HYBRID EVENT
: You Can Participate In Person At
Putrajaya, Malaysia
Or Virtually From Your Home Or Work
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ICDAPMT · Registering as Listener
International Conference on Data Analytics and Predictive Modeling Techniques
26–27 Mar 2027
Putrajaya, Malaysia
Standard / Physical
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$
135
virtual · $175 in person
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1. Policy on Cancellations & Refunds :
A full refund is possible only if the cancellation request is submitted at least 70 days before the conference, with formal paperwork completed at least 60 days prior.
If cancellation occurs between 60 and 30 days before the event, partial refunds may be granted based on administrative costs incurred.
Cancellations made within 30 days of the event are non-refundable, though participants will receive a credit valid for one year.
Registrations made less than 30 days before the event are not eligible for refunds, but may be transferred to another ISIT conference.
Since this conference is hybrid format, the organizer reserves the right to conduct the event either in-person or virtually. Please note that no refunds will be issued due to changes in the event format.
Virtual registration fees are non-refundable. A credit will instead be issued for use at a future conference event.
2. Participation & Registration Requirements :
To attend an ISIT event, participants must complete the registration process within the stipulated time.
The event schedule, venue, and format are subject to changes at the discretion of the organizers, with prior notice sent via email.
ISIT is not liable for any financial losses resulting from changes in event details.
Fees paid for registration are strictly non-refundable.
If the primary author cannot participate, a co-author may attend instead, but refunds will not be granted for non-attendance.
3. Submission & Publication Norms :
Researchers submitting papers to ISIT must ensure their institution or supervisor is aware of their submission.
Each submission is subject to a rigorous peer review before being accepted for presentation.
Only papers linked to a completed registration will be included in conference proceedings.
The submitting author is considered the primary author; ISIT does not verify individual authorship claims.
If any concerns regarding authorship arise and are validated, the paper will be withdrawn without reconsideration.
Once a paper is removed, it cannot be reintroduced into any ISIT publication.
4. Travel & Accommodation Responsibilities :
Attendees are responsible for making their own travel and lodging arrangements.
ISIT does not provide logistical assistance for travel or accommodation.
The organization bears no responsibility for expenses incurred due to conference modifications or rescheduling.
5. Visa & Invitation Letter Policy :
Attendees are responsible for making their own travel and lodging arrangements.
ISIT does not provide logistical assistance for travel or accommodation.
The organization bears no responsibility for expenses incurred due to conference modifications or rescheduling.
ISIT does not engage directly with consulates or embassies on behalf of attendees.
Participants must handle their own visa applications and processes.
Important Information Regarding Invitation Letters:
The invitation letter is provided solely for conference attendance and does not serve as a document for immigration, employment, or residency purposes.
The letter assists in visa applications but does not guarantee visa approval.
ISIT holds no responsibility for visa denials or processing delays, and all related costs are borne by the applicant.
Any alterations or unauthorized use of the invitation letter will result in its invalidation and possible cancellation of conference participation.
Legal action may be pursued if the document is misused.
By accepting the invitation letter, attendees agree to comply with international travel regulations and ethical participation standards.
6. Registration Transfers :
Registrations may be transferred to another individual from the same institution if the original participant cannot attend.
Transfer requests must be made via email to
[email protected]
with necessary details and supporting documents.
Transfers must be requested at least 14 days before the event; otherwise, they will not be accommodated.
Transferred registrations are not eligible for refunds.
7. General Considerations :
Any modifications or cancellations must be communicated in writing to
[email protected]
.
Registration confirms acknowledgment and acceptance of these policies.
ISIT does not initiate automatic transactions; all payments are voluntarily completed by registrants.
Once registered, participants must submit a conference registration form within three days for confirmation.
Travel plans should only be finalized after receiving the official conference itinerary, which will be shared 15 days before the event.
8. Conference Programme and Participation Policy :
Presentations from different but relevant academic areas may be combined by the Organiser within an interdisciplinary or multidisciplinary programme to encourage cross-disciplinary understanding, interaction, and future research partnerships.
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What you'll hear about
Session tracks covered across the event.
View all 11 tracks →
01
Advanced Statistical Methods in Data Science
This track focuses on the latest advancements in statistical methodologies that enhance data analysis and interpretation. Participants will explore innovative techniques that improve the robustness and accuracy of statistical models in various applications.
02
Machine Learning Algorithms for Predictive Analytics
This session will delve into the development and application of machine learning algorithms tailored for predictive analytics. Attendees will discuss the effectiveness of various models in forecasting and decision-making processes.
03
Optimization Techniques in Big Data Analytics
This track emphasizes optimization strategies that are crucial for managing and analyzing large datasets. Participants will examine methods that enhance computational efficiency and model performance in big data environments.
04
Neural Networks and Deep Learning Applications
This session will explore the transformative impact of neural networks and deep learning on data analytics. Researchers will present case studies showcasing their applications in diverse fields such as healthcare, finance, and marketing.
05
Statistical Simulation and Modeling Techniques
This track will cover the role of simulation in statistical modeling and its applications in real-world scenarios. Participants will learn about various simulation techniques that aid in understanding complex systems and processes.
06
Data Mining Techniques for Knowledge Discovery
This session focuses on data mining methodologies that facilitate the extraction of valuable insights from large datasets. Attendees will discuss the integration of data mining with statistical analysis to enhance knowledge discovery.
07
Regression Analysis and Its Applications
This track will examine the principles and applications of regression analysis in various domains. Participants will explore advanced regression techniques that improve predictive accuracy and model interpretation.
08
Classification and Clustering Techniques in Data Science
This session will investigate the methodologies of classification and clustering as essential tools in data science. Attendees will discuss their applications in pattern recognition and data categorization.
09
Forecasting Methods in Statistical Analysis
This track will highlight various forecasting techniques used in statistical analysis for predicting future trends. Participants will explore the effectiveness of these methods in different sectors, including economics and environmental science.
10
Decision Support Systems and Predictive Modeling
This session will focus on the integration of predictive modeling techniques within decision support systems. Attendees will discuss how these systems enhance decision-making processes across various industries.
11
Quantitative Analysis in Business and Economics
This track will explore the application of quantitative analysis in business and economic research. Participants will examine statistical methods that inform strategic decision-making and policy formulation.