International Conference on Applied Mathematics in Climate and Environmental Studies

ICAMCLES

21st Sep – 22nd Sep 2026 Kota Kinabalu, Malaysia

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Registration Summary

Conference ICAMCLES

Date 21st Sep – 22nd Sep 2026

Location Kota Kinabalu, Malaysia

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

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Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Mathematical Modeling of Climate Systems +

This track focuses on the development and application of mathematical models to understand complex climate systems. Participants will explore various modeling techniques and their implications for climate change predictions.

SDG 13 SDG 15 SDG 17

02 Statistical Methods in Environmental Data Analysis +

This session emphasizes the use of statistical techniques to analyze environmental data, addressing issues such as data quality and variability. Participants will discuss innovative approaches to extract meaningful insights from large datasets.

SDG 12 SDG 13 SDG 15

03 Simulation Techniques for Climate Impact Assessment +

This track will cover advanced simulation methods used to assess the impacts of climate change on various environmental systems. Attendees will learn about the integration of simulations with real-world data to enhance predictive accuracy.

SDG 13 SDG 15 SDG 17

04 Risk Analysis in Climate Change Scenarios +

This session will delve into risk assessment methodologies related to climate change, focusing on quantifying uncertainties and potential impacts. Participants will share case studies and frameworks for effective risk management.

SDG 13 SDG 15 SDG 16

05 Data Science Applications in Environmental Research +

This track highlights the role of data science in environmental studies, showcasing techniques for data mining, visualization, and interpretation. Participants will explore how data-driven insights can inform policy and decision-making.

SDG 12 SDG 13 SDG 17

06 Machine Learning Techniques for Climate Prediction +

This session will explore the application of machine learning algorithms in predicting climate patterns and trends. Participants will discuss the challenges and opportunities presented by integrating AI into climate research.

SDG 9 SDG 13 SDG 17

07 Optimization Methods for Resource Management +

This track focuses on optimization techniques applied to resource management in the context of environmental sustainability. Participants will examine mathematical approaches to improve efficiency and reduce waste in resource allocation.

SDG 12 SDG 13 SDG 15

08 Forecasting Climate Variables: Methods and Applications +

This session will address various forecasting methods used to predict climate variables, including temperature, precipitation, and extreme weather events. Participants will discuss the effectiveness and limitations of different forecasting models.

SDG 13 SDG 15 SDG 17

09 Quantitative Methods in Climate Change Research +

This track emphasizes the application of quantitative methods to analyze climate change data and trends. Participants will explore statistical techniques and their relevance in understanding climate dynamics.

SDG 13 SDG 15 SDG 17

10 Numerical Methods for Environmental Modeling +

This session will cover numerical techniques used in environmental modeling, focusing on their application to solve complex equations related to climate phenomena. Participants will discuss the accuracy and efficiency of various numerical approaches.

SDG 12 SDG 13 SDG 15

11 Computational Statistics in Climate Science +

This track will explore the intersection of computational statistics and climate science, highlighting innovative statistical methods for analyzing climate data. Participants will share insights on computational tools that enhance statistical analysis in environmental studies.

SDG 12 SDG 13 SDG 15