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

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

India's top engineering universities have been awarded fellowships under the IndiaAI Mission's FutureSkills initiative, recognizing students working on AI projects that bridge the gap between theory and practice. The fellowships were awarded to students from various institutions, showcasing innovative applications of AI and ML across various fields, including healthcare, education, and security and privacy.

Kumud Sahni Pruthi by Kumud Sahni Pruthi
Friday, 3 January 2025, 20:59 PM
in News
IndiaAI's B.Tech and M.Tech fellowships draw a diverse pool of applications

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. 

Also Read: Rajeev Chandrasekhar announces 10 AI labs in Thiruvananthapuram Colleges under India AI Mission

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. 

Also Read: India AI Mission: 10,000 Crores Funds for GPUs and STPI Initiatives

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. 

Also Read: 3 AI Centers of Excellence Launched in India for Sustainable Cities, Agriculture, and Healthcare

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.

Click here to know in detail list.

Also Read: Apply Now: NVIDIA Graduate Fellowship Offering Up to $60,000 for PhD Students

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Kumud Sahni Pruthi

Kumud Sahni Pruthi

A postgraduate in Science with an inclination towards education and technology. She always looks for ways to help people improve their lives by putting complex things into simple words through her writing.

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