Hybrid Conference (In Person / Virtual)

International Conference on Statistical Techniques for Machine Learning and AI (ICSTMMLA - 27)
11th - 12th February 2027 , Espoo, Finland
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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 Espoo. 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 Espoo conference."
  • Networking with Global Experts:
    "Join global experts at our conference in Espoo 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 ICSTMMLA 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
Machine learning algorithms for statistical analysis
02
Statistical techniques in AI model evaluation
03
Feature selection methods in machine learning
04
Statistical learning theory applications
05
Data preprocessing for machine learning models
06
Ensemble methods in statistical learning
07
Deep learning and statistical inference
08
Bayesian statistics in AI applications
09
Statistical methods for big data analytics
10
Interpretability of machine learning models
11
Statistical challenges in AI deployment
12
Reinforcement learning and statistical methods
13
Statistical evaluation of AI systems
14
Transfer learning in statistical contexts
15
Statistical methods for time series analysis
16
Unsupervised learning and statistical techniques
17
Statistical issues in data privacy
18
Statistical frameworks for AI ethics
19
Applications of statistics in natural language processing
20
Statistical modeling of complex systems

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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