Date: 6th & 7th May 2026 | Time: 8.00 am – 12:00 pm (IST) | Location: Online
Overview
The International Conference on Applied Probability, Stochastics & Decision Science brings together mathematicians, engineers, economists, and data scientists to discuss the latest developments in probabilistic modeling, stochastic processes, and decision theory. The conference promotes an interdisciplinary understanding of uncertainty quantification, optimization, and real-world applications across engineering, finance, operations research, and analytics. It serves as a platform for sharing analytical techniques and simulation models that enhance decision-making under uncertainty in complex, dynamic systems.
Structure and Sessions (Who Does What)
Participate and Contribute (Who Benefits)
Benefits for Attendees
Abstract Topics / Call for Papers (CFP) Tracks
Detailed Program Grid
| Time (IST) | Day 1 | Day 2 |
| 08:00 – 08:15 | Opening Ceremony & Welcome | Recap and Opening Remarks |
| 08:15 – 09:00 | Keynote: Modeling Randomness in Real-World Systems | Keynote: Decision Theory and Stochastic Optimization |
| 09:00 – 10:15 | Technical Session I – Probability & Stochastic Processes | Technical Session IV – Optimization & Decision Science Models |
| 10:15 – 10:30 | Break | Break |
| 10:30 – 11:15 | Technical Session II – Simulation & Reliability Analysis | Technical Session V – Game Theory and Applied Decision Analytics |
| 11:15 – 11:45 | Panel Discussion: Bridging Stochastics and Data-Driven Decision-Making | Student & Research Forum: Applied Probability & Modelling Approaches |
| 11:45 – 12:00 | Day Summary & Announcements | Awards & Closing Ceremony |
Submit Abstract & Registration
| Conference Dates | Conference Title | Timing (IST) | Abstract Submission Deadline | Registration Deadline |
| 6th, 7th May 2026 | International Conference on Applied Probability, Stochastics & Decision Science | 8:00 AM – 12:00 PM | 27th April 2026 | 29th April 2026 |
Abstract Guidelines
Conclusion
This international conference unites theorists and practitioners to advance research in randomness, uncertainty, and decision frameworks. Participants will explore innovative strategies to model stochastic systems, optimize performance, and enhance quantitative analysis in engineering, economics, and technology.