Prof. Kenli Li

Vice President of Hunan University and Director of the National Supercomputing Center in Changsha, China

Short Bio: Kenli Li obtained his computer science Ph.D from Huazhong Universtiy of Science and Technology on 2003, and is currently a Cheung Kong Scholar Chair Professor and the Vice-President of the Hunan University and the Director of National Supercomputing Center in Changsha. He is also the principle investigator (PI) of the Creative Research Groups Program and the Distinguished Youth Science Fund of the National Natural Science Foundation of China. Professor Li is a CCF Fellow and is also supported by the Program for the “Ten-thousand Talents”. Professor Li’s research interests mainly include high-performance computing scheduling and applications, as the PI, he has been responsible for eighteen research projects including the National Key R&D Project and major projects under the National Science and Technology Innovation 2030 Initiative. He was selected for the National Innovation and Excellence Award. As the first-completer, he has won the second-class Award of National Science and Technology Progress (twice), one China Patent Gold Award, and four first-class awards of science and technology from provincial or ministerial departments or academic societies.

Keynote's Title: Exploration of Cloud-Edge-End Collaborative Multimodal Large Models for Fetal Applications

Prof. Francesco Flammini

University of Florence, Italy - IDSIA USI-SUPSI, Switzerland

Short Bio: Prof. Francesco Flammini is a Full Professor at the University of Florence, where he is a member of the Resilient Computing Lab (RCL) and of the Computer Science Ph.D. steering board at the Department of Mathematics and Computer Science “Ulisse Dini”. He is also jointly affiliated with the University of Applied Sciences and Arts of Southern Switzerland, where he leads the Trustworthy Autonomous Systems (TAS) research group at Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI), formerly serving as the program director of the bachelor in Data Science and Artificial Intelligence.

He received his laurea (M.D., 2003), cum laude, and research doctorate (Ph.D., 2006) both in Computer Engineering from the University of Naples Federico II, Italy. He spent 15 years in public and private organizations, including Ansaldo STS (now Hitachi Rail) and IPZS (Italian State Mint and Polygraphic Institute), leading large international programs in intelligent transportation and critical infrastructure protection, as the technical leader and unit head.

Prof. Flammini has also been a Full Professor of Computer Science with a focus on Cyber-Physical Systems at Mälardalen University, Sweden. He previously served as an Associate Professor and the Chair of the Cyber-Physical Systems (CPS) environment at Linnaeus University (Sweden), and as an Adjunct Professor at several universities, including the University of Maryland Global Campus Europe.

Prof. Flammini is an IEEE Senior Member and an active volunteer leader across IEEE societies. He serves on the IEEE Systems, Man, and Cybernetics Society Board of Governors as Associate Vice President for Members and Student Activities and chairs the IEEE SMC Technical Committee on Homeland Security. He has also served as Vice-Chair of the IEEE Computer Society Italy Chapter. He is an IEEE Computer Society Distinguished Visitor and an ACM Distinguished Lecturer.

During his career, he received several research and innovation awards, including the most recent TRA Visions Senior Researcher Competition Award (2024), and the Dalle Molle Award for the Quality of Life Label (2024).

He has (co)authored 200+ publications and has served in leadership roles (chair, invited speaker, steering/program committee member, editor) for 50+ international conferences, books, and journals. He has been PI/technical manager and WP/task leader in 15+ research projects (largely EU-funded) and also serves as an expert evaluator for research agencies. He has supervised 10+ Ph.D. students as primary advisor and co-supervised 20+.

Keynote's Title:

Assoc. Prof. Sadi Alawadi 

Blekinge Tekniska Högskola (BTH), Sweden

Short Bio: Sadi Alawadi is an Associate Professor (Docent) in Artificial Intelligence and Machine Learning at the Blekinge Institute of Technology (BTH), Sweden. He received his Ph.D. in Computer Science (Artificial Intelligence) in 2018 from the Research Center for Intelligent Technologies (CiTIUS) at the University of Santiago de Compostela, Spain. He also holds a Master’s degree in Soft Computing and Intelligent Information Systems from the University of Granada, Spain.

Prior to joining BTH, Dr. Alawadi held several academic and research appointments across Europe, including Assistant Professor at Halmstad University and postdoctoral research positions at Uppsala University, Malmö University, and the Italian National Research Council (CNR-ISTI) in Pisa. His research interests lie in Artificial Intelligence and Machine Learning, with particular emphasis on Federated Learning, the Internet of Things (IoT), Edge and Cloud Computing, and digital forensics.

Dr. Alawadi has authored numerous peer-reviewed publications in leading international journals and conferences, including IEEE Transactions on Industrial Informatics, IEEE Transactions on Engineering Management, Neural Networks, and Information and Software Technology. He is actively engaged in the international research community as a reviewer, guest editor, and organizer of scientific events.

Keynote's Title: The Federated Learning Shift: How We Can Collaboratively Train AI Models Without Violating Data Privacy

Assoc. Prof. Rehmat Ullah

Newcastle University, UK

Short Bio: Dr Rehmat Ullah is an Associate Professor and a member of the National Edge AI Hub, UK, at the School of Computing, Newcastle University, England, UK. His research focuses on network and distributed systems that span the cloud-edge-device continuum and edge intelligence applications. He is currently working on privacy-preserving decentralized machine learning (also known as federated learning) for edge computing systems. His work involves designing and developing algorithms and protocols, building prototypes using testbeds, and evaluating their performance in real-world environments to address practical challenges. His research has been widely published in leading IEEE and ACM venues, and he holds eight patent applications in IoT and distributed AI.  More information is available from his personal website at https://rehmatkhan.com

Keynote's Title: Wireless Edge Intelligence: Deploying Federated Learning at Scale