ICISKE · Registering as Listener

International Conference on Intelligent Systems and Knowledge Engineering

16th Oct – 17th Oct 2026 Yokohama, Japan Standard / Physical Participation
Listener Registration From
$—
$— in person
Registration Benefits:
Official invitation letterIssued automatically after registration
Certificate & digital materialsGet certificate, slides and resource materials
Supporting global researchConnect with researchers across 30+ countries

Select registration mode

Prices are shown before tax and bank charges — no surprises at checkout.

All sessions Networking Certificate Invitation letter Conference kit

Your details

We only need what's required to register and email your confirmation. Everything else is optional.

For Support Please Contact

team@researchleagues.com

Coupon code

Have a code? Apply it here — the discount updates the total immediately.

Apply

Get 10% OFF on registration — use coupon code FAST10 and click Apply.

VISA MC AMEX UPI

Payments encrypted & processed securely. Refundable up to 14 days before the event.

Registration summary

ConferenceICISKE
ModeStandard / Physical
ParticipationListener
Registration fee$—
Bank charges (5.8%)$—
Discount-$0.00
Total payable $—

Includes all bank processing charges — the amount above is exactly what will be charged. View charge breakdown

Need help?

Contact our registration team:

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 Wheel

SDG-Aligned Research Themes

International Conference on Intelligent Systems and Knowledge Engineering conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 4 - Quality Education SDG 8 - Decent Work and Economic Growth SDG 9 - Industry, Innovation and Infrastructure SDG 11 - Sustainable Cities and Communities

This track focuses on the latest methodologies and applications of predictive modeling in various engineering domains. Researchers are invited to present their findings on enhancing prediction accuracy through innovative techniques.

This session aims to explore the distinctions and applications of supervised and unsupervised learning in computer science engineering. Contributions that highlight novel algorithms or frameworks are particularly encouraged.

This track will delve into the transformative impact of deep learning technologies across engineering disciplines. Participants are invited to share case studies and research that demonstrate practical applications and outcomes.

This session addresses the challenges and solutions related to anomaly detection within complex engineering systems. Submissions that present new techniques or frameworks for effective anomaly identification are welcome.

This track focuses on innovative methods for feature extraction and representation in data-intensive engineering applications. Researchers are encouraged to discuss their approaches to improving data interpretability and model performance.

This session will explore the development and implementation of expert systems in engineering contexts. Contributions that address knowledge representation techniques and their practical implications are highly sought after.

This track examines the role of workflow automation in enhancing efficiency and productivity in engineering processes. Papers that showcase successful automation strategies and their outcomes are encouraged.

This session focuses on the integration of system monitoring techniques with predictive maintenance strategies. Researchers are invited to present their work on improving system reliability and reducing downtime.

This track will address the critical aspects of model evaluation and the development of performance metrics in machine learning applications. Contributions that propose new evaluation frameworks or metrics are particularly welcome.

This session explores the intersection of industrial IoT and intelligent systems, focusing on innovative solutions for real-time data processing and decision-making. Researchers are encouraged to share insights on enhancing operational efficiency through IoT technologies.

This track investigates the application of fuzzy logic in the development of decision support systems for engineering challenges. Papers that demonstrate the effectiveness of fuzzy approaches in complex decision-making scenarios are invited.

COPYRIGHT © 2026 International Conference on Intelligent Systems and Knowledge Engineering. ALL RIGHTS RESERVED