International Conference on Explainable AI in Engineering (ICEAIE-26)

Conference Session Tracks

Aligned with

UN SUSTAINABLE DEVELOPMENT GOALS

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals.

SDG 4 Quality Education

SDG 9 Industry, Innovation and Infrastructure

SDG 11 Sustainable Cities and Communities

TRACK 01

Advancements in Explainable AI for Predictive Maintenance

This track focuses on the integration of explainable AI techniques in predictive maintenance applications within enginee...

TRACK 02

Interpretable Models in Supervised Learning

This session will delve into the development and application of interpretable models in supervised learning frameworks. ...

TRACK 03

Unsupervised Learning and Anomaly Detection

This track addresses the challenges and innovations in unsupervised learning techniques for anomaly detection in enginee...

TRACK 04

Feature Importance and Model Evaluation Techniques

This session will explore various methods for assessing feature importance in machine learning models. Participants will...

TRACK 05

Deep Learning Interpretability Frameworks

This track focuses on the latest frameworks and methodologies developed to enhance the interpretability of deep learning...

TRACK 06

Human-in-the-Loop AI Systems

This session will investigate the role of human-in-the-loop approaches in the development of explainable AI systems. Emp...

TRACK 07

Explainable AI in Industrial IoT Applications

This track will examine the application of explainable AI methodologies in the context of industrial IoT. Participants w...

TRACK 08

Decision Support Systems Leveraging Explainable AI

This session will explore the integration of explainable AI in decision support systems across various engineering domai...

TRACK 09

Challenges in AI Trustworthiness and Transparency

This track will address the critical challenges surrounding AI trustworthiness and model transparency in engineering app...

TRACK 10

Feature Extraction Techniques for Explainable Models

This session will focus on innovative feature extraction techniques that enhance the interpretability of machine learnin...

TRACK 11

Case Studies in Explainable Predictive Modeling

This track will showcase case studies that highlight the practical applications of explainable predictive modeling in en...

Hybrid Event