ICMLABDITS · Registering as Listener

International Conference on Machine Learning Algorithms for Big Data IT Systems

📅 15–16 Dec 2026 📍 Rome, Italy 👤 Standard / Listener

Listener registration from

$165

virtual · $165 in person

Registration benefits

✉

Official invitation letterIssued automatically after registration

📜

Certificate & digital materialsCertificate, slides and resource materials

🌐

Supporting global researchConnect with researchers across 30+ countries

Credit Card

Debit Card

Net Banking

Cash Card

Unified Payments

For Support Please Contact

[email protected]

Select registration mode

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

Standard $165 On-site keynotes, talks, workshops, networking, conference kit and certificate. SelectedSelect Virtual $125 Live streaming access to all sessions, digital materials and certificate. SelectedSelect

All sessionsNetworkingCertificateInvitation letterConference kit

Your details

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

Name:

Email address:

Phone Number

City

State

Country

Zip / Postal code

Address

Coupon code

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

Coupon Code(If Any)

Apply

I agree to the Terms & Conditions and Refund & Cancellation Policy.

VISAMastercardAmexPayPal

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

Conference session tracks

Key research areas covered across the sessions — tap a track to read more.

This track focuses on the latest developments in machine learning algorithms tailored for big data applications. Researchers are invited to present novel approaches that enhance predictive accuracy and computational efficiency.

This session explores innovative techniques for analyzing large datasets within IT infrastructures. Contributions should highlight methods that improve data processing and decision-making capabilities.

This track examines the integration of intelligent systems in automating IT processes. Papers should discuss the impact of AI models on operational efficiency and system optimization.

This session addresses the challenges and solutions associated with scalable computing in big data environments. Researchers are encouraged to share insights on architectures and frameworks that facilitate large-scale data processing.

This track focuses on methodologies for effective data integration across diverse IT systems. Contributions should emphasize strategies that enhance data coherence and accessibility.

This session investigates tools and techniques for monitoring the performance of big data systems. Papers should address metrics, benchmarks, and methodologies for ensuring optimal system performance.

This track explores the role of predictive analytics in driving business intelligence initiatives. Researchers are invited to present case studies and frameworks that demonstrate the value of data-driven decision-making.

This session focuses on the application of AI models in improving decision-making processes within IT systems. Contributions should highlight real-world applications and performance evaluations.

This track examines optimization strategies for enhancing the performance of machine learning algorithms. Researchers are encouraged to present novel techniques that address computational challenges.

This session explores cutting-edge innovations in IT infrastructure that support big data processing. Papers should discuss the implications of these innovations on system scalability and reliability.

This track addresses the various challenges faced in applying machine learning to big data contexts. Contributions should provide insights into overcoming obstacles related to data quality, volume, and velocity.