20 | 0 | 0 | 100 |
| 01CR1103 | Value Education | HSMC | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 50 | 50 | 100 |
| 01CR0105 | Verbal Ability-1 | HSMC | 1 | 0 | 0 | 0 | 50 | 0 | 0 | 0 | 50 | 100 |
| 01GS0103 | Indian Constitution | HSMC | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Total | 27 | 21 | 2 | 6 | 20 | 300 | 180 | 120 | 175 | 225 | 1000 | |
Sem 2
| B. Tech. Year I, Sem II | Evaluation Scheme | |||||||||||
| Subject code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | |||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term work (TW) | |||||
| 01MA0103 | Matrix algebra and vector calculus | BSC | 3 | 2 | 0 | 5 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01ML0101 | Python Programming | ESC | 0 | 0 | 4 | 2 | 0 | 0 | 0 | 50 | 50 | 150 |
| 01ME1102 | Engineering Graphics | ESC | 3 | 0 | 4 | 5 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01EE2101 | Basics of Electrical and Electronics Engineering | ESC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01ME1104 | Mechanical Workshop | ESC | 0 | 0 | 2 | 1 | 0 | 0 | 0 | 0 | 50 | 100 |
| 01CR0106 | Verbal Ability – 2 | HSMC | 1 | 0 | 0 | 0 | 50 | 0 | 0 | 0 | 50 | 100 |
| 01ML0202 | Fundamental of AI & ML | ESC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | Total | 30 | 13 | 2 | 14 | 21 | 250 | 120 | 80 | 200 | 250 | 900 |
Sem 3
| B. Tech. Year II, Semester III | Evaluation Scheme | |||||||||||
| Subject code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | |||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term work (TW) | |||||
| 01ME1305 | Fundamental of Machine Design | ESC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01MA1301 | Applied Differential Equations | BSC | 3 | 2 | 0 | 5 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01ML0101 | Fluid Mechanics & Hydraulic Machines | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01ME2302 | Kinematics of Machines | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01ML0301 | Manufacturing Technolgy | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01CR0302 | Quantitative & Logical Ability – 1 | HSMC | 1 | 0 | 0 | 1 | 50 | 0 | 0 | 0 | 50 | 100 |
| 01ML0301 | Python Programming for AI & ML | ESC | 0 | 0 | 4 | 2 | 0 | 0 | 0 | 50 | 50 | 100 |
| Total | 30 | 16 | 2 | 12 | 24 | 300 | 150 | 100 | 175 | 225 | 950 | |
Sem 4
| B. Tech. Year II, Semester IV | Evaluation Scheme | |||||||||||
| Subject code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | |||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term work (TW) | |||||
| 01MA1401 | Complex Variable & Numerical Analysis | BSC | 3 | 2 | 0 | 5 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01ML2401 | Machine Design & Industrial Drafting | PCC | 4 | 0 | 2 | 5 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01ME2403 | Material Science and Metallurgy | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01ME1404 | Engineering Thermodynamics | PCC | 3 | 2 | 0 | 5 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01ML0401 | Data Science | Skill | 0 | 0 | 4 | 2 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01ME0406 | Creativity, Problem Solving and Innovation | HSMC | 0 | 0 | 2 | 1 | 0 | 30 | 20 | 0 | 0 | 50 |
| 01CR0402 | Quantitative & Logical Ability – 2 | HSMC | 0 | 0 | 2 | 1 | 50 | 0 | 0 | 0 | 50 | 100 |
| Total | 29 | 13 | 4 | 12 | 23 | 300 | 180 | 120 | 125 | 175 | 900 | |
Sem 5
| B. Tech. Year III, Semester V | Evaluation Scheme | ||||||||||||
| Subject code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | ||||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term work (TW) | ||||||
| 01ML0501 | Dynamics of Machine | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01ML0502 | Machine Design | PCC | 3 | 2 | 0 | 5 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01ME0504 | Metrology | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01ML0503 | Machine Learning | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01CR0503 | Quantitative & Logical Ability – 3 | HSMC | 1 | 0 | 0 | 1 | 50 | 0 | 0 | 0 | 50 | 100 | |
| 01ML0504 | Automation and Control Systems | PCC | 0 | 0 | 4 | 2 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01ME051* | Programme Elective I | PCE | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| Total | 30 | 16 | 2 | 12 | 24 | 350 | 180 | 120 | 150 | 200 | 1000 | ||
| Programme Elective – I | |||||||||||||
Sem 6
| B. Tech. Year III, Semester VI | Evaluation Scheme | ||||||||||||
| Subject code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | ||||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term work (TW) | ||||||
| 01ML0601 | Deep Learning | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01ME1602 | Heat Transfer | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01ML0602 | Soft Computing | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01ML0603 | Machine Vision | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01ML062* | Programme Elective II | PCE | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01ME0612 | Basics of Pneumatics and Hydraulics | Skill | 0 | 0 | 2 | 1 | 0 | 0 | 0 | 50 | 50 | 100 | |
| 01CR0602 | Quantitative Aptitude and Verbal Ability | HSMC | 1 | 0 | 0 | 1 | 50 | 0 | 0 | 0 | 50 | 100 | |
| Total | 28 | 16 | 0 | 12 | 22 | 300 | 150 | 100 | 175 | 225 | 950 | ||
Programme Elective – II
| |||||||||||||
Sem 7
| B. Tech. Year IV, Semester VII | Evaluation Scheme | ||||||||||||
| Subject code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | ||||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term work (TW) | ||||||
| 01ML0701 | Advanced Computational Method for Mechanical System | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01ML0702 | Operation Management with AI/ML | PCE | 2 | 0 | 4 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01ML0703 | Robotics | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01ML073* | Programme Elective – III | PEC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01ML074* | Programme Elective – IV | PEC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| Total | 26 | 14 | 0 | 12 | 20 | 250 | 150 | 100 | 125 | 125 | 750 | ||
Programme Electives – III
| |||||||||||||
Programme Electives – IV
| |||||||||||||
Sem 8
| B. Tech. Year IV, Semester VIII | Evaluation Scheme | |||||||||||
| Subject code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | |||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term work (TW) | |||||
| 01ML0801 | Internship/Project | Project | 0 | 0 | 30 | 15 | 0 | 0 | 0 | 100 | 100 | 200 |
| Total | 0 | 0 | 30 | 15 | 0 | 0 | 0 | 100 | 100 | 200 | ||
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.
AI/ML Engineer (Mechanical Focus)
Design & Simulation Engineer
Robotics Engineer
Smart Manufacturing Engineer (Industry 4.0)
Product Development Engineer
Data Analyst/Engineer in Engineering Firms
Control Systems Engineer
Research and Development (R&D)
Higher Education & Academics
Entrepreneur/Startup Founder
AI/ML Engineer (Mechanical Focus) Design & Simulation Engineer Robotics Engineer Smart Manufacturing Engineer (Industry 4.0) Product Development Engineer Data Analyst/Engineer in Engineering Firms Control Systems Engineer Research and Development (R&D) Higher Education & Academics Entrepreneur/Startup FounderCareer Options
Graduates of Mechanical Engineering with specialization in Artificial Intelligence and Machine Learning are prepared for a wide range of dynamic and high-impact roles across industries. Potential career paths include:
Systems Engineer
Solutions Specialist
Product Engineer
Technical Designer
Software QA Analyst
Programmer Analyst
System Architect
Data Analytics Professional
IoT-Based Solutions Developer
Software Engineer
Embedded
Hardware/
Software Engineer
Cybersecurity Analyst
AI/ML Engineer
Database Technology Specialist
Wireless and Sensor Networks Engineer
Image and Video Processing Engineer
VLSI Systems Designer
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.Facilities
Lab
Marwadi University is creating professionals and innovators for the future through exclusively sourced equipment available only at other top universities of India.
With reference to the Final assessment of Marwadi University Material Testing Laboratory in the disciplines of Mechanical Testing conducted by National Accreditation Board for Laboratories (NABL) in June 2017, NABL has evaluated the assessment report and decided grant of accreditation in accordance with ISO/IEC 17025:2005 in the disciplines of Mechanical Testing as per the scope and authorized signatories recommended by the assessment team. With this accreditation, Marwadi University becomes the 1st university in Gujarat, to have a NABL accredited Civil Engineering Material Testing Laboratory which are very few in the country
Fluid Mechanics
Refrigeration & Air-conditioning
Heat Transfer
Fluid Power Engineering
I. C. Engine
Dynamics of Machines
Material Science & Metallurgy
Metrology
Element of Mechanical Engineering
Mechanical workshop
Advanced Laboratories
Computer Aided Manufacturing
Computer Aided Design
With reference to the Final assessment of Marwadi University Material Testing Laboratory in the disciplines of Mechanical Testing conducted by National Accreditation Board for Laboratories (NABL) in June 2017, NABL has evaluated the assessment report and decided grant of accreditation in accordance with ISO/IEC 17025:2005 in the disciplines of Mechanical Testing as per the scope and authorized signatories recommended by the assessment team. With this accreditation, Marwadi University becomes the 1st university in Gujarat, to have a NABL accredited Civil Engineering Material Testing Laboratory which are very few in the country
Fluid Mechanics Refrigeration & Air-conditioning Heat Transfer Fluid Power Engineering I. C. Engine Dynamics of Machines Material Science & Metallurgy Metrology Element of Mechanical Engineering Mechanical workshopAdvanced Laboratories
Computer Aided Manufacturing Computer Aided Design 
Software
PTC’s Creo for Design MATLAB/Simulink for Modeling and Simulation Python & ROS for Robotics Programming PLC Programming for Automation ANSYS for System AnalysisAdvanced Lab for Research, Innovation & Training
Smart Foundry supported by DST, Govt. of India Bosch Rexroth Center of Excellence in Automation Rapid Prototyping Lab Automation Training with Jyoti CNC Automation Pvt. Ltd. Advance Robotics Lab 
Campus Facilities
Impressive Infrastructure IT Enabled Infrastructure Sports Infrastructure State-of-the-art Classrooms Hostels with Gymnasium Library with 50000+ Books Academic & Cultural Events Industry Association
Membership of Professional Bodies
HOD's Message
Prof. (Dr.) Ramesh Bhoraniya
HoD, Department of Mechanical Engineering
HoD, Department of Mechanical Engineering
It gives me immense pleasure to welcome you to the Department of Mechanical Engineering with Artificial Intelligence and Machine Learning. This unique interdisciplinary program aims to build a strong foundation in core mechanical engineering while integrating advanced knowledge of AI and ML—technologies shaping the future of engineering.
In today’s tech-driven era, the fusion of mechanical systems with intelligent computing is revolutionizing industries through smart manufacturing, robotics, predictive maintenance, and sustainable innovation. Our department is committed to developing engineers who can design systems that not only function—but learn, adapt, and evolve.
We emphasize experiential learning, innovation, and industry engagement. Through hands-on projects, research, and real-world applications, our students grow as ethical professionals and creative problem-solvers.
Supported by a dedicated faculty, modern labs, and an industry-relevant curriculum, our program bridges traditional engineering with emerging digital trends. We welcome you to explore this transformative journey and become part of tomorrow’s intelligent engineering solutions.
In today’s tech-driven era, the fusion of mechanical systems with intelligent computing is revolutionizing industries through smart manufacturing, robotics, predictive maintenance, and sustainable innovation. Our department is committed to developing engineers who can design systems that not only function—but learn, adapt, and evolve.
We emphasize experiential learning, innovation, and industry engagement. Through hands-on projects, research, and real-world applications, our students grow as ethical professionals and creative problem-solvers.
Supported by a dedicated faculty, modern labs, and an industry-relevant curriculum, our program bridges traditional engineering with emerging digital trends. We welcome you to explore this transformative journey and become part of tomorrow’s intelligent engineering solutions.
Faculties of Mechanical Engineering
Dr. Rameshkumar Bhoraniya
Professor, HoD
Dr. Amit Sata
Professor
Dr. Nikunj Rachchh
Professor
Dr. Pinak Patel
Associate Professor
Dr. Bhavesh Kanabar
Associate Professor
Dr. Nikhil Chotai
Associate Professor
Dr. Gaurang Joshi
Associate Professor
Dr. Parag Rajpara
Associate Professor
Dr. Karan Motwani
Associate Professor
Dr Jomy Joseph
Associate Professor
Mr. JIGNESH JANI
Assistant Professor
Mr. Chandreshkumar Vyas
Assistant Professor
Mr. Puneet Mathur
Assistant Professor
Mr. PRASHANT UJENIYA
Assistant Professor
Mr. Dhaiwat Trivedi
Assistant Professor
Mr. Dhaval Anadkat
Assistant Professor
Dr. MIT SHETH
Assistant Professor
Mr. NIKUNJ MASHRU
Assistant Professor
Mr. MUKHTAR SAMA
Assistant Professor
Mr. Kartik Pipalia
Assistant Professor
Dr Shalok Bharti
Assistant Professor
Mr. BHAVIK VAGHASIA
Assistant Professor
Mr. Mayank Thummar
Assistant Professor
MR. BHAVIK VAGHASIA
Lab Assistant
Mechanical Department Placement
Department Newsletter
December 2024
June 2024
December 2023
June 2023
December 2022
June 2022
December 2021
December 2024
June 2024
December 2023
June 2023
December 2022
June 2022
December 2021
Key Highlights
State-of-the-Art Facilities and Hands-on Learning Integration of Industry 4.0 and Emerging Technologies Quality Assurance through Accreditation Robust Industry Partnerships and Research Collaborations Curriculum Focused on Advanced Fields Comprehensive Student Outcomes Active Student Engagement Industry Internships at Bosch, Jyoti CNC, and Adani Robotics Competitions & Club Activities (e.g., ASME, IEEE) Holistic skill development: from Design to DeploymentFaculties
Successful
Alumni
Our Recruiters
Events
Teaching and Learning
The faculty members of the Mechanical Engineering Department at Marwadi University are trained and certified in Teaching-Learning Pedagogy through various platforms, including MOOCs, Faculty Development Programs, workshops, and initiatives by IUCEE (Indo Universal Collaboration for Engineering Education). These certification programs expose participants to diverse pedagogical methods and learning styles. The department implements an activity-based curriculum designed to simplify and effectively teach complex concepts. This curriculum emphasizes imparting skills and knowledge to students through interactive tasks and activities.
The faculty of the Department of Mechanical Engineering at Marwadi University employs various active learning strategies, which can be broadly classified as follows:
Project Based Learning Flipped Classroom Experimental Learning Peer Group Learning Technological Learning Skill Oriented Learning Case Studies Group Projects Collaborative Learning Support for Slow Learners Project Based Learning
Experimental Learning
Simulation Based Learning
Flipped Classroom
Virtual Lab
Virtual Lab
FAQ
Q. Is there any Loan Facility Available ?
There are various kinds of scholarships and financial aid available at MU. Marwadi University has made special arrangements with State Bank of India, Bank of India, Central Bank of India, HDFC Bank and other private Banks for speedy sanctioning and dispersal of Educational and Student Loan to students taking admission.
https://mcuniversity.in/student-loan/
https://mcuniversity.in/student-loan/
Q. Is there any Scholarship Available ?
A student can avail various scholarships and financial aids at MU. There are International Scholarships, GATE Scholarship, Vidhyalaxmi Yojana, GPAT Scholarship, and alike. You can contact the University and get all the guidance related to Student Loan.
https://mcuniversity.in/student-loan/
https://mcuniversity.in/student-loan/
Q. How is the Placement at Marwadi University ?
Marwadi University provides 100% Placement Assistance and Opportunities. So much so that in the previous academic year, we hosted more than 480 companies for placement. If the students are dedicated enough with regular work and follow-ups, they are sure to receive placement in well-known companies with a worthy package. You can contact the Placement and Corporate Relations Department and go through Placement News to know more about it.
Q. How to Reach MU ?
Marwadi University is located on Rajkot-Morbi Road. You can take a city bus to Madhapar Chowk and from there, a Rickshaw Ride will drop you to Marwadi University which is a landmark known by all local drivers. It is 10 km from Bus Station, 12 km from Airport, and 10 km from Railway Station. You can easily find it on Google Maps if you want to self-drive to the University.
Q. Is there a Hostel Facility available at Marwadi University ?
Yes, Marwadi University has 6 hostels with a capacity of more than 3500 students. Many National and International students stay here and feel at home. There are ample facilities available at MU hostel. You can inquire about the hostel when you take admission and get accommodated in your new home.
Q. What is the Fee Structure of Degree Programmes at Marwadi University ?
Fee Structure at Marwadi University is different across various courses at UG and PG level. You can contact the Admission Department for knowing the Fees Structure of various courses offered at MU.
Q. How to Apply for Admission at Marwadi University? What form to fill ?
You can apply online by filling the Application form to start your admission process. If you do not want to fill the application online, you can visit the University for walk-in admissions anytime.
Q. Is Marwadi University recognised by the Government ?
Marwadi University is UGC (University Grants Commission) approved/listed. You can find the name of Marwadi University under the list of UGC approved Universities. MU is also the only institute that is given the NAAC A+ grade in Gujarat.
Q. What all Documents are necessary to bring in while joining the University ?
While you come for admissions, you need to carry your HSC and SSC results, school leaving certificate, JEE score card & registration slip (ACPC). We advise you to keep originals along with photocopies of the same. If you are taking admissions for a Master’s degree, you need to also keep the Bachelor’s Degree Certificate and Marksheet, and any other examination’s scorecard if applicable along with the previously mentioned documents. (GATE score, CMAT, CAT score, GPAT score)
Q. Is there any Medical Facility provided ?
Yes, first-aid medical kits and assistance are available on campus. There is also an ambulance available 24/7 to take students off campus for any kind of emergency.
International Airport 
Railway Station 
GSRTC Bus Port 
