7th International Conference on Machine Learning and Soft Computing (MLSC 2026)

Name: 7th International Conference on Machine Learning and Soft Computing (MLSC 2026)
Start: 2026-02-27T10:00:00-08:00
End: 2026-02-28T18:00:00-08:00
Location: Vancouver, Canada

Schedule

Fri, 27 Feb, 2026 at 10:00 am to Sat, 28 Feb, 2026 at 06:00 pm

UTC-08:00

Location

Vancouver, Canada | Vancouver, BC

7th International Conference on Machine Learning and Soft Computing (MLSC 2026)

February 27 ~ 28, 2026, Vancouver, Canada

https://acsty2026.org/mlsc/index

Scope

7th International Conference on Machine Learning and Soft Computing (MLSC 2026) invites high quality research contributions that advance the theory, algorithms, and applications of machine learning and soft computing. As intelligent systems continue to shape science, engineering, and society, MLSC 2026 provides a premier international forum for researchers, practitioners, and innovators to present breakthroughs, exchange ideas, and explore emerging challenges across learning algorithms, intelligent optimization, and computational intelligence.

Topics of interest include, but are not limited to, the following

Machine Learning Foundations & Algorithms

Foundations of machine learning
Supervised, unsupervised, and semi supervised learning
Clustering, dimensionality reduction, and representation learning
Probabilistic models and Bayesian learning
Reinforcement learning and sequential decision making
Evolutionary, genetic, and bio inspired learning algorithms
Ensemble learning and model aggregation
Inductive logic programming and symbolic learning
Neuro symbolic and hybrid learning architectures
Multi strategy and multi agent learning
Automated knowledge acquisition and reasoning
Explainable, interpretable, and trustworthy ML

Deep Learning & Neural Computation

Deep neural networks and advanced architectures
Generative AI and foundation models
Multimodal learning (vision–language–audio)
Graph neural networks and relational learning
Continual, transfer, and meta learning
Neural computing and biologically inspired models
Natural Language, Vision & Intelligent Perception
Natural language processing and understanding
Machine learning for information retrieval
Computer vision, pattern recognition, and image/video analytics
Perception based intelligent decision systems
Multisensory and perceptual computing

Soft Computing Foundations & Techniques

Fuzzy logic, fuzzy systems, and approximate reasoning
Stochastic, probabilistic, and uncertainty aware computing
Evolutionary computation and multi objective optimization
Morphic computing and biologically inspired soft computing
Soft computing for pattern recognition and intelligent decision making

Intelligent Systems & Agent Based Computing

Intelligent software agents and architectures
Multi agent systems and distributed intelligence
Cognitive and integrated learning architectures
Learning from instruction, demonstration, and interaction
Human centered and interactive intelligent systems

Data Mining, Knowledge Discovery & Big Data Analytics

Data mining theory, algorithms, and applications
Social network analysis and mining
Large scale data analytics and distributed ML
Soft computing for Big Data and high dimensional data
Visualization of patterns, models, and complex datasets

Optimization, Search & Evolutionary Intelligence

Global optimization and heuristic search
Multi objective evolutionary algorithms
Swarm intelligence and nature inspired optimization
Hybrid optimization frameworks combining ML and soft computing

Applications of ML & Soft Computing

Bioinformatics, healthcare, and biomedical intelligence
Robotics, autonomous systems, and intelligent control
Finance, business intelligence, and decision support
Smart environments, IoT, and cyber physical systems
Computer graphics, animation, and creative AI
Industrial, scientific, and engineering applications

Emerging Trends & Future Directions

Responsible, ethical, and fair AI
Green and energy efficient ML
Quantum machine learning and quantum inspired soft computing
Edge AI, TinyML, and on device intelligence
Advances in explainability, safety, and robustness

Paper Submission

Authors are invited to submit papers through the conference Submission System by January 17, 2026. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).

Selected papers from MLSC 2026, after further revisions, will be published in the special issue of the following journal.