Workshop

University of Portsmouth, Portsmouth, UK

Workshop Chair: Dr. Elisavet Andrikopoulou, Senior Lecturer in University of Portsmouth

The workshop “Data Visualisation Methods in Healthcare” was successfully held on September 12th 2024 by Dr. Elisavet Andrikopoulou. The 12 students attended the workshop were master and doctoral students of the University of Portsmouth, UK. The workshop explored various chart types which was both enjoyable and enlightening. It helped reveal the strengths and weaknesses of each visualization method, allowing the students to select the one that best conveys their story. For example, to determine which players, games, or countries were the most successful in the Olympics, a bar chart proves to be a simple yet effective choice for making comparisons.

One of the most frequent questions we receive is: “What’s the right visualization for my data?” Choosing the appropriate visualization can be overwhelming, but it becomes easier once you understand the key principles. To illustrate this, I created ten different visualizations using a single dataset—the SOPCA dataset, which focuses on Olympic performance data sourced from kaggle.com.

Illinois Institute of Technology, USA

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

The Quantum-enhanced Machine Learning workshop offered an in-depth exploration of the exciting intersection between quantum computing and classical machine learning. Attendees gained valuable insights into the groundbreaking potential of quantum algorithms, particularly in accelerating machine learning tasks and addressing complex challenges that are currently beyond the reach of traditional computing. A significant focus was placed on how quantum systems can be seamlessly integrated into existing data science workflows, enhancing the capabilities of classical models.

The workshop featured interactive, hands-on sessions, allowing participants to experience the practical applications and subtle nuances of quantum-enhanced machine learning techniques. This approach enabled attendees to develop a deeper understanding of how these techniques can improve problem-solving in various domains. Renowned experts presented real-world applications, demonstrating the transformative potential of quantum-enhanced approaches in industries such as pharmaceuticals, finance, and materials science. Overall, the workshop succeeded in bridging the knowledge gap between quantum physics and machine learning, fostering a new generation of innovation. Participants left with a solid foundation in quantum-enhanced machine learning, empowered to explore its applications in their respective fields. The event underscored the immense possibilities ahead as quantum computing continues to evolve, offering unique advantages that can reshape industries and accelerate scientific discovery.

Torrens University Australia

Workshop Chair: Dr. Ammar Alazab, Senior Lecturer in Torrens University Australia

The CONF-CDS 2024 workshop, held on January September 23rd, 2024, brought together 50 students eager to delve into the realms of machine learning and its applications in advancing cybersecurity. The workshop, titled "Privacy-Preserving Intrusion Detection: Empowering Security with Federated Learning," served as a dynamic platform for participants to explore the intersection of these two rapidly evolving fields.

Led by Dr. Amma Alazab, the workshop covered diverse aspects of machine learning relevant to cybersecurity, aiming to equip attendees with practical skills and theoretical knowledge. Topics included anomaly detection, threat intelligence, and the integration of machine learning algorithms into security frameworks. Through hands-on exercises and interactive sessions, participants gained valuable insights into leveraging machine learning techniques to bolster defense mechanisms against evolving cyber threats.

The workshop fostered a collaborative learning environment, allowing students to exchange ideas, troubleshoot challenges, and build a network within the cybersecurity and machine learning communities. As the participants delved into real-world case studies and emerging trends, they left with a deeper understanding of the role machine learning plays in fortifying cybersecurity measures. CONF-CDS 2024 provided a comprehensive and engaging experience, empowering the next generation of cybersecurity professionals with the tools needed to navigate the complex landscape of digital security.

China Agricultural University Smart Sensing Group, Beijing, China

Workshop Chair: Dr. Xinqing Xiao, Associate Professor in China Agricultural University

The workshop “Edge Computing and AI based Intelligent Sensing Data Management” was successfully held on August 12, 2024 at the College of Engineering, China Agricultural University chaired by Assoc. Professor Xinqing Xiao. The 10 students attending the workshop were mainly doctor, master and international students from the discipline of mechanical and electronic engineering and agriculture engineering, and 2 researchers accounting at China Agricultural University. The workshop showcased some of the latest research conducted in the area of edge computing and AI based intelligent sensing data management technologies and applications as well as overlaps between the subjects. Some of the topics discussed including examination of edge computing, machine learning and intelligent sensing topics or have implications for edge computing and AI based intelligent sensing data management technologies and applications and the development trends in future. The workshop also has discussed the possible application in smart agriculture, food monitoring etc. by using edge computing or AI methods and intelligent sensing technologies.

Beijing Computer Federation Blockchain and Digital Finance Specialized Committee, Beijing, China

Workshop Chair: Prof. Wang Juan, Postdoctoral fellow at the University of Florida, Director of the Beijing Computer Federation

On June 2, 2024, The workshop “Blockchain and Fintech”, organized by the Beijing Computer Federation's Blockchain and Digital Finance Specialized Committee, was successfully held in Haidian District, Beijing. The workshop brought together scholars, doctoral students, and industry practitioners to discuss the latest research and innovations in blockchain, financial technology, decentralized exchanges, private key storage techniques, and quantitative trading. Professor Wang Juan, Chair of the Beijing Computer Federation's Blockchain and Digital Finance Specialized Committee, emphasized the importance of blockchain as a fundamental infrastructure for digital finance and the committee's commitment to fostering academic and industry collaborations to drive innovation and application in this field. Key presentations included Cheng Qixiang's discussion on the integration of the Rust programming language with the Ethereum ecosystem and Skysys.eth's exploration of native AI models in digital financial public goods. Mikkk provided insights on new opportunities within EVM-based public chains and highlighted the advantages of the Artela ecosystem. Participants engaged in lively discussions, exchanging constructive ideas and suggestions that could further the development of blockchain and digital finance.