This track focuses on the latest developments in survival modeling techniques, emphasizing innovative approaches to time-to-event data analysis. Researchers are encouraged to present novel methodologies and applications in various fields, including healthcare and engineering.

This session will explore reliability analysis methodologies applicable to engineering systems, including failure time data modeling and risk assessment. Contributions that integrate statistical methods with engineering principles are particularly welcome.

This track aims to discuss statistical inference techniques specifically tailored for hazard models, including estimation and hypothesis testing. Participants are invited to share their insights on the challenges and solutions in this area.

This session will highlight the role of biostatistics in epidemiological studies, focusing on survival analysis and time-to-event data. Contributions that bridge the gap between statistical theory and public health practice are encouraged.

This track will cover simulation methodologies used in reliability studies, including Monte Carlo methods and bootstrap techniques. Presentations should demonstrate the practical application of these techniques in real-world scenarios.

This session will explore the integration of machine learning techniques with survival analysis, focusing on predictive modeling and risk assessment. Researchers are invited to present case studies that illustrate the effectiveness of these approaches.