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Hybrid Event

9th - 10th July 2026 | Phuket, Thailand

International Conference on Stochastic Simulation Techniques and Applications (ICSSTA - 26)

4

Days

4

Hrs

07

Min

02

Sec

Conference Program

Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

Why it matters

SDG 8 — Decent Work and Economic Growth
SDG 9 — Industry, Innovation and Infrastructure
SDG 12 — Responsible Consumption and Production
SDG 16 — Peace, Justice and Strong Institutions
SDG 17 — Partnerships for the Goals
Explore All Session Tracks
Track 01
Advancements in Stochastic Simulation Techniques

This track focuses on the latest methodologies in stochastic simulation, emphasizing innovative techniques that enhance computational efficiency. Researchers are invited to present their findings on new algorithms and frameworks that improve simulation accuracy and speed.

Track 02
Monte Carlo Methods in Complex Systems

This session explores the application of Monte Carlo methods in modeling complex systems across various fields. Participants will discuss advancements in algorithmic approaches and their implications for probabilistic modeling.

Track 03
Probabilistic Modeling in Real-World Applications

This track highlights the role of probabilistic modeling in addressing real-world challenges. Contributions should focus on case studies and applications that demonstrate the practical utility of probabilistic approaches.

Track 04
Random Processes and Their Applications

This session delves into the theory and applications of random processes in diverse domains. Researchers are encouraged to present their work on the implications of random processes in understanding complex phenomena.

Track 05
Statistical Computing and Simulation Tools

This track aims to showcase advancements in statistical computing tools that facilitate stochastic simulation. Discussions will center on software developments, computational techniques, and their impact on research productivity.

Track 06
Queueing Systems: Theory and Applications

This session focuses on the theoretical foundations and practical applications of queueing systems. Participants are invited to share insights on modeling, analysis, and optimization of queueing processes in various industries.

Track 07
Risk Analysis and Management through Stochastic Models

This track addresses the integration of stochastic models in risk analysis and management. Researchers will present methodologies that enhance risk assessment and decision-making processes in uncertain environments.

Track 08
Algorithms for Stochastic Optimization

This session explores novel algorithms designed for stochastic optimization problems. Contributions should focus on theoretical advancements and practical implementations that improve optimization outcomes.

Track 09
Applications of Applied Probability in Industry

This track highlights the application of applied probability in various industrial contexts. Participants are encouraged to present case studies that illustrate the impact of probabilistic methods on operational efficiency.

Track 10
Emerging Trends in Stochastic Simulation Research

This session aims to identify and discuss emerging trends in stochastic simulation research. Researchers are invited to share their perspectives on future directions and potential breakthroughs in the field.

Track 11
Interdisciplinary Approaches to Stochastic Modeling

This track emphasizes the importance of interdisciplinary approaches in stochastic modeling. Contributions should highlight collaborations across fields that leverage stochastic techniques to solve complex problems.

2026 UPDATE

Consistent Academic Support

Science Net ensures that research activities continue without interruption in the current global situation. Participants can engage through digital and hybrid conference formats.