Charles Sturt University to Showcase Research at International Machine Learning and Data Science Conference
In an exciting development for the fields of machine learning and data science, Charles Sturt University (CSU) is set to co-organize the IEEE International Conference on Future Machine Learning and Data Science (FMLDS) in Sydney from November 20 to 23, 2024. This prestigious event will gather leading experts from around the globe to discuss the latest advancements in artificial intelligence (AI), computer vision, cybersecurity, and data science, among other critical topics.
A Collaborative Effort
The conference is a collaborative effort between Charles Sturt University and Western Sydney University, with the Institute of Electrical and Electronics Engineers (IEEE) serving as the convening body. The IEEE is renowned as the world’s largest technical professional organization, dedicated to advancing technology for the benefit of humanity. This partnership not only highlights CSU’s commitment to research excellence but also strengthens its presence in the rapidly evolving landscape of machine learning and data science.
A Platform for Knowledge Exchange
Associate Professor Rafiqul Islam, who serves as Chair of the conference’s Technical Program Committee, emphasized the importance of this event as a platform for knowledge exchange. “This conference will serve as an important platform for leading and emerging researchers, computer practitioners, industry professionals, and government participants to exchange ideas and present the latest research,” he stated.
The conference is expected to attract a diverse audience, including academics, industry leaders, and government representatives, all eager to share insights and explore the future of machine learning technologies.
A Record Number of Submissions
The response to the conference has been overwhelming, with approximately 170 presentation submissions received from around the world, exceeding initial expectations. This high level of interest underscores the significance of the conference and the relevance of its themes in today’s technological landscape. Accepted papers will undergo a rigorous review process by at least two independent expert reviewers, ensuring that only the highest quality research is presented.
Key Topics of Discussion
The conference will cover a wide array of topics, including but not limited to:
- Artificial Intelligence (AI)
- Computer Vision
- Future Machine Learning Technologies
- Cybersecurity
- Data Science
- Pattern Recognition
- Motion Tracking
- Bioinformatics
- Internet of Things (IoT)
These topics reflect the multifaceted nature of machine learning and data science, highlighting their applications across various sectors.
Publication Opportunities
Accepted papers will be published in the IEEE Xplore Digital Library, providing researchers with a platform to disseminate their findings to a global audience. Additionally, selected conference papers will be considered for publication in a Special Issue on Emerging Applications of Machine Learning in Smart Systems, subject to the journal’s acceptance criteria. This offers an excellent opportunity for researchers to gain recognition for their work.
Showcasing Student Talent
Professor Islam also noted that the conference will serve as a showcase for the talent of CSU’s computing research students. “It is so vitally important that anyone interested in a career in advanced computing explores the pathways and options offered by Charles Sturt University because the demand for computer science professionals will only continue to increase,” he remarked.
CSU offers a range of undergraduate and postgraduate degrees, along with industry internships, including a partnership with IBM Australia to facilitate work-integrated learning opportunities for students in regional New South Wales.
Highlighted Research Papers
Several noteworthy research papers from Charles Sturt University will be presented at the conference, including:
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Mitigating Cybersecurity Risk of Threat Actors through Dark Web Browser Fingerprinting: This paper investigates various cyber-attack types on both the Surface Web and Dark Web, focusing on browser fingerprinting, which captures metadata from users’ browsers.
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Privacy-Preserving Federated Incremental Learning for Spatial Crowdsourcing: This research explores Spatial Crowdsourcing (SC), an emerging model that allocates tasks based on real-time user locations to perform spatiotemporal relevant tasks.
- A Comparative Study on Permissioned Based Blockchain Implementation on Healthcare Data: This paper delves into permissioned blockchain frameworks in the healthcare sector, examining their security, privacy, and adoption rates.
Conclusion
The IEEE International Conference on Future Machine Learning and Data Science promises to be a landmark event for Charles Sturt University and the broader research community. By bringing together leading experts and emerging researchers, the conference will foster collaboration and innovation in the fields of machine learning and data science. As the demand for skilled professionals in these areas continues to grow, CSU is poised to play a pivotal role in shaping the future of technology and research.