Dr. K. B. Shiva Kumar is a professor and the head of the Department of Computer Science and Engineering, DBIT, Bangalore. He received a BE degree in Electronics and Communications in 1983 followed by an ME in Electronics in 1989. Thereafter, he earned an MBA from Bangalore University in 1998 and an M.Phil from Dravidian University, Kuppam in 2009. He also has a Ph.D. in Computer Science from Fakir Mohan University, Balasore, Orissa.

Dr. Kumar has his work published in over 160 plus publications in international journals and conferences. Additionally, he has authored a book on Covert Communications. He has served for 38 years as a professor and HOD of Engineering and Technology at SSIT, Tumkur. 

Don Bosco Institute of Technology

What is the latest program that you are offering in your institute/dept. which will help students outperform and stand apart from the crowd.

There are two programs which we have started recently, Artificial Intelligence and Machine Learning, and Artificial Intelligence and Data Science. The first program is offered under the Department of Computer Science and Engineering while the second is an independent branch. Due to the all pervasive nature of Artificial Intelligence, we expect the students graduating from this branch to stand out from their peers. In our opinion, the demand in the employment market for these branches would sustain for the next two decades before it gets into a sort of balance in the supply chain. 

What are the factors that make this program the best for the students to opt?

We have several factors working for us that make our courses attractive. AI technology is all pervasive across multiple domains of application. By opting for these UG programs and getting knowledge about specific domains of application, students are securing their way to a bright future. They are also able to manage any sort of risk that might occur in the AI industry since the two programs being offered are closely related to CSE. 

What are the best practices in the course you’re offering?

For the program on artificial intelligence and machine learning, we are closely associated with a leading multinational company who have AI and ML as a significant vertical. Through this collaboration, we can get industry problem statements for our students to work on during their final and sophomore years. Alongside the curriculum, we also offer value-added courses in embedded intelligence, which is highly prevalent. Assimilation of this practice would place our students in specific niche areas many of which are still, not fully, explored.

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What are some valuable insights of the program that you are offering at your institute/dept.?

As parts of the two programs mentioned above, we teach our students the Anatomy of AI. Students learning programming languages with a specific focus on Python. The curriculum covers data structures with an emphasis on complex structures which are used by AI applications. Our students also have knowledge of allied technologies like cloud computing, microservices, public cloud services and other technologies which are useful to practice AI. There is also a focus on practical application development based on industry statements of the problems. Another major portion of the syllabus includes Mathematical foundations for the AI domain with a focus on Linear Algebra and Probability and Statistics.

How does the program ensure that students are being prepared for the future?

Fundamentally, the very nature of this discipline of this course is futuristic. However, it involves a lot of effort being spent on developing technologies behind AI. In future, serious applications may have to get built many of which might even be safety critical. We are working in this direction to prepare our students for future requirements in the space of AI. Identifying industry problems in AI, packetizing them into smaller worklets and getting them executed by our students is the essence of our effort in preparing them for future needs.

What are the types of projects that the students are working on through this program?

Our students work on several type of projects during their final year and sophomore. Most projects are about building hardware and software infrastructure for data collection. This would lead to training set generation for building AI applications. This activity would, invariably, employ IoT-based hardware. They also build and deploying machine learning application software for specific requirements besides creating deep learning application on cloud platforms (GCP).

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What are the benefits and career options after pursuing this course?

Most of the job profiles our students opt for after undergoing either of the two programs indicated are domain specific in data collection and organizing them for AI applications, programming for an AI application, predominantly using Python. Others have found employment in the deployment of AI applications, mostly, cloud-based and intensive testing of AI applications, especially, while building safety-critical applications. There has also been a rise in jobs in the specialized software architecture for AI application development and middle ware development upon which AI applications can be developed