Registration summary
ConferenceICDLACSC
ModeStandard / Physical
ParticipationListener
Registration fee$155.00
Bank charges (5.8%)$8.99
Total payable$163.99
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
ICDLACSC conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.
01 Advancements in Deep Learning Techniques +
This track focuses on the latest advancements in deep learning methodologies and their applications in computational science. Researchers are invited to present innovative approaches that enhance model performance and efficiency.
02 Machine Learning Algorithms for Data Analysis +
This session will explore various machine learning algorithms tailored for data analysis in computational science. Contributions that demonstrate novel applications or improvements in algorithmic efficiency are highly encouraged.
03 Neural Networks in Scientific Computing +
This track examines the role of neural networks in scientific computing, particularly in solving complex mathematical problems. Participants are invited to share their findings on the integration of neural networks with traditional computational methods.
04 Optimization Techniques in Computational Science +
This session will highlight optimization techniques that enhance computational models and simulations. Papers that present new optimization strategies or applications in real-world scenarios are welcome.
05 Big Data Analytics in Computational Research +
This track focuses on the challenges and solutions related to big data analytics within the realm of computational research. Contributions that showcase innovative data processing techniques and their implications for scientific discovery are encouraged.
06 Modeling and Simulation in Computational Science +
This session will delve into modeling and simulation techniques used in various fields of computational science. Researchers are invited to present their work on new models, simulation frameworks, or case studies demonstrating their effectiveness.
07 Pattern Recognition and Computer Vision Applications +
This track explores the intersection of pattern recognition and computer vision within computational science. Submissions that highlight novel applications or advancements in these domains are particularly welcome.
08 Natural Language Processing in Scientific Contexts +
This session will focus on the application of natural language processing techniques in scientific research and data analysis. Researchers are encouraged to present innovative methods that enhance understanding and interpretation of scientific texts.
09 Reinforcement Learning for Optimization Problems +
This track examines the application of reinforcement learning techniques to solve complex optimization problems in computational science. Contributions that demonstrate practical implementations or theoretical advancements are invited.
10 Automation and AI in Computational Science +
This session will explore the role of automation and artificial intelligence in enhancing computational workflows. Papers that discuss the integration of AI technologies to improve efficiency and accuracy in scientific computations are encouraged.
11 Research Applications of Deep Learning in Science +
This track focuses on the practical applications of deep learning techniques across various scientific domains. Researchers are invited to share case studies that illustrate the impact of deep learning on scientific research and discovery.
