1. Dr Dinesh Kumar, Professor, IIMB, Bengaluru (Research and Academia)
2. Mr. Srinivasan Govindaraju, Member and Head of Data Science, Happiest Minds, Bengaluru (Industry)
3. Mr. Siva Kumar Bale, Program Analyst, Frontier Company, Bengaluru (Parent Representative)
4. Shreeya Gontikonda, 1st Year AIML (Student Representative)
5. Dr Bharathi Malakreddy A, Professor and Head, Dept of AIML, Internal Member
6. Dr Anupama H S, Associate professor, Dept of AIML, Internal Member
7. Dr Santhi Natarajan, Associate professor, Dept of AIML, Internal Member
8. Dr Viswa Kiran S, Assistant Professor, Dept of AIML, Internal Member.

To develop professionals equipped to build sustainable and intelligent solutions that effectively interact with the natural intelligence towards creating a digitally empowered environment for future generations, safeguarding social ethics.

● To enable students with the spirit and power of interdisciplinary acumen by integrating a world of knowledge into a world of intelligent systems and subsystems.
● Boost academic outcome through place-based education and collaborations with established research labs and industries.
● Encourage entrepreneurship efforts among students and develop them into great leaders.

1. Possess essential professional engineering skills that make them confident to develop high-quality AI solutions for various application domains under realistic constraints.
2. Demonstrate the importance of life-long learning through professional development, computing practises, and specialized certifications.
3. Engage and succeed in their professional careers through team work, ethical behaviour, proactive involvement, and effective communication.

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.

1. Ability to apply acquired skills to build optimized solutions adhering to principles and practices of Computational Intelligence.
2. Employ ethical strategies and policies in project and product development.