Hybrid Conference (In Person / Virtual)

International Conference on Computational Methods in Statistical Learning (ICCMSL - 27)
11th - 12th January 2027 , Kopavogur, Iceland
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Conference Notifications:

"Be sure to check this section regularly for all IIRD Global Conference updates. We’ll keep you informed about deadlines, event details, and more important notifications."

  • Abstract Submissions Open:
    "We are now accepting abstract submissions for the IIRD Global Conference in Kopavogur. Submit your abstract by today to be part of this exciting international event." Call for Abstracts – Submit Now!
  • Paper Submission Guidelines:
    "Please ensure your paper follows the submission guidelines for smooth processing. Visit our paper submission page for more details."
  • Peer Review Process:
    "The peer review process will begin soon. Authors will receive valuable feedback that will help enhance their presentations for the Kopavogur conference."
  • Networking with Global Experts:
    "Join global experts at our conference in Kopavogur and engage in meaningful conversations. Build relationships that last." Register now to join!
  • Best Paper Presentation Award:
    Dr. Shatha Hawarna from Hamdan Bin Mohammed Smart University received the Best Paper Presentation Award at (ICBAI-25) in Bangkok, Thailand.
  • SDG-Inspired Conference Focus:
    "The conference will explore themes related to sustainability and inclusive development, with an emphasis on research that contributes to global well-being."

Call For Papers

The ICCMSL provides a supportive platform for both experienced researchers and early-career academicians to present their work and gain recognition.

The conference covers diverse topics such as Statistics, Data Science, encouraging participation from emerging researchers and fostering academic growth.

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

01
Computational methods in statistical learning
02
Algorithms for high-dimensional data
03
Statistical learning theory applications
04
Model selection in statistical learning
05
Statistical learning for time series analysis
06
Deep learning and statistical methods
07
Regularization techniques in statistical learning
08
Statistical learning in genomics
09
Bayesian approaches to statistical learning
10
Statistical learning for image analysis
11
Ensemble methods in statistical learning
12
Statistical learning for text classification
13
Robustness in statistical learning models
14
Statistical learning for network data
15
Applications of statistical learning in finance
16
Statistical learning in social sciences
17
Interpretable models in statistical learning
18
Statistical learning for causal inference
19
Computational challenges in statistical learning
20
Future directions in statistical learning

Assessment

Submissions will be reviewed to ensure quality and relevance, with a focus on encouraging emerging research contributions. Accepted papers will be presented and considered for publication opportunities.

Registration

Early-career researchers are encouraged to register and present their work, gaining valuable feedback and academic exposure.

Publication

The conference provides opportunities for emerging researchers to publish their work in recognized platforms.

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