Pre-Enrollment

26th September 2026

Final Paper Submission

1st October 2026

Registration Deadline

11th October`2026

Conference Date

26th Oct - 27th Oct 2026

Call for Papers

The International Conference on Statistical Techniques for Machine Learning and AI invites researchers, academicians, industry experts, and practitioners to submit original and high-quality research contributions. This conference serves as a global platform for presenting innovative ideas, exchanging knowledge, and fostering interdisciplinary collaboration.

Focusing on key research areas such as Statistics,Data Science, the conference aims to bridge theoretical advancements with real-world applications.

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
Conference Registration

To confirm your participation and secure your presentation slot, authors of accepted papers must complete the registration. Early registration is highly recommended to enjoy discounted fees.

Register Now to Confirm Participation
Publication & Submission

Present your findings to a global audience. All accepted papers are eligible for publication in ISER-affiliated journals and conference proceedings, providing you with maximum academic visibility.

Submit Your Paper for Review