CONF-MLA 2025

Intelligent Systems and Automation: AI Models, IoT, and Robotic Algorithms

Date

November 17, 2025

Organizer

University of East London

Symposium Chair

Dr. Hisham AbouGrad
Senior Lecturer in University of East London

Personal Bio

Dr. Hisham AbouGrad, DProf, MSc, MBA, PGCHEP, FHEA, CITP MBCS, PMP, ITQM, is a Senior Lecturer in Computer Science & Digital Technologies with a robust academic and research background. His expertise lies in artificial intelligence (AI), machine learning (ML), cybersecurity, financial technology (FinTech), multi-criteria decision making (MCDM), and information systems performance. Dr. AbouGrad actively collaborates with fellow researchers and supervise PhD and DProf students on projects that bridge theoretical knowledge with practical application. Particularly, he has supervised innovative projects such as the development of Contactless Payment Mobile Applications utilising QR Code and NFC Technologies, and predictive modeling systems for financial applications using ML. These projects provide invaluable hands-on experience, particularly in emerging technologies like mobile app development and financial performance prediction. Dr. AbouGrad's research contributions are well-documented through his numerous publications, which address critical issues in ML, information security, and financial applications. His recent work, including a research paper "AI-Framework to Predict eCommerce Fake Reviews: A Hybrid Neural Network Machine Learning Model," showcases his ability to apply advanced AI methodologies to solve real-world financial and sustainability challenges by emphasising on quality, scalability, and reliability. His contributions not only advance academic knowledge but also have significant implications for sustainable business environment. More details on his work are available on Google Scholar and LinkedIn.

Committee Members

Dr. Mustansar Ghazanfar, UEL, London, UK; [email protected]
Dr. Salem Alsaid Sebha, University, Sebha, Libya; [email protected]
Dr. Ahmed Abubahia, Edge Hill University, Ormskirk, UK; [email protected]

Call for Papers

Background

Intelligent systems and automation are revolutionising industries by integrating Artificial Intelligence (AI) models, Machine Learning (ML), the Internet of Things (IoT), and Robotic Algorithms. AI-driven automation enhances decision-making, efficiency, and adaptability across diverse applications, from smart manufacturing to autonomous robotics. Machine learning enables intelligent systems to process vast datasets, optimise operations, and improve real-time responses. The IoT connects devices, generating valuable data for prediction, smart environments, and seamless automation. Robotic algorithms support autonomous navigation, precision control, and adaptive behaviour in robotics for enhancing performance in fields such as healthcare and industrial automation. Supported by leading higher education institutions, including the University of East London, Edge Hill University, and Sebha University, the ISA 2025 symposium explores the advancements in intelligent systems by focusing on how AI models, IoT, and robotics intersect to drive automation and innovation. Participants gain insights into emerging trends, challenges, and future directions in this evolving research area.

Goal/Rationale

The demand for intelligent systems and automation has surged, driven by the convergence of AI models, machine learning, the IoT, and Robotic Algorithms. However, integrating these technologies remains a complex challenge, requiring innovative solutions for seamless communication, real-time decision-making, and autonomous adaptability. A key problem is ensuring that AI-driven automation operates efficiently in dynamic, uncertain environments while maintaining reliability, security, and ethical compliance. Recent advances in deep learning, edge AI, and swarm robotics have significantly improved automation capabilities. AI models are becoming more sophisticated in processing vast, real-time IoT-generated data, which enables predictive analytics, smart infrastructure, and autonomous robotic systems. Enhanced robotic algorithms now support improved navigation, human-robot collaboration, and self-learning mechanisms, optimising industrial and service applications. The ISA 2025 hybrid symposium aims to explore cutting-edge research and practical solutions to bridge gaps in the areas of AI, IoT, and robotics. It will bring together experts, researchers, and practitioners to discuss strategies for overcoming current limitations to ensure scalability and utilising automation for intelligent decision-making. Participants will gain valuable insights into emerging trends and future opportunities, which promote interdisciplinary collaboration in this evolving research field.

Scope and Information for Participants

This hybrid symposium focuses on the utilisation of AI models, machine learning, the IoT, and Robotic Algorithms to advance intelligent systems and automation. It will explore recent innovations, challenges, and future research directions in these domains by addressing both theoretical and practical aspects. Participants are invited to contribute research and insights on the following key themes:

  • AI-Driven Automation: This focuses on enhancing decision-making, optimisation, and adaptability in dynamic environments.
  • Machine Learning for Intelligent Systems This utilises ML for the applications of deep learning, reinforcement learning, and edge AI toward smarter intelligent systems.
  • IoT-Enabled Smart Systems: Improving smart systems through Data-driven automation, predictive analytics, and real-time decision-making.
  • Robotic Algorithms and Autonomous Systems: Advances in navigation, control, and human-robot interaction using robotics algorithm for the next-generation smart robotic systems (SRS).
  • Security, Ethics, and Scalability in Automation: Develop automation by addressing risks, reliability, and sustainable AI-driven systems using security, ethics, and scalability.

Submission

Prospective authors are kindly invited to submit full papers that include title, abstract, introduction, tables, figures, conclusion and references. It is unnecessary to submit an abstract in advance. The deadline for general submission is November 10, 2025.

Each paper should be no less than 4 pages. One regular registration can cover a paper of 6 pages, and additional pages will be charged. Please format your paper well according to the conference template below before submission.

Please prepare your paper in both .docx and .pdf format and submit your full paper by email with both formats attached directly to [email protected].

Topics

This symposium welcomes submissions with the following topics

Automation

  • AI-Assisted Design
  • Automated Machine Learning
  • Clustering and Classification
  • Collaborative Filtering and Recommendation Systems
  • Computer Vision
  • Cyber-Physical Systems
  • Data Preprocessing Methods
  • Feature Selection Approaches
  • Graph and Network Data
  • Home Automation
  • Regression with Machine Learning
  • Robotic Process Automation
  • Sensor Technology
  • Warehouse Automation
  • Hyperparameter Optimization
  • Industrial Automation
  • IoT (Internet of Things)
  • Machine-to-Machine Communication
  • Meta-learning
  • Model Interpretability Techniques
  • Model Selection Strategies
  • Neural Architecture Search
  • Pipeline Generation Methods
  • Predictive Maintenance
  • Process Automation
  • Supply Chain Automation
  • Time Series Analysis

Robotics and Intelligent Systems

  • Aerial and Underwater Robotics
  • Assistive Devices and Exoskeletons
  • Autonomous Vehicles
  • Deep Learning for Robotic Vision
  • Drones
  • Human-Robot Collaboration and Learning
  • Human-Robot Interaction
  • Imitation Learning and Learning from Demonstration
  • Intelligent Transportation Systems
  • Learning-Based Control and Planning Algorithms
  • Multi-Robot Systems and Learning
  • Reinforcement Learning for Robotics
  • Robotic Manipulation and Grasping
  • Robot Navigation and Path Planning
  • Robot Perception
  • Transfer Learning and Domain Adaptation

Meanwhile, submissions aligned with the overall conference scope are also welcomed.

Machine Learning

  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
  • Deep Learning
  • Convolutional Neural Networks
  • Recurrent Neural Networks
  • Generative Adversarial Networks
  • Transfer Learning
  • Ensemble Learning
  • Explainable AI
  • Natural Language Processing
  • Speech Recognition
  • Image Recognition
  • Recommendation Systems
  • Anomaly Detection
  • Cluster Analysis
  • Dimensionality Reduction
  • Feature Engineering
  • Model Evaluation

Submission & Payment

Type Regular Submission
Final Submission November 10, 2025
Review Process 2 weeks
Revise & Acceptance 2 weeks
Registration & Payment 2 weeks

Fees

Items Amount (VAT Included)
Registration and Publishing Fee (6 pages included) $500
Additional Page $40/extra page

Publication

Accepted papers of this symposium will be published in conference proceedings, and will be submitted to EI Compendex, Conference Proceedings Citation Index (CPCI), Crossref, Portico, Inspec, Google Scholar, CNKI, and other databases for indexing. The situation may be affected by factors among databases like processing time, workflow, policy, etc.

This symposium is organized by CONF-MLA 2025 and will independently proceed the submission and publication process.

Please note that the publication policy may vary between different publishers. For details regarding the publication process, kindly refer to the policies of the respective publisher.

Venue

University of East London, Docklands Campus University Way London, E16 2RD United Kingdom.

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