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ICMLDA · Registering as Listener

International Conference on Machine Learning and Data Analytics

14 - 15 Dec 2026 Bali, Indonesia Standard / Physical Participation
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$120
virtual · $135 in person
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Registration summary

ConferenceICMLDA
ModeStandard / Physical
ParticipationListener
Registration fee$135.00
Bank charges (5.8%)$7.83
Total payable$142.83
Includes all bank processing charges — the amount above is exactly what will be charged.

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• Conference Session Tracks •
SDGs
SDG-Aligned Research Themes

ICMLDA conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 4 - Quality Education SDG 9 - Industry, Innovation and Infrastructure SDG 10 - Reduced Inequalities SDG 11 - Sustainable Cities and Communities
01 Advancements in Supervised Learning Techniques +
This track focuses on the latest developments in supervised learning methodologies and their applications across various engineering domains. Researchers are invited to present their findings on novel algorithms, performance improvements, and case studies demonstrating practical implementations.
02 Unsupervised Learning: Theory and Applications +
This session will explore the theoretical foundations and practical applications of unsupervised learning techniques in data analytics. Contributions may include clustering methods, dimensionality reduction, and innovative use cases in engineering fields.
03 Deep Learning Architectures in Engineering +
This track aims to showcase cutting-edge deep learning architectures and their transformative impact on engineering problems. Papers discussing advancements in neural networks, convolutional networks, and recurrent networks are particularly encouraged.
04 Reinforcement Learning in Intelligent Systems +
This session will delve into the application of reinforcement learning in developing intelligent systems capable of autonomous decision-making. Contributions should highlight novel algorithms, real-world applications, and the challenges faced in implementation.
05 Ethics and Responsible AI in Engineering +
This track addresses the ethical considerations and societal implications of deploying artificial intelligence in engineering applications. Papers discussing frameworks for responsible AI, bias mitigation, and ethical decision-making are highly encouraged.
06 Cognitive Computing and Human-Machine Interaction +
This session focuses on the intersection of cognitive computing and human-machine interaction, emphasizing the development of systems that enhance user experience. Researchers are invited to present innovative approaches that leverage AI to improve communication and collaboration.
07 Natural Language Processing in Engineering Applications +
This track explores the role of natural language processing in engineering, particularly in automating and enhancing communication processes. Contributions may include novel algorithms, case studies, and applications in technical documentation and user interfaces.
08 Expert Systems and Decision Support Technologies +
This session will highlight the development and implementation of expert systems and decision support technologies in engineering contexts. Papers should focus on innovative approaches to knowledge representation, reasoning, and user interaction.
09 AI Applications in Robotics and Automation +
This track invites contributions that explore the integration of artificial intelligence in robotics and automation systems. Topics may include perception, control, and learning algorithms that enhance robotic capabilities in various engineering applications.
10 Data Science Techniques for Engineering Challenges +
This session will focus on the application of data science techniques to address complex engineering challenges. Researchers are encouraged to present methodologies that leverage big data analytics, predictive modeling, and statistical analysis.
11 Knowledge Representation and Reasoning in AI +
This track explores the methodologies for knowledge representation and reasoning within artificial intelligence systems. Contributions should discuss theoretical advancements, practical applications, and the implications for intelligent system design.