Date: 15th & 16th July 2026 | Time: 9.00 am – 12:00 pm (IST) | Location: Online
Overview:
The International Conference on Mathematics and Data Science Applications brings together mathematicians, data scientists, statisticians, and industry experts to explore mathematical foundations powering AI, machine learning, and big data analytics. The conference focuses on optimization techniques, probabilistic modeling, topological data analysis, and real-world applications in predictive analytics, finance, healthcare, and sustainability, fostering interdisciplinary solutions for complex data challenges.
Structure and Sessions (Who Does What):
Participate and Contribute (Who Benefits):
Benefits for Attendees :
Abstract Topics / CFP (Call for Papers) Tracks:
Detailed Program Grid (2 Half Days – 8 AM to 12 PM)
| Time | Day 1 | Day 2 |
| 08:00 – 08:15 | Opening Ceremony & Welcome | Recap and Opening Remarks |
| 08:15 – 09:00 | Keynote: Math Powering AI Innovation | Keynote: Big Data Optimization Frontiers |
| 09:00 – 10:15 | Technical Session I – Optimization & Graphs | Technical Session IV – Applications & Ethics |
| 10:15 – 10:30 | Break | Break |
| 10:30 – 11:15 | Technical Session II – Statistics & Topology | Technical Session V – Future Directions |
| 11:15 – 11:45 | Panel Discussion: Data Science Governance | Student & Research Forum |
| 11:45 – 12:00 | Day Summary & Announcements | Awards & Closing Ceremony |
Submit Abstract & Registration :
| Conference Dates | Conference Title | Timing (IST) | Abstract Submission Deadline | Registration Deadline |
| 15th & 16th July 2026 | International Virtual Conference on Mathematics and Data Science Applications | 8:00 AM – 12:00 PM (IST) | 26th Jan 2026 | 28th Jan 2026 |
10:30 AM – 2:30 PM (SGT/CST/JST) | 12:30 PM – 4:30 PM (AEST – Australia) | 3:30 AM – 7:30 PM (BST – UK) | 9:30 PM – 1:30 AM (EST-US&Canada)
Abstract Guidelines:
Conclusion:
This conference bridges pure mathematics with data science innovation, empowering researchers to develop robust algorithms and models for AI-era challenges, promoting sustainable and ethical data applications across industries.