CONF-MLA 2023

The 2023 International Conference on Machine Learning and Automation (CONF-MLA 2023) was a hybrid conference which includes several workshops (offline and online) around the world. Dr. Marwan Omar from Illinois Institute of Technology, Dr. Alan Wang from the University of Auckland, Prof. Hong Zhu from Oxford Brookes University, Prof. Anil Fernando from University of Strathclyde and Dr. Mustafa ISTANBULLU from Çukurova University have chaired these workshops on related topics of Machine Learning in Advancing Cyber Security, Machine Learning for Medicine, Automation of Testing Machine Learning, Autoencoder Based Semantic Communications for Image Transmission on Error Prone Channels, Process Design of Semiconductor Device Fabrication, etc. CONF-MLA 2023 provided the participants with good opportunities to exchange ideas and build networks, and it will lead to further collaborations between both universities and other societies.

Workshop

Illinois Institute of Technology, Chicago

Workshop Chair: Dr. Marwan Omar, Associate Professor in Illinois Institute of Technology

On August 28th, 2023, the workshop "The Role of Machine Learning in Advancing Cyber Security" was held in Bologna (Italy). The workshop on the role of machine learning in advancing cybersecurity is designed to provide participants with a comprehensive understanding of how machine learning can be applied to enhance cybersecurity. The workshop covers a wide range of topics related to the intersection of machine learning and cybersecurity, including the various machine learning techniques that can be used to detect and respond to cyber threats, the practical considerations involved in deploying and managing machine learning algorithms in a cybersecurity context, and the ethical and legal implications of using machine learning in cybersecurity. The workshop is structured to provide a mix of theoretical and practical instruction, with hands-on exercises and case studies designed to help participants develop a deeper understanding of the concepts being discussed. Participants will have the opportunity to collaborate with others from different backgrounds and disciplines, including cybersecurity professionals, data scientists, and machine learning experts, in order to gain a more nuanced understanding of the challenges and opportunities presented by this rapidly evolving field. Ultimately, the goal of the workshop is to equip participants with the knowledge and skills they need to effectively leverage machine learning to improve their organization's cybersecurity posture and protect against emerging threats. By providing practical guidance on the deployment and management of machine learning algorithms, as well as addressing ethical and legal considerations, the workshop aims to ensure that participants are well-prepared to take on the challenges of applying machine learning in a cybersecurity context.



The University of Auckland, New Zealand

Workshop Chair: Dr. Alan Wang, Associate Professor in The University of Auckland

On October 13th, 2023, the workshop "Workshop on Machine Learning for Medicine 2023 (WMLM2023)" was held in Auckland, New Zealand. The Workshop on Machine Learning for Medicine 2023 offers a comprehensive exploration of the intersection between machine learning and the field of medicine. Join us on Friday, 13th October 2023, from 13:30 to 16:30 at Room 502-463, or connect remotely via Zoom. This workshop serves as a platform for experts, researchers, and practitioners to converge, exchange insights, and catalyze innovation in utilizing machine learning techniques to address critical medical challenges. Throughout the workshop, participants will be immersed in the latest advancements and trends in machine learning tailored specifically to the realm of medicine. The presentations will cover various topics, ranging from cognitive training and neuromodulation in stroke, to cutting-edge applications like brain age estimation using T1-MRI. Attendees will gain profound insights into stroke lesion segmentation, deep learning methodologies, and quantification of multiple brain lesions. These presentations promise to illuminate the transformative potential of machine learning in the medical landscape. The interactive nature of the workshop encourages dynamic discussions and meaningful exchanges among participants. By the conclusion of the event, attendees will emerge with a deeper understanding of how machine learning can revolutionize healthcare outcomes, diagnostics, and personalized medicine. Moreover, the Workshop on Machine Learning for Medicine 2023 provides a unique networking opportunity, fostering collaborations that have the potential to drive substantial progress in the dynamic field of machine learning in medicine.



Oxford Brookes University, Oxford OX33 1HX, United Kingdom

Workshop Chair: Prof. Hong Zhu, Professor of computer science in Oxford Brookes University

The First Oxford Brookes Workshop on Automation of Testing Machine Learning took place successfully on 18th Oct. 2023 at the Wheatley campus of Oxford Brookes University in Oxford, United Kingdom. It was a hybrid event with 13 persons attended in-person and 4 online remotely. At the workshop, nine researchers reported their recent work, which inspired interesting discussions after each presentation. The five hours of talks and discussions covered a wide range of topics on testing machine learning and its automation, including methodology of testing machine learning applications and automated tools, feature selection via testing, testing large language models, etc.



University of Strathclyde, UK

Workshop Chair: Prof. Anil Fernando, Professor in University of Strathclyde

The objective of this tutorial is to produce an overview of the historical development and current status of semantic communication while providing an understanding on the challenges and possible future direction in the field. We expect to present our new findings on autoencoder based semantic communication for image transmission over error prone channels. It is expected to discuss the autoencoders in detail and their applications and how they can be used for semantic communications. Furthermore, it will be discussed how autoencoders can be trained for semantic communications and how they can be used in image transmission over a noisy channel. Challenges faced in transmitting the images and how machine to machine (M2M) image communications can be happened with the proposed architecture will also be discussed. We expect to present our study providing a comprehensive overview on the historical development of AI algorithms in stock price prediction. In addition, through this tutorial it is expected to produce an in-depth overview on the kinds of algorithms that are currently utilized by researchers to generate next day price and price direction prediction based on numeric and textual data.



Cukurova University, Adana, Türkiye

Workshop Chair: Dr. Mustafa ISTANBULLU, Assistant Professor in Çukurova University

The Process Design of Semiconductor Device Fabrication workshop offers a comprehensive exploration of the intricate and essential aspects involved in designing and manufacturing semiconductor devices. This workshop is designed to provide participants with a deep understanding of the various stages and methodologies employed in the fabrication process, from initial concept to production. Semiconductor devices are the backbone of modern technology, powering a wide range of electronic systems and devices. The ability to design and manufacture these devices with precision is crucial to meet the increasing demands of the industry. In this workshop, participants will delve into the key elements of process design, enabling them to contribute effectively to the development and optimization of semiconductor fabrication procedures.

Online Session

The online session of the 2023 International Conference on Machine Learning and Automation (CONF-MLA 2023) was held on October 18, 2023. Prof. Marwan Omar from Illinois Institute of Technology, Prof. Abdullahi Arabo from University of the West of England, Prof. Alan Wang from University of Auckland, Prof. Roman Bauer from University of Surrey, Prof. Ali Darejeh from University of New South Wales (UNSW), Prof. Anil Fernando from University of Strathclyde, Prof. Hong Zhu from Oxford Brookes University, Prof. Mustafa Istanbullu from Mustafa Istanbullu, Prof. Moayad Aloqaily from Mohamed Bin Zayed University of Artificial Intelligence and Prof.Turgay Batbat from Erciyes University have given keynote speeches on related topics of Machine Learning on Physiological Signals, Machine Learning for Intelligent Biomedical Data Quantification, Scenario-Based Functional Testing of Machine Learning Applications, etc. Also, we invited authors of qualified papers to deliver oral presentations at the Online Session. Five authors have presented their studies of Silicon Carbide (SiC) MOSFET Technology, early warning system, 5-stage pipeline RISC-V CPU, etc. Questions from the audience were collected and answered by the presenters.

Highlights

Title: Supervised Learning for Biomedical Applications
Presented by: Roman Bauer, Lecturer, Department of Computer Science, University of Surrey

Title: Autoencoder Based Semantic Communications
Presented by: Anil Fernando, Professor, Department of Computer and Information Science, University of Strathclyde

Title: Machine Learning on Physiological Signals
Presented by: Turgay Batbat, Assistant Professor, Department of Biomedical Engineering, Erciyes University

Title: Machine Learning for Intelligent Biomedical Data Quantification
Presented by: Alan Wang, Associate Professor, Faculty of Medical and Health Sciences and Bioengineering Institute, University of Auckland

Title: Explainable Artificial Intelligence in Education
Presented by: Abdullahi Arabo, Senior Lecturer, Computer Networks and Mobile Technology, University of the West of England

Title: Scenario-Based Functional Testing of Machine Learning Applications
Presented by: Hong Zhu, Professor, School of Engineering, Computing and Mathematics, Oxford Brookes University

Title: An ANN-Based Impedance Measurement System
Presented by: Mustafa Istanbullu, Assistant Professor, Biomedical Engineering Department, Çukurova University

Title: Towards AI-Assisted Blockchain for Metaverse and Industry 5.0
Presented by: Moayad Aloqaily, Research & Development Manager, Machine Learning Department, Mohamed Bin Zayed University of Artificial Intelligence

Title: Metaverse Applications in Higher Degree Education
Presented by: Ali Darejeh, Lecturer, School of Computer Science and Engineering, University of New South Wales (UNSW)

Title: Decision Trees
Presented by: Marwan Omar, Associate Professor, Faculty of Information Technology and Management, Illinois Institute of Technology

Title: Next Generation Transistors for Autonomous Vehicles and Intelligent Systems
Presented by: Sharidya Rahman, Monash University, Australia

Title: An Automated FX Currency Transaction Forecasting Process for Global E-commerce and Fin
Presented by: Rudrendu Kumar Paul, Boston University

Title: Design a 5-stage pipeline RISC-V CPU and optimise its ALU
Presented by: Lifu Deng, Glasgow College, University of Electronic Science and Technology of China

Title: Prediction-based early warning system for overflow of people in metro stations
Presented by: Di Lu, Southeast University

Title: Implementation of Intelligent Healthcare Image Detection System based on OpenCV
Presented by: Zhipeng Zou, School of International Information and Software, Dalian University of Technology

Title: A Review of Virtual Reality Technology
Presented by: Zac Wu, Southeast University

Title: Applications and Challenges of Silicon Carbide (SiC) MOSFET Technology in Electric Veh
Presented by: Yige Xu, Jilin University

Videos

You can find the Youtube Playlist of online session Here.

Publications

Accepted papers of CONF-MLA 2023 will be published in in Journal of Physics: Conference Series (Print ISSN: 1742-6588) or Applied and Computational Engineering (Print ISSN: 2755-2721) and were submitted to EI Compendex, Conference Proceedings Citation Index (CPCI), Crossref, Portico, Inspec, Google Scholar, and other databases for indexing.

Title: Journal of Physics: Conference Series
Press: IOP Publishing, United Kingdom
ISSN: 1742-6588

Title: Applied and Computational Engineering
Press: EWA Publishing, United Kingdom
ISSN: 2755-2721