UNIVERSITY OF MANAGEMENT AND TECHNOLOGY

Academic Programs

Program Overview

Robotics and Intelligent Systems has its foundation in Electrical Engineering, Mechanical Engineering, Computer Science, Control theory, Artificial Intelligence, Mathematics, and Modern Engineering Techniques. The MS in Robotics & Intelligent Systems (MS-RIS) program aims to produce highly skilled professionals focused on research, development, and innovation in robotics and intelligent autonomous systems.

The MS-RIS program offers an understanding of both the breadth of interdisciplinary education and depth of specialized training required for leadership roles in Robotics and Intelligent Systems. The program is designed in line with current industrial trends and research needs, covering areas such as robot kinematics and dynamics, machine learning, artificial intelligence, computer vision, advanced control systems, embedded systems, and smart manufacturing.

The program provides graduates with strong theoretical foundations and practical skills necessary for productive employment in industry, research and development organizations, and for further study towards doctoral degrees in robotics, intelligent systems, and related engineering disciplines.

Program Objectives

The objectives of the MS Robotics & Intelligent Systems program are to prepare graduate students for careers in professional practice, research, and advanced studies. The program aims to develop the following competencies in graduates:

  1. Knowledge of fundamental engineering principles relevant to robotics and intelligent systems.
  2. Knowledge of current developments and contemporary societal issues related to automation and intelligent technologies.
  3. Knowledge of state-of-the-art information technologies, artificial intelligence, and robotics tools.
  4. Broad education necessary to understand the impact of robotic and intelligent system solutions in a global, economic, environmental, and societal context.
  5. Ability to facilitate systems engineering and project management.
  6. Ability to communicate effectively in written, verbal, and presentation forms.
  7. Ability to grow through lifelong acquisition of knowledge and skills.
  8. Ability to design robotic systems, components, or processes to meet desired needs within realistic constraints such as economic, environmental, social, ethical, health and safety, manufacturability, and sustainability.
  9. Ability to identify, formulate, and solve complex robotics and intelligent systems engineering problems.

10. Ability to function effectively in multidisciplinary teams.

11. Capability to use state-of-the-art engineering and computer tools necessary for professional practice or research.

12. Skills to locate, evaluate, and use relevant technical information.

13. Ability to design and conduct experiments, simulations, and tests, and to analyze and interpret data.

14. Ability to evaluate and apply modern robotics, control, and artificial intelligence techniques.

Career Prospects

Robotics and Intelligent Systems is a rapidly growing and high-impact field with strong demand across multiple sectors. Graduates of the MS-RIS program are well positioned for careers in robotics, automation, artificial intelligence, and intelligent manufacturing.

Career opportunities include roles in robotic system design, automation and control, intelligent manufacturing, embedded systems, computer vision, AI and machine learning, unmanned systems, healthcare and rehabilitation robotics, and research and development organizations. Graduates may also pursue doctoral studies and academic or industrial research careers.

Admission Criteria

  1. Educational Qualification
    Applicants must have 16 years of formal educationin any of the following disciplines:
    • Robotics and Intelligent Systems
    • Electrical Engineering
    • Computer Engineering
    • Computer Science
    • Mechanical Engineering
    • Mechatronics Engineering
    • Information Technology
  2. Entry Test Requirement
    Candidates must qualify any oneof the following:
    • GRE / GAT / NTS (General)
    • UMT Graduate Admission Test
    Shortlisted candidates will be required to appear in an Admission Interview conducted by the UMT Graduate Admission Committee.
  3. Minimum Academic Requirement
    Minimum 50% marks in the previous degree (Annual System) or a minimum 2.00 CGPA (Semester System) from a recognized degree-awarding institution.
  4. Additional Requirements
    Any other requirement as specified by the Department or the relevant Regulatory Body.

MS Robotics & Intelligent Systems Roadmap – Spring 2026

Semester (1st)

CodeCourse TitleCHPre-req
RIS-XXX Core-I 3 – – – –
RIS-XXX Core-II 3 – – – –
RIS-XXX Elective-I 3 – – – –
RIS-XXX Elective-II 3 – – – –

Semester (2nd)

CodeCourse TitleCHPre-req
RIS-XXX Core-III 3 – – – –
RIS-XXX Elective-III 3 – – – –
RIS-XXX Elective-IV 3 – – – –
RIS-XXX Elective-V 3 – – – –

Semester (3rd)

CodeCourse TitleCHPre-req
RIS-XXX Thesis or Elective VI 3 – – – –

Semester (4th)

CodeCourse TitleCHPre-req
RIS-XXX Thesis or Elective VII 3 – – – –

Total Credit Hours: 30

List of Core Courses:

  • Robot Kinematics (RIS701)
  • Machine Learning (EE731)
  • Research Methodology (ME704)

List of Electives:

  • Kinematics and Dynamics of Robots (RIS702)
  • Analysis of Mechanisms
  • Computer Aided Engineering Design (RIS703)
  • Mechanical Engineering Modeling and Analysis (RIS704)
  • Sustainable Product Design (RIS705)
  • Mechatronics Systems (RIS706)
  • Finite Element Methods (RIS707)
  • Advanced Manufacturing Processes (RIS708)
  • Computer Integrated Manufacturing (RIS709)
  • Mechanical Vibration (RIS710)
  • Advanced Stress Analysis (RIS711)
  • Structural Optimization (RIS712)
  • Artificial Intelligence for Design (RIS713)
  • Embedded Systems (RIS714)
  • Deep Learning (RIS715)
  • Computer Vision (RIS716)
  • Advanced Control Systems (RIS717)
  • Natural Language Processing (RIS718)
  • Human Machine Interaction (RIS719)
  • Generative AI and Applications (RIS720)
  • Smart Manufacturing and IoT (RIS721)
  • Adaptive Control (RIS722)
  • Digital Twin Systems (RIS723)
  • Cognitive Robotics (RIS724)
  • Data Acquisition and Control (RIS725)
  • Unmanned Aircraft Systems (RIS726)
  • Reinforcement Learning (RIS727)
  • Generative Deep Models (RIS728)
  • Augmented and Virtual Reality (RIS729)
  • Robotic Grasping and Fixturing (RIS730)
  • Rehabilitation and Assistive Robotics (RIS731)
  • Legged Robotics (RIS732)
  • Robot Design (RIS733)
  • Bio Robotics (RIS734)
  • Medical Devices and Robotics (RIS735)
  • Modern Brain-Machine Interfaces (RIS736)
  • Human Robot Interaction (RIS737)
  • Simultaneous Localization and Mapping (RIS738)
  • Modern Motion Planning Techniques (RIS739)

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