The Department of Computer Science & Engineering, Faculty of Engineering and Technology, SRM University Delhi-NCR, Sonepat, organized a workshop on “Role of XAI Approaches in Machine Learning for Enhancing Transparency” on 8th May 2026 in Nandi Hall. The workshop aimed to provide students with knowledge about Explainable Artificial Intelligence (XAI) and its growing importance in developing transparent and trustworthy Machine Learning systems.

The session was conducted by Dr. Nonita Sharma, Associate Professor, Department of Computer Science & Engineering, IGDTUW, Delhi, who shared valuable insights into modern AI technologies and explainability techniques.

Objective of the Workshop

• To introduce students to the concept and significance of Explainable Artificial Intelligence (XAI).
• To enhance understanding of transparency and interpretability in Machine Learning models.
• To create awareness about ethical AI practices and trustworthy AI systems.
• To expose students to real-world applications of XAI in different domains.
• To encourage students to explore research and innovation in Artificial Intelligence and Machine Learning.

Highlights of the Workshop

• Dr. Nonita Sharma explained the importance of XAI in improving transparency and accountability in AI systems.
• The session covered topics such as interpretable Machine Learning models, feature importance, visualization techniques, fairness, bias reduction, and ethical AI.
• Real-world examples and practical applications of XAI in healthcare, robotics, finance, and cybersecurity were discussed.
• Interactive discussions and question-answer sessions made the workshop engaging and informative.
• Students gained exposure to emerging trends and challenges in Artificial Intelligence and Machine Learning.
• Faculty members and students actively participated throughout the session.

Outcomes of the Workshop

• Students developed a clear understanding of Explainable Artificial Intelligence and its applications.
• Participants learned about the importance of transparency and interpretability in Machine Learning systems.
• Awareness regarding ethical AI, fairness, and accountability in AI models was enhanced.
• Students gained knowledge of practical XAI techniques used in industry and research.
• The workshop motivated students to explore advanced research opportunities in AI and Machine Learning.
• Participants improved their analytical and critical thinking skills related to AI technologies.

Conclusion

The workshop on “Role of XAI Approaches in Machine Learning for Enhancing Transparency” was highly informative and beneficial for the participants. The expert session delivered by Dr. Nonita Sharma provided valuable insights into Explainable Artificial Intelligence and its role in building reliable and transparent AI systems.

The workshop successfully enhanced students’ technical knowledge and encouraged them to understand the ethical and practical aspects of Artificial Intelligence. Overall, the event proved to be a successful academic initiative by the Department of Computer Science & Engineering and contributed significantly to the learning and professional development of the students.