Follow Us:

Research &
Innovation














AI Lab

Today, an increasing number of firms across all sectors rely on artificial intelligence approaches to drastically improve their goods, operations, and services. The usage of these technologies, such as machine learning, necessitates cutting-edge technology and highly qualified personnel. The expansion of artificial intelligence is hampered by a severe dearth of competent workers and a lack of crucial technologies in the form of a laboratory in many businesses. In these Labs, academics from several disciplines collaborate with professionals from public and commercial companies, governments, and other knowledge institutions to create new knowledge and applications. Artificial intelligence (AI), one of the most essential digital future subjects, is now witnessing a significant increase in all disciplines of science, economics, technology, health care, and entertainment. Despite its initial peak in the 1950s, its present success can be attributed to the rapid advancement of computer technology. Thus, current hardware accelerators such as graphics processing units (GPUs) can now manage large amounts of data (Big Data) in an effective and efficient manner. Many businesses throughout the world have already recognised the immense potential of AI.

Our theme-based Labs focus on particular areas such as transportation, health, and animal welfare, and contribute directly to relevant AI solutions while emphasizing ethics and openness. We are contributing to a greater alignment of education and professional practice by working closely together in the AI Labs with academics and field specialists.

The AI Lab's Objective

  1. To discover novel research directions in Artificial Intelligence, Deep Learning, Machine Learning, and Big Data Analytics.
  2. To encourage students to submit research articles, patents, and launch start-ups on campus/university.
  3. Trained to integrate Students, developers, data scientists, and researchers to creates a multidisciplinary environment.
  4. To develop and deploy distributed systems for information exploitation, collaboration, and decision making.
  5. Data-intensive agent-based solutions provide students and professors with high-quality education and practical skills.
  6. To assist in developing ties with industry for internships, summer jobs, publications, and student placements.
  7. Create, improve, and implement tactics to spread the concept across students and educators.