Machine Learning (ML) is rapidly evolving beyond traditional computer science and becoming a powerful catalyst for innovation across multiple disciplines. At the national level, these trends align with strategic priorities in digital transformation, sustainable development, smart infrastructure, and data-driven governance.
By fostering collaboration between domain experts, researchers, and industry, interdisciplinary machine learning is enabling scalable solutions, enhancing decisionmaking, and driving inclusive technological growth. This convergence is shaping a skilled workforce and strengthening the nation’s research, innovation, and economic ecosystem.
Abstract for paper can be emailed to etiami@sxca.edu.in Kindly ensure that your abstract title should be the subject of email and the format should be in Times New Roman, font size 12 with four to five key words in italics at the end of the abstract. The abstract should be within 150-200 words. The title should be in capital letters and bold font, followed by names of all the authors and addresses of affiliated institutions. The name of the corresponding author should be in bold. The first author will be considered as the presenting author unless specified otherwise. The details of the corresponding author should be mentioned. Each author requires to register individually. Details of oral presentation and poster presentation format will be communicated post abstract acceptance.
| Category | National | International | ||
| Early Bird | Regular | Early Bird | Regular | |
| Industrialist | ₹ 2300 | ₹ 2600 | 34 USD | 39 USD |
| Scientist / Academicians | ₹ 1800 | ₹ 2100 | 28 USD | 34 USD |
| Research Scholars | ₹ 1000 | ₹ 1300 | 19 USD | 28 USD |
| Student / Conference Attendee | ₹ 800 | ₹ 1100 | 17 USD | 19 USD |
Last Updated on: January 3,2026
