Aims and Objectives
Faculty development in computer science and engineering focuses on enhancing pedagogical effectiveness, strengthening subject knowledge, and promoting the adoption of modern teaching methodologies. It aims to keep educators aligned with recent technological advancements, ensuring that curricula remain current and relevant. Additionally, it encourages research engagement, industry collaboration, and the integration of emerging technologies into teaching practices, thereby fostering a dynamic and responsive academic environment.
Faculty Development Program: 2026–27
FDP on Research Excellence in AI Era: Latex for Research Documentation and Publication
Five-Day Online Faculty Development Programme (FDP) on “Research Excellence in AI Era”, was organized by the Department of Electrical Engineering, JIET, Jodhpur, from August 24 to 29, 2026. One of the area of deliberation was application of Latex Tools for research documentation and publication.
Faculty Development Program: 2025–26
FDP on Data Science: Deep Learning and AI
This faculty development session was delivered at the Department of Computer Science and Engineering, MBM University during the PM-USHA sponsored FDP on Data Science (23–30 March 2026). The lecture focused on Generative AI and Large Language Models, discussing their foundations, applications, and implications for teaching, research, and industry.
FDP on Image Processing and Computer Vision
These sessions were conducted at the Department of Computer Science and Engineering, MBM University under the PM-USHA sponsored FDP on "Image Processing and Computer Vision” (7–12 July 2025). The lecture presented a comprehensive overview of machine learning, tracing its evolution from basic neural networks to modern deep learning architectures.
Deep Learning and Visual AI
Faculty Development Program: 2023-24
FDP topic: Generative AI
This program explored Generative AI: Opportunities and Challenges, providing insights into emerging AI technologies and their applications in education and research. It also addressed practical challenges, ethical considerations, and strategies for integrating generative AI into academic environments.