Speaker I:  Prof. Ka Lok Man, University of Liverpool, UK

Title: AI-IoT: Hybrid Emerging Research on Artificial Intelligence (AI) and Platform Technology (PT)

Abstract: During the last decade, many countries have adopted in recent years road-map for developing the future infrastructure in emerging Internet of Things (IoT) areas such as autonomous vehicles, big data processing technology, wearable technologies and smart home devices. Recent progress in Deep Learning and Machine Learning have unleashed some of the promises of Artificial Intelligence (AI), moving it from the realm of toy applications to a powerful tool that can be leveraged across a wide number of industries. In recognition of these, this talk has selected Artificial Intelligence and Internet of Things as its central theme and presents the state of the art of the AI-IoT: Hybrid Emerging Research on Artificial Intelligence (AI) and Internet of Things (IoT) along with research challenges and opportunities that would be of interest to researchers getting into this exciting field.

Biography: Ka Lok Man holds a Dr. Eng. in Electronic Engineering from Politecnico di Torino, Italy, and a Ph.D. in Computer Science from Technische Universiteit Eindhoven, The Netherlands. He has several years of industrial experience in integrated circuit design (chip designer/research engineer at STMicroelectronics, Agrate, Italy) and has been involved in many industry-oriented research projects in Microelectronics and Computer Science, many of them in cooperation with STMicroelectronics, Synopsys and LG. 

He is currently a Professor at University of Liverpool, UK and the School of Advanced Technology, Xi'an Jiaotong-Liverpool University (XJTLU), Suzhou, China. He has a good publication record and to date has more than 700 published academic articles and a number of IPs as well as received more than 50 international research awards and fellowships.

Currently, he is supervising/co-supervising about 20+ PhD students in AI, WSN, IoT, photovoltaics, image/video processing, radar technology and IC design.

Speaker II: Dr. Yeon Lee, Inha University, Incheon, South Korea

Title: From Intelligent Service Placement to Privacy-Aware AIoT: Emerging Strategies for Secure and Scalable Edge Intelligence 

Abstract: As Artificial Intelligence of Things (AIoT) continues to integrate deep learning into distributed cloud-edge environments, the balance between computational efficiency and data privacy becomes increasingly critical. In this talk, we explore two converging research trajectories that reflect this dual challenge: service placement strategies for High-Performance Computing (HPC) cloud environments, and privacy-preserving deep learning for sensitive domains such as medical imaging. First, we discuss a fuzzy-based resource placement approach that dynamically allocates services in real time, optimizing for cost, latency, and performance in heterogeneous HPC cloud systems. This approach highlights the role of multi-criteria decision-making and feedback learning in managing data-intensive applications. We then transition to the domain of privacy in AIoT systems, focusing on MedErase, a lesion-aware federated unlearning framework tailored for privacy-preserving medical imaging. MedErase demonstrates how selective gradient masking and feature-level knowledge distillation can enable compliance with “rightto-be-forgotten” regulations such as GDPR, while preserving diagnostic utility and minimizing retraining overhead. By connecting these two lines of research, the talk offers a unified perspective on how AIoT systems can be made both intelligent and privacy-aware. We also provide an overview of current trends in federated unlearning, lightweight AI models at the edge, and legal compliance in data-driven systems. The session concludes with future research directions for integrating context-aware service management with secure, federated learning in scalable AIoT environments. 

Biography: Dr. Yeon Lee received her B.S. degree from the School of Computer Science and Engineering at Chongqing University of Posts and Telecommunications, Chongqing, China, and her M.S. and Ph.D. degrees in Computer Science and Information Engineering from Inha University, Incheon, South Korea, completing her Ph.D. in 2017.

She is currently an Assistant Professor in the Department of Computer Science and Information Engineering at Inha University. Her research interests include indoor location-based services, personalized point-of-interest (POI) recommendation systems, geo-sensor data processing, data stream clustering, and spatial data management.

Dr. Lee has made significant contributions to the development of personalized indoor POI recommendation techniques and real-time geo-spatial data stream management systems. Her recent work focuses on enhancing the accuracy and scalability of location-aware services using innovative data analytics and sensor driven models.

In addition to her academic and research achievements, Dr. Lee actively contributes to the academic community. She serves as an editorial board member for two international journals: Human-centric Computing and Information Sciences (HCIS) and Journal of Information Processing Systems (JIPS). She also holds key leadership roles as a board member of the Korea Society for Next-Generation Computing (KSNGC), the Korea Information Processing Society (KIPS), and the Korea Industry Association. Through her research, teaching, and editorial responsibilities, Dr. Lee continues to play a pivotal role in advancing technologies for smart environments and intelligent computing systems. She is a sought-after speaker in the fields of indoor location computing and sensor-based data recommendation.