Registration summary
ConferenceICAMS
ModeStandard / Physical
ParticipationListener
Registration fee$195.00
Bank charges (5.8%)$11.31
Total payable$206.31
Includes all bank processing charges — the amount above is exactly what will be charged.
Benefits of Registering as Listener
Access to Conference Sessions
Networking Opportunities
Certificate of Participation
Invitation Letter Support
Conference Kit / Materials
Access to Keynote Sessions
• Conference Session Tracks •
SDG-Aligned Research Themes
ICAMS conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.
01 Advanced Statistical Methods in Applied Mathematics +
This track focuses on the development and application of advanced statistical techniques in various fields of applied mathematics. Participants will explore innovative methodologies that enhance data analysis and interpretation.
02 Data Science Techniques for Predictive Modeling +
This session will delve into the latest data science techniques used for predictive modeling in real-world applications. Emphasis will be placed on the integration of machine learning algorithms and statistical methods.
03 Numerical Methods and Their Applications +
This track will cover a range of numerical methods used to solve complex mathematical problems. Discussions will include their applications in engineering, physics, and finance.
04 Statistical Learning and Big Data Analytics +
Participants will examine the intersection of statistical learning and big data analytics, focusing on techniques that facilitate the extraction of insights from large datasets. Case studies will highlight practical applications across various domains.
05 Mathematical Modeling in Science and Engineering +
This session will explore the role of mathematical modeling in solving scientific and engineering problems. Attendees will discuss various modeling techniques and their effectiveness in real-world scenarios.
06 Bayesian Methods in Applied Statistics +
This track will focus on the application of Bayesian methods in statistical analysis and decision-making. Participants will explore both theoretical foundations and practical implementations of Bayesian approaches.
07 Optimization Techniques in Data Science +
This session will highlight optimization techniques that are essential in data science for improving model performance. Discussions will include both linear and nonlinear optimization methods.
08 Statistical Inference and Hypothesis Testing +
This track will cover the principles of statistical inference and hypothesis testing, emphasizing their importance in applied mathematics. Participants will engage in discussions on recent advancements and methodologies.
09 Time Series Analysis and Forecasting +
This session will focus on time series analysis techniques and their applications in forecasting future trends. Participants will explore various models and their effectiveness in different contexts.
10 Data Visualization and Interpretation +
This track will emphasize the importance of data visualization in the interpretation of complex datasets. Participants will learn about various tools and techniques for effective data presentation.
11 Ethics in Data Science and Statistical Practice +
This session will address the ethical considerations in data science and statistical practice. Discussions will focus on responsible data use, privacy concerns, and the implications of statistical findings.
