Welcome to the Faculty Development Program

ABOUT FDP

Deep learning, a subset of artificial intelligence (AI), leverages neural networks with multiple layers to model complex patterns and representations in data. Inspired by the structure of the human brain, these networks learn from vast amounts of information, identifying intricate patterns that traditional algorithm might miss. Deep learning has revolutionized various fields, from image recognition to natural language processing, by enabling computers to perform tasks that previously required human intelligence.

In academics and research, deep learning has become a transformative tool. It assists researchers in processing massive datasets, allowing for faster and more accurate data analysis in fields such as biology, physics, and social sciences. For instance, deep learning algorithms can analyze genomic data, detect anomalies in medical imaging, and predict complex chemical interactions, all of which accelerate scientific discovery. In the humanities, deep learning aids in deciphering ancient texts and understanding linguistic trends.

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Our upcoming Faculty Development Program (FDP) aims to equip faculty members with foundational and advanced knowledge of AI and deep learning, focusing on their transformative applications in academics and research. This program will provide an overview of deep learning principles, showcase practical applications in fields like data analysis, medical research, and education, and explore how these technologies can enhance teaching and personalized learning. Through interactive sessions, hands-on workshops, and knowledge-sharing discussions, faculty members will gain valuable insights and skills to leverage AI and deep learning in their own academic work, quality publications in journals and patents and fostering a culture of innovation and interdisciplinary collaboration.

OBJECTIVES

  • Introduce fundamental concepts of AI and deep learning relevant to academic and research contexts.
  • Demonstrate practical applications of deep learning across diverse fields, including data analysis and education.
  • Equip faculty with tools and techniques for implementing AI-driven solutions in research projects.
  • To promote quality research publications and familiarise with process of IPR and patent filing.
  • Foster a collaborative environment for knowledge exchange and interdisciplinary research innovation.
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Registration fees for the participants:

Interested participants can apply using the link https://www.jimsindia.org/fdp/. Candidates are required to register on or before 30th December 2024. All participants have to pay a registration fee of Rs 500 while filling up the registration form. For any other query, participants can email and seek guidance at [email protected].

Program Schedule

6th to 10th January 2025
Date Resource Person Session 1 (9.30am- 11:30am ) Session 2 (12:00pm -02:00pm)
Jan-06 Dr. A.K. Mohapatra (HOD-IT, IGDTUW) Artificial intelligence Cyber Security
Jan-07 Dr Aman Jatain (Profesor, SOET, KR Mangalam University) Artificial Intelligence Artificial Intelligence
Jan-08 Dr Anuradha Chug (Associate Professor, USICT) Deep learning and Diffusion Matrix Deep learning and Diffusion Matrix
Jan-09 Dr Ajay Singholi (Director, GGSIPU, East Campus) Robotics Robotics
Jan-10 Dr Mithilesh Kumar Dubey (Professor, Lovely Professional University) Research motivation and insights on paper publication in Sci indexed journals IPR and Copyrights

Eligibility

This programme is open to the faculty members AICTE approved Engineering and Management Colleges, Polytechnic Colleges, Research Scholars from industry/Universities and research organizations.

FDP Brochure

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Duration & Venue

  • FDP will be organized in offline mode from 6th to 10th January 2025
  • Venue: Jagan Institute of Management Studies, Sector-5, Rohini, Delhi 110085
  • No TA will be provided to the participants.
  • For outside Delhi participants, stay at hostel can be provided at nominal charges.
    Participants need to make a formal request for the same via email to the organizer at least 10 days in advance.