Hybrid Conferencee

International Conference on Statistical Learning and Machine Learning Integration (ICSLMLI - 27)

2nd - 3rd April 2027 | Kota Kinabalu, Malaysia
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Expand the Academic Reach of Your Research - a Q1-ranked and Scopus-indexed journal publication opportunity

Journal consideration and publication are subject to editorial review, peer review and applicable journal policies.

Conference Notifications:

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

Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Kota Kinabalu. 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 Kota Kinabalu 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 Kota Kinabalu conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Kota Kinabalu, 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 Kota Kinabalu."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICSLMLI 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, 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
Integration of statistical learning and machine learning
02
Applications of machine learning in statistics
03
Statistical methods for predictive modeling
04
Bayesian statistics and machine learning synergy
05
Statistical learning techniques for big data
06
Feature selection methods in statistical learning
07
Statistical validation of machine learning models
08
Deep learning applications in statistical analysis
09
Statistical approaches to model interpretability
10
Ensemble methods in statistical learning
11
Statistical methods for time series forecasting
12
Applications of neural networks in statistics
13
Statistical learning in bioinformatics
14
Causal inference in machine learning contexts
15
Statistical frameworks for unsupervised learning
16
Statistical software for machine learning applications
17
Challenges in integrating statistics and machine learning
18
Statistical methods for anomaly detection
19
Ethics in statistical machine learning applications
20
Future directions in statistical learning research