An official invitation letter will be provided upon successful registration for your participation in the conference.
학술대회 참가 등록이 정상적으로 완료되면 공식 초청장이 발급됩니다.
Plenary, keynote and parallel sessions.
전체회의, 기조연설 및 분과 세션.
Connect with fellow researchers.
동료 연구자들과의 교류.
Digital certificate of participation.
디지털 참가 증명서 발급.
Official letter after successful registration.
등록 완료 후 공식 초청장 발급.
E-proceedings & resource materials.
전자 논문집 및 참고 자료.
Learn from leading experts & scholars.
저명한 전문가 및 학자들의 강연.
The conference's session tracks effectively support the following SDGs.
본 학술대회의 세션 트랙은 다음의 지속가능발전목표를 효과적으로 지원합니다.
This track focuses on the latest methodologies and algorithms in simulation-based optimization. Participants will explore innovative approaches that enhance efficiency and accuracy in complex problem-solving.
This session highlights the integration of machine learning techniques within computational modeling frameworks. Researchers will present case studies demonstrating the effectiveness of these applications in various domains.
This track examines cutting-edge data science techniques tailored for big data challenges. Discussions will center on novel algorithms and tools that facilitate the extraction of meaningful insights from vast datasets.
This session delves into the role of numerical methods in solving complex optimization problems. Presenters will share advancements that improve convergence rates and solution accuracy.
This track focuses on quantitative analysis methodologies applied to complex systems. Participants will explore statistical techniques that enhance understanding and modeling of intricate interactions.
This session investigates the role of automation in enhancing computational science workflows. Researchers will discuss tools and frameworks that streamline processes and improve productivity.
This track emphasizes the development and application of pattern recognition methods in data science. Presentations will cover theoretical advancements and practical implementations across various fields.
This session explores the intersection of artificial intelligence and optimization techniques. Participants will discuss AI-driven approaches that lead to improved decision-making and resource allocation.
This track focuses on the use of simulation modeling in the development of decision support systems. Researchers will present methodologies that enhance decision-making processes in uncertain environments.
This session examines the application of probabilistic models in various computational science contexts. Participants will explore how these models can effectively represent uncertainty and variability.
This track encourages interdisciplinary collaboration to address optimization challenges across different fields. Presenters will share insights and methodologies that bridge mathematics, statistics, and applied sciences.