Hybrid Conferencee

International Conference on Predictive Analytics and Statistical Modeling (ICPASM - 27)

8th - 9th March 2027 | Lucerne, Switzerland
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Expand the Academic Reach of Your Research - a Q1-ranked and Scopus-indexed journal publication opportunity

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Conference Notifications:

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Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Lucerne. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the Lucerne event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Lucerne conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Lucerne, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Lucerne."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Conference Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

SDG 4
SDG 4 Quality Education
SDG 8
SDG 8 Decent Work and Economic Growth
SDG 9
SDG 9 Industry, Innovation and Infrastructure
Track 01

Advancements in Predictive Analytics

This track focuses on the latest methodologies and technologies in predictive analytics. Researchers are encouraged to present innovative approaches that enhance predictive accuracy across various domains.

Track 02

Statistical Modeling Techniques

This session will explore diverse statistical modeling techniques used in contemporary research. Contributions that demonstrate novel applications and theoretical advancements are highly welcomed.

Track 03

Machine Learning Applications in Statistics

This track examines the integration of machine learning algorithms within statistical frameworks. Papers that highlight practical applications and theoretical insights are encouraged.

Track 04

Forecasting Methods and Innovations

This session will delve into innovative forecasting methods that leverage statistical principles. Participants are invited to share their findings on improving forecasting accuracy and reliability.

Track 05

Data Mining Techniques and Applications

This track focuses on the intersection of data mining and statistical analysis. Researchers are invited to present their work on extracting meaningful patterns from large datasets.

Track 06

Computational Statistics and Algorithms

This session will highlight advancements in computational statistics and algorithm development. Contributions that enhance computational efficiency and statistical inference are particularly welcome.

Track 07

Artificial Intelligence in Statistical Research

This track explores the role of artificial intelligence in advancing statistical research methodologies. Papers that demonstrate the synergy between AI and statistical techniques are encouraged.

Track 08

Big Data Analytics and Statistical Insights

This session will address the challenges and opportunities presented by big data in statistical analysis. Researchers are invited to share insights on methodologies that effectively handle large-scale data.

Track 09

Probabilistic Models in Applied Statistics

This track focuses on the development and application of probabilistic models in various fields. Contributions that illustrate the practical implications of these models are highly encouraged.

Track 10

Risk Modeling and Management

This session will explore statistical approaches to risk modeling and management. Papers that address innovative techniques for assessing and mitigating risk are particularly welcome.

Track 11

Data Science and Statistical Methodologies

This track examines the integration of data science principles with traditional statistical methodologies. Researchers are encouraged to present work that bridges these two fields for enhanced analytical outcomes.