Hybrid Conferencee

International Conference on Computational Statistics and Numerical Methods (ICCSNM - 26)

13th - 14th June 2026 | Prague, Czech Republic
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Conference Brochure
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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 Prague. 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 Prague 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 Prague conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Prague, 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 Prague."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICCSNM aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Statistics,Data Science, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

Authors are invited to submit papers addressing, but not limited to, the following areas:

01
Computational statistics in data analysis
02
Numerical methods for statistical modeling
03
Statistical simulation techniques and applications
04
Bayesian computation methods in statistics
05
Statistical methods for high-dimensional data
06
Computational challenges in statistical inference
07
Statistical software for computational statistics
08
Monte Carlo methods in statistical analysis
09
Statistical methods for optimization problems
10
Applications of computational statistics in finance
11
Statistical modeling of complex systems
12
Parallel computing in statistical analysis
13
Statistical methods for machine learning algorithms
14
Computational techniques for time series analysis
15
Statistical methods for spatial data analysis
16
Data visualization in computational statistics
17
Statistical education in computational methods
18
Future directions in computational statistics
19
Statistical methods for big data computation
20
Applications of computational statistics in healthcare