Introduction

The Department of Electrical and Electronics Engineering organized a One-Day Seminar on “Artificial Intelligence Approaches to Assess Wide Bandgap Device Integration in Electrical Machines” on 20th April 2026 at the 5th Floor Conference Room, Engineering Block. The seminar was conducted with the objective of providing students and faculty members with insights into emerging advancements in electrical machines, power electronics, and Artificial Intelligence (AI)-driven technologies.

The expert session was delivered by Dr. Shubham Sundeep from the Department of Electrical Engineering, Indian Institute of Technology Delhi, who shared his expertise on the integration of wide bandgap semiconductor devices in modern electrical machines and the role of AI techniques in their assessment and optimization.

Objectives of the Seminar

• To provide awareness about emerging advancements in wide bandgap semiconductor device technologies used in electrical machines.
• To introduce participants to the application of Artificial Intelligence (AI) techniques in the assessment and optimization of electrical systems.
• To enhance understanding of the integration of Silicon Carbide (SiC) and Gallium Nitride (GaN) devices in modern electrical engineering applications.
• To familiarize students and faculty members with current research trends and technological developments in power electronics and electrical machines.
• To encourage academic interest and research-oriented learning in the areas of AI-driven electrical system analysis and intelligent energy technologies.

Event Overview

Dr. Shubham Sundeep from the Department of Electrical Engineering, Indian Institute of Technology Delhi delivered a highly insightful and technically enriching presentation on “Artificial Intelligence Approaches to Assess Wide Bandgap Device Integration in Electrical Machines.” The session provided participants with an in-depth understanding of emerging semiconductor technologies and their applications in modern electrical systems.

The major highlights of the presentation included:

• Introduction to Wide Bandgap Devices:
Dr. Sundeep explained the fundamentals of wide bandgap semiconductor devices such as Silicon Carbide (SiC) and Gallium Nitride (GaN), highlighting their advantages over conventional silicon-based devices in terms of higher switching frequency, improved efficiency, reduced power losses, and superior thermal performance.
• Integration Challenges in Electrical Machines: The session discussed key technical challenges associated with integrating wide bandgap devices into electrical machines, including parasitic effects, electromagnetic interference (EMI), high-voltage insulation stress, and thermal management complexities.
• Role of Artificial Intelligence in Electrical Systems: Special emphasis was placed on the application of Artificial Intelligence (AI), Machine Learning (ML), and neural network-based approaches for:
• Predicting device behavior under varying operating conditions.
• Optimizing inverter–machine integration and system performance.
• Enabling real-time condition monitoring and fault diagnosis.
• Performing thermal profiling and lifetime estimation of electrical components.
• Research and Industrial Applications: Dr. Sundeep also shared insights into current research developments, simulation methodologies, and industry-oriented applications of AI-driven electrical system analysis.

The session was highly interactive, with participants actively engaging in discussions and raising queries related to practical implementation, simulation tools, industrial adoption, and future research opportunities. Dr. Sundeep’s ability to effectively connect theoretical concepts with real-world engineering applications was highly appreciated by the attendees.

Conclusion

The One-Day Seminar on “Artificial Intelligence Approaches to Assess Wide Bandgap Device Integration in Electrical Machines” was a great success and proved to be highly informative and academically enriching for all participants. The seminar effectively achieved its objectives by:

• Providing faculty members, researchers, and students with valuable insights into emerging wide bandgap (WBG) semiconductor technologies and AI-based assessment techniques used in modern electrical machines.
• Enhancing participants’ understanding of advanced concepts related to power electronics, intelligent monitoring systems, and AI-driven optimization methods.
• Strengthening the department’s academic and research focus on emerging areas such as power electronics, electric drives, smart energy systems, and intelligent electrical technologies.
• Encouraging research-oriented learning and fostering awareness about the growing industrial relevance of AI applications in electrical engineering.

The Department of Electrical and Electronics Engineering expresses its sincere gratitude to Dr. Shubham Sundeep from Indian Institute of Technology Delhi for delivering an insightful and engaging session. The active participation of faculty members, and students contributed significantly to the success of the seminar.