Data-Efficient and Interpretable Computer Vision

The Department of Computer Science and Engineering at Green University of Bangladesh is pleased to announce a special seminar titled “Towards Data-Efficient and Interpretable Computer Vision: Advances in Few-Shot Learning and Explainable AI.” This seminar is designed to provide students and faculty members with valuable insights into modern research directions in computer vision, particularly focusing on how models can learn efficiently with limited data and offer transparent decision-making through explainable AI techniques.

The event will be held on Sunday, 10 August 2025, starting at 10:20 AM, in the Multi-purpose Hall of Green University of Bangladesh. The seminar is mandatory for all sections of the Machine Learning and Machine Learning Lab courses that have scheduled classes during this time. Students must attend the session, and faculty members are kindly requested to consider this seminar as part of regular class attendance.

We are honored to welcome Prof. Dr. Mohammad Shorif Uddin, Vice-Chancellor of Green University of Bangladesh, as the Keynote Speaker and Chief Guest. The session will be chaired by Prof. Dr. Md. Ahsan Habib, Chairperson of the Department of CSE, GUB. Their presence will provide both inspiration and academic value to all attendees.

This seminar is organized by the IEEE Computer Society Student Branch Chapter, GUB, and co-organized by the IEEE Student Branch, GUB, in association with the IEEE Computer Society Bangladesh Chapter. The collaboration of these professional bodies reflects the significance of the topic and the relevance to the current technological landscape.

Faculty members are requested to share the seminar details and the official event banner in their course classrooms to inform and encourage student participation. We look forward to an engaging session that not only deepens our understanding of data-efficient learning and model interpretability but also inspires students to explore advanced research areas in computer vision.