Invited Speaker 1: Prof. Scott Fowler, Linköping University, Sweden

Title: Enhancing QoE in Virtual Reality Gaming: Bridging Technology and Sociality

Abstract: This talk delves into enhancing the Quality of Experience (QoE) in Virtual Reality (VR) gaming by integrating cutting-edge technology with sociality. VR gaming demands ultra-low latency, high-quality rendering, and seamless interactivity—requirements that challenge conventional network infrastructures. By leveraging mobile edge networks, this work tackles these challenges through distributed edge computing, reducing latency and delivering immersive user experiences. The talk presents a comprehensive framework for optimizing network resource allocation, balancing processing demands, bandwidth distribution, and delay constraints to sustain superior QoE. Findings reveal how efficient resource management not only elevates user satisfaction but also ensures scalability for large and diverse player bases. Beyond technical advancements, the discussion underscores the role of VR gaming in fostering social connections and collaborative interactions within virtual environments. By aligning technological innovation with societal needs, VR gaming transcends entertainment to become a platform for building meaningful and shared experiences. This exploration highlights the transformative potential of VR gaming in addressing societal challenges through immersive and interactive technology. By combining advanced computational techniques with a strong focus on social engagement, this talk offers insights into designing VR experiences that are both technically groundbreaking and socially impactful.

Short-Bio: Scott Fowler (Senior Member, IEEE, ACM) received his Ph.D. in Computer Science from Wayne State University, Detroit, MI, USA, in 2006. Prior to joining Linköping University (LiU), Campus Norrköping, Sweden, in 2010, he was a Research Fellow at Aston University and Sony Ericsson R&D Lab in the UK, where he collaborated with interdisciplinary academic and industry teams on Next Generation Networks (NGNs). At LiU, he serves as an Associate Professor in the Department of Science and Technology, specializing in Communications and Transport Systems (KTS). Dr. Fowler's research spans Quality of Service (QoS), Quality of Experience (QoE), computer networks (wired and wireless), energy management, cloud computing, the Internet of Things (IoT), optimization, machine learning, network analytics, and security. He has significantly advanced these fields through impactful research and leadership initiatives. An active contributor to the IEEE community, Dr. Fowler has served as Chair/Co-Chair for technical programs at prestigious conferences, including IEEE ICC and IEEE GlobeCom. Additionally, he has held leadership roles, such as Special Interest Groups Coordinator for the IEEE Communications Software (CommSoft) Technical Committee (2012-2017) and Vice-Chair of the IEEE Communications Software and Reliability (CSR) Technical Committee, following terms as Executive Secretary (2021-2023). Dr. Fowler's research has been funded by renowned organizations, including the European Union, Vinnova, Ericsson, Swerock, Heidelberg Materials, Cementa, and SmartBuild. Bridging academia and industry, his work addresses real-world challenges and fosters innovative solutions in technology and infrastructure.

Homepage: https://liu.se/en/employee/scofo47

Invited Speaker 2: Prof. Wenjia Li, New York Institute of Technology, USA

Title: Toward Secure and Trustworthy Internet of Vehicles (IoVs) Using Blockchain and Federated Learning

Abstract: The Internet of Vehicles (IoVs) has revolutionized connected transportation by enabling large-scale data collection and analysis, fostering advancements in traffic management, autonomous driving, and smart cities. However, the proliferation of IoV data presents critical challenges, particularly concerning security, privacy and trustworthiness. To address these issues, this talk explores a novel integration of blockchain technology with federated learning to establish a secure and decentralized framework for IoV data management and analysis. Blockchain's immutable and transparent nature ensures data integrity and trust among IoV nodes, while federated learning enables collaborative machine learning without exposing individual data. By employing cryptographic techniques and consensus mechanisms, the proposed system mitigates adversarial attacks, secures data aggregation, and strengthens network resilience. Performance evaluations through simulations demonstrate the framework's efficacy in enhancing IoV security and scalability. This work underscores the potential of blockchain-enabled federated learning to address pressing IoV challenges, paving the way for robust, privacy-preserving, and trustworthy IoV ecosystems.

Short-Bio: Dr. Wenjia Li received his Ph.D. degree in computer science from the University of Maryland Baltimore County (UMBC), Baltimore, MD, USA, in 2011. In 2014, he joined the Department of Computer Science, New York Institute of Technology, New York, NY, USA as a tenure-track assistant professor, and he is currently a tenured associate professor since September 2020. Prior to joining NYIT, he was a tenure-track Assistant Professor of computer science at Georgia Southern University, Statesboro, GA, USA, from 2011 to 2014. He has authored or co-authored over 100 peer-reviewed publications in various journals and conference proceedings. His current research interests include cyber security, mobile computing, and wireless networking, particularly security, trust, and policy issues for wireless networks, cyber-physical systems, Internet of Things, and intelligent transportation systems. His research has been supported by the National Institute of Health (NIH) and the U.S. Department of Transportation Region 2 University Transportation Research Center (UTRC). He was the recipient of the 2019 IEEE Region 1 Technological Innovation (Academic) Award. He also received the 2020 NYIT Presidential Award for excellence in Student Engagement in Research, Scholarship, or Creative Activities. Recently, he received the 2023 IEEE Region 1 Outstanding Teaching in an IEEE area of interest (University or College) Award. Dr. Li is a Senior Member of the IEEE and a Fellow of the European Alliance for Innovation (EAI).

Homepage: https://site.nyit.edu/bio/wli20