IndiaAI’s B.Tech and M.Tech fellowships draw a diverse pool of applications

Students enrolled in B.Tech. and M.Tech. programs at India’s best engineering universities were eligible to apply for fellowships under the IndiaAI Mission’s FutureSkills initiative. 

Fellowship consideration was given to students who work on AI projects, bridging the gap between theory and practice and guaranteeing a workforce with fundamental AI capabilities. 

There were 110 M.Tech and 280 B.Tech nominations for the IndiaAI Fellowship program. Twelve M.Tech students and seventy-seven B.Tech students received grants. 

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Which Universities were chosen for B.Tech grant?

Reputable technological universities responded favorably to the B.Tech grant. Among the organizations that applied were Aligarh Muslim University, Sri Sivasubramaniya Nadar College of Engineering, S.R.M. Institute of Science and Technology, and the Indian Institute of Technology (IIT) Kharagpur. The following universities were chosen to receive the fellowship: 

• Chandigarh University,
• Amity University,
• Visvesvaraya Technological University,
• Dr. B.R. Ambedkar National Institute of Technology, Jalandhar,
• IIT Hyderabad,
• IIT (BHU) Varanasi,
• IIT Guwahati,
• IIT Roorkee, and
• IIT Madras.

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Which Universities were chosen for M.Tech grant?

There were several prominent institutions that participated in the M.Tech fellowship. Among the universities selected for the grant were 

• the Indian Institute of Technology (IIT) Kharagpur,
• Indian Institute of Space Science and Technology,
• Dr B.R. Ambedkar National Institute of Technology, Jalandhar,
• Indian Institute of Technology Gandhinagar,
• National Institute of Technology Calicut,
• the Indian Institute of Technology Roorkee,
• the Defence Institute of Advanced Technology, and
• the Indian Institute of Technology Madras.

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What are the Project themes and areas of focus?

The B.Tech fellowship submissions showcased a wide range of innovative projects that demonstrated the broad applications of AI and ML across multiple fields. For example, the use of AI in healthcare was a prominent theme, with many projects focusing on improving medical diagnostics, disease detection, and personalized treatment. These projects included AI-driven systems for early disease detection, medical image segmentation, and even applications in cancer treatment, highlighting how AI can improve healthcare outcomes and accessibility. 

Education was another important area of focus, with several projects exploring the potential of AI to create more inclusive and adaptive learning environments. The M.Tech fellowship submissions focused on the application of AI for environmental and sustainability challenges, autonomous systems and robotics, and security and privacy.

Several key themes emerged from the submitted projects, reflecting innovation in multiple domains. The M.Tech fellowship submissions focused on the application of AI, ML, and data analysis to address a wide range of real-world problems. One prominent area was speech recognition and natural language processing (NLP), with multiple projects focused on language-specific AI systems. For example, there were attempts to design and implement Automatic Speech Recognition (ASR) systems tailored for Tamil and Marathi, with the goal of improving accessibility and communication in regional languages.

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