The 10th International Conference on Fuzzy Systems and Data Mining (FSDM 2024)

Abstract: In recent years, mobile devices can be equipped with increasingly advanced computing capabilities, which opens up countless possibilities for meaningful applications. Traditionally, any cloud-based Machine Learning (ML) approach requires that data be centralized on a cloud-based server/data center. However, this can result in critical issues related to unacceptable latency and communication inefficiency as well as major security and privacy concerns. However, conventional ML technologies still require personal data to be shared. Recently, in light of increasing security and privacy concerns, the concept of Federated Learning (FL) has been introduced. In FL, end devices use their local data to train a local ML model required by the server. In a large, complex mobile edge networks, FL still faces implementation challenges with regard to communicational costs, resource allocation, security, and privacy. In this talk, we begin with an introduction to the background and fundamentals of FL. We then discuss how FL can work to try and preserve privacy while maintaining security of data. Finally, we discuss some open research areas and specific open problems where attendees may be able to make an impact.

Biography: Gautam Srivastava was awarded his B.Sc. degree from Briar Cliff University in U.S.A. in the year 2004, followed by his M.Sc. and Ph.D. degrees from the University of Victoria in Victoria, British Columbia, Canada in the years 2006 and 2012, respectively. He then taught for 3 years at the University of Victoria in the Department of Computer Science, where he was regarded as one of the top undergraduate professors in the Computer Science Course Instruction at the University. From there in the year 2014, he joined a tenure-track position at Brandon University in Brandon, Manitoba, Canada, where he currently is active in various professional and scholarly activities. He was promoted to Professor in January 2023. Dr. G, as he is popularly known, is active in research in the field of Data Mining and Big Data. In his 10-year academic career, he has published a total of 400 papers in high-impact conferences in many countries and in high-status journals (SCI, SCIE) and has also delivered invited guest lectures on Big Data, Cloud Computing, Internet of Things, and Cryptography at many international universities. He is an Editor of several international scientific research journals. He currently has active research projects with other academics in Taiwan (China), Singapore, Canada, Czech Republic, Poland and U.S.A. He is constantly looking for collaboration opportunities with foreign professors and students. For more details about Dr. G., please refer to his personal website at (https://people.brandonu.ca/srivastavag/).