Submission of high-quality papers is encouraged, not limited to the specified areas. We welcome a broad spectrum of contributions, ranging from theoretical insights to practical applications, including case studies, works in progress, and conceptual explorations. Additionally, a virtual meeting platform is available for all registered authors who wish to submit their work but are unable to attend the conference in person.

The scope of this conference is broad, and the following topics are covered (but not limited to):

Track 1. Computer Science & Engineering

• Algorithms for AI and Machine Learning 

• Cloud & Edge Computing

• AI enabled Software Engineering 

• Big Data Analytics

• IT Systems Automation 

• Cybersecurity and AI 

• Social Media Analytics

• AI for Blockchain Applications

• AI & Data Science for Healthcare & Agriculture

Track 2 : Electronics and Communication Engineering

• 5G technology & Big Data Applications 

• VLSI, Signal & Image Processing and IoT

• Micro & Nano Materials 

• Robotics & Automation

• Microwave & Wearable Technologies

Track 3: Mechanical Engineering

• Application of AI in Nano Technology

• AI –Enabled Sustainable Green Manufacturing 

• Role of Data Science in Renewable Energy Sources 

• Autonomous Vehicles

• Mathematical Modelling and Optimization

⁠Track 4: Civil Engineering

• Expert Systems for Smart Infrastructure.

• AI Models for Geotechnical and Structural Engineering 

• IoT for Smart Cities and Urban Planning

• Smart Construction Materials

• AI Perspective for Disaster Management and Climate Resilience in Civil Engineering

Track 5. Electrical Engineering

• Electric Power Systems, Smart Grid & Micro Grid

• Power Electronics and its applications 

• Automation & Control Drone Technology 

• AI & ML applications to Electrical Engineering 

• Electric Vehicles.

Track 6. Basic Science and Humanities:

• Role of AI in Pedagogy

• Prediction of Environmental effect of chemicals using AI models 

• Optimization techniques for Mathematical Modelling using ML 

• Quantum Computing in Physics

• Prompt Engineering for innovative teaching and learning methods