SPECIAL SESSION

Special Session 1


Title of the proposal Recent Advances in Digital Signal Processing Combined IoT Technology for the Prognostic and Health Management of Complex Electromechanical Equipment
Introduction and topics
Outline of the Session:
Prognostic and health management (PHM) of electromechanical equipment, leveraging the Internet of Things (IoT) and Artificial Intelligence (AI), stands as a compelling subject within the realm of intelligent manufacturing. However, the integration of IoT and AI for PHM applications in complex electromechanical equipment is still in its nascent phase. Consequently, the current implementation of PHM for such equipment is lacking a standardized reference specification and a cohesive architectural framework. Additionally, the degree of interconnection and integration between the design, manufacturing, and operational aspects of complex equipment is not yet adequate. This Special Session is designed to foster an international platform for scientists and engineers to disseminate the latest research findings and innovative ideas on modeling, real-time monitoring, and diagnostics of complex electromechanical systems. We encourage theoretical submissions that seek to deepen the understanding of scholarly techniques, encompassing advanced signal processing, deep learning, fuzzy logic, evolutionary algorithms, swarm intelligence, and other interdisciplinary areas.

Topics of the Session:
This Special Session will gather papers with the topics of interest including, but not limited to:
  • Topic 1 Advanced digital signal processing methodologies for industrial big data to solve the PHM problem of complex electromechanical equipment;
  • Topic 2 Data-driven health indicator and threshold representation methodologies for fault detection, diagnosis, and isolation;
  • Topic 3 AI-based approaches for fault diagnosis of machinery;
  • Topic 4 Spectrum-based capability evaluation on noise disturbance robustness, and weak diagnostic signal enhancement;
  • Topic 5 Applications of AI techniques to imbalanced fault label recognition, and fault diagnosis problems under small sampling data;
  • Topic 6 Big data analysis and processing of PHM of complex equipment combined with Industrial IoT technologies;
  • Topic 7 Advanced machine vision methods and control technologies for robot assisted PHM.
Organizing Committee
Name Affiliation Email
Dr. Zhi-Xin YANG Prof. at State Key Laboratory of Internet of Things for Smart City, University of Macau zxyang@um.edu.mo
Dr. Xianbo WANG Research Fellow, Hainan Institute of Zhejiang University xianbowang@zju.edu.cn

Special Session 2


Title of the proposal Workshop Proposal on Comprehensive Positioning, Computer Vision, Robotics, and AR/VR (OPERA)
Introduction and topics
Outline of the Session:
The workshop focused on the latest advancements and research in comprehensive positioning, robotics, machine vision, and AR/VR. This workshop aims to bring together leading experts, researchers, and practitioners from academia and industry to discuss and share insights on these rapidly evolving fields.
Objectives
- To explore recent developments in comprehensive positioning technologies and their applications.
- To discuss innovative approaches and solutions in robotics, including autonomous systems and human-robot interaction.
- To delve into advancements in machine vision and its integration with AI for enhanced visual processing.
- To examine the current and future state of AR/VR technologies and their impact on various industries.

Topics of the Session:
  • Topic 1 Comprehensive Positioning Systems such as GPS and GNSS advancements, Indoor positioning technologies, Integration of positioning systems with IoT
  • Topic 2 Robotics such as autonomous robots and self-navigation, human-robot collaboration, robotic systems in manufacturing and service industries, LLM for robotics
  • Topic 3 Machine Vision such as deep learning in image processing, real-time object detection and tracking, applications of machine vision in quality control and inspection
  • Topic 4 Augmented Reality and Virtual Reality such as AR/VR in education and training, immersive technologies for simulation and gaming, future trends and challenges in AR/VR development
Organizing Committee
Name Affiliation Email
Dr. Jiehan Zhou Prof. at Shandong University of Science and Technology, Qingdao, China and Docent at University of Oulu, Oulu, Finland. jiehan.zhou@ieee.org
Dr. Jun Zhou Prof. at Shandong University, Jinan, China zhoujun@sdu.edu.cn
Dr. Zhi Wang Prof. at Zhejiang University zjuwangzhi@zju.edu.cn

Special Session 3


Title of the proposal Wearable sensing and assistive devices for robotic rehabilitation
Introduction and topics
Outline of the Session:
Over the last decade, there has been an increasing amount of research into the use of wearable sensing and assistive devices for robotic rehabilitation due to the increasing number of elderly and disabled people with neural diseases, such as stroke, worldwide. Emerging sensing and soft robotic technologies are crucial in the design and development of wearable rehabilitation devices and compliant control systems to help solve this problem. Rapid advances in mechatronic technologies, including soft actuators, wearable sensors and robots or exoskeletons, as well as the human-in-charge or human-in-the-loop control of such soft mechatronic systems, in the last several years have demonstrated the growing significance and potential utility of this unique advantage in the rehabilitation practice. This special session aims to attract experts from all around the world to provide an overview of the current research and developments in the innovative technologies for advanced wearable sensing and assistive devices in medical rehabilitation and healthcare.


Topics of the Session:
Potential topics include but are not limited to the following:
  • Topic 1 Wearable sensors, e-skin, motion or interaction capture
  • Topic 2 Brain-computer interface, neuromuscular interfaces
  • Topic 3 Design and modelling of soft actuators or exoskeletons
  • Topic 4 Compliant human-robot interaction or tracking control
  • Topic 5 Applications and clinical practices of wearable robots
Organizing Committee
Name Affiliation Email
Dr. Wei Meng Wuhan University of Technology, China weimeng@whut.edu.cn
Dr. Dingguo Zhang University of Bath, UK d.zhang@bath.ac.uk
Dr. Shan Luo King's College London, UK shan.luo@kcl.ac.uk
Dr. Mingjie Dong Beijing University of Technology, China dongmj@bjut.edu.cn

Special Session 4


Title of the proposal Intelligent perception, wearable computing, physical and neurological human-machine interaction
Introduction and topics
Outline of the Session:
This session focuses on the latest advancement in intelligent perception, wearable computing, physical and neurological human-machine interaction. With the increasing application of wearable devices in limb assistance and rehabilitation, especially in realizing the physical and neurological human-machine interaction, the requirements for intelligent perception of limbs and improving computing efficiency are increasing. This session aims to fuse the researches in wearable sensors, wearable devices, machine learning, artificial & computational intelligence, sensor fusion & sensor networks, etc, to improve their efficiency in physical and neurological human-machine interaction.

Topics of the Session:
  • Topic 1 Wearable flexible sensors, sensor fusion & sensor networkss
  • Topic 2 Wearable computing, artificial & computational intelligencee
  • Topic 3 Robot-assisted physical rehabilitation, physical human-machine interactionn
  • Topic 4 Biological and physiological signal processingg
  • Topic 5 Neurological rehabilitation, neurological human-machine interactionn
  • Topic 6 Intelligent perception, intelligent control and automation
Organizing Committee
Name Affiliation Email
Dr. Mingjie Dong Beijing University of Technology, China dongmj@bjut.edu.cn
Dr. Jie Zhang Queen’s University Belfast, U.K.  jie.zhang@qub.ac.uk
Dr. Zhongbo Sun Changchun University of Technology, China zbsun@ccut.edu.cn

Special Session 5


Title of the proposal Human intention perception and interaction control of rehabilitation robots
Introduction and topics
Outline of the Session:
This session will explore the latest advancements in rehabilitation robots, focusing on human intention perception and interaction control. As rehabilitation robots are increasingly utilized across diverse medical applications, the primary challenges for current rehabilitation robots are understanding human intentions and delivering appropriate assistance. This session aims to examine state-of-the-art sensor fusion techniques, machine learning, human-robot interaction, and control algorithms that allow robots to accurately interpret and respond to human intentions. We also aim to foster collaboration among researchers, practitioners, and industry experts to explore the potential of rehabilitation robotics in enhancing mobility and independence for individuals with disabilities or recovering from injuries.

Topics of the Session:
  • Topic 1 Exoskeletons, exosuits, actuated orthoses and prostheses;
  • Topic 2 Supernumerary robotic limbs;
  • Topic 3 Neuro-robotics, neuro-prostheses and neuro-rehabilitation;
  • Topic 4 Multimodal sensing technologies in human-robot interaction;
  • Topic 5 Physiological signal filtering and fusion;
  • Topic 6 Intention perception in human-robot interaction;
  • Topic 7 Mechanical design for safe and compliant human-robot interaction;
  • Topic 8 Human-robot cooperation and interaction control.
Organizing Committee
Name Affiliation Email
Dr. Xinxing Chen Southern University of Science and Technology, China chenxx@sustech.edu.cn
Dr. Yu Cao University of Leeds, UK caoyu.leeds@foxmail.com
Dr. Jian Huang Huazhong University of Science and Technology, China huang_jan@mail.hust.edu.cn
Dr. Yuquan Leng Southern University of Science and Technology, China lengyq@sustech.edu.cn
Dr. Chenglong Fu Southern University of Science and Technology, China fucl@sustech.edu.cn

Special Session 6


Title of the proposal Vision-based Behaviour Analysis and Its Applications
Introduction and topics
Outline of the Session:
Vision-base behaviour analysis encompasses the examination of patterns of behavior, emotions, and intentions to gain a deeper understanding of human/animal actions and decision-making processes. This interdisciplinary field has witnessed remarkable growth and has found applications in diverse domains, including psychology, healthcare, agriculture, economics, and so on. We are particularly interested in research papers that explore the following topics, although we welcome submissions on other relevant topics as well:

Topics of the Session:
  • Topic 1 Abnormal Behavior Detection
  • Topic 2 Action Recognition
  • Topic 3 Gaze Estimation
  • Topic 4 Facial Expression Recognition
  • Topic 5 Human-robot Interaction
Organizing Committee
Name Affiliation Email
Dr. Jing Li Tianjin University of Technology jing.li.2003@gmail.com
Dr. Meili Wang Northwest A&F University wml@nwsuaf.edu.cn
Dr. Dongxu Gao University of Portsmouth, UK dongxu.gao@port.ac.uk

Special Session 7


Title of the proposal Enhancing human-machine interaction with both computational intelligence and mechanical intelligence
Introduction and topics
Outline of the Session:
Human-machine interaction (HMI) is vital because it determines how seamlessly humans can interact with and control machines, impacting efficiency, safety, and user satisfaction. Effective HMI design ensures that machines are intuitive and accessible, reducing the likelihood of errors and increasing productivity. In critical fields such as healthcare, transportation, and manufacturing, well-designed HMI can prevent accidents and enhance operational safety. Moreover, as technology advances, innovative HMI solutions drive the adoption of new systems and applications, enabling users to harness the full potential of emerging technologies like artificial intelligence and robotics.

Artificial intelligence (AI) has proven to be a powerful tool in advancing HMI, showcasing its potential through computational intelligence. Additionally, there is a growing emphasis on novel computing theories and control algorithms to reduce the energy consumption of mainstream AI techniques, such as convolutional neural networks (CNNs). Brain-inspired intelligence models, like spiking neural networks (SNNs), are gaining significant attention.

However, the mechanical aspect of intelligence has often been overlooked. Improved mechanical design can substantially reduce computing power requirements and control complexity. For instance, a soft robotic hand with compliance can simplify the control algorithm for grasping tasks due to its passive deformation. Therefore, integrating mechanical intelligence with computational intelligence is crucial for achieving optimal HMI.

We are particularly interested in studies conducted globally to enhance HMI through both computational and mechanical intelligence. This includes research on neuroimaging, biological and statistical approaches, brain-inspired discoveries, and innovative mechanical designs. We invite authors to submit original research that can significantly impact human-machine interaction.

Topics of the Session:
Potential topics include but are not limited to the following:
  • Topic 1 Bio-signal processing algorithms
  • Topic 2 Brain-computer/machine interfaces
  • Topic 3 Smart mechanical designs for HMI
  • Topic 4 Human oriented control strategy for robots
  • Topic 5 Multi-source signal data acquisition
Organizing Committee
Name Affiliation Email
Dr. Li MA Wuhan University of Technology, China excellentmary@whut.edu.cn
Dr. Yi-Feng Chen Southern University of Science and Technology, China chenyf6@sustech.edu.cn
Dr. Wenzhong Yan UCLA, US wzyan24@g.ucla.edu

Special Session 8


Title of the proposal Robotics and Automation for Additive Manufacturing
Introduction and topics
Outline of the Session:
Additive Manufacturing (AM), commonly known as 3D printing, has transformed the landscape of modern manufacturing by enabling the creation of complex geometries, customized components, and rapid prototyping. However, the integration of robotics and automation presents a frontier that promises to further revolutionize this field by enhancing precision, efficiency, and scalability. This special session will delve into the intersection of robotics and automation with AM, showcasing innovative research, practical applications, and future possibilities. The session aims to provide a comprehensive exploration of how these technologies are being leveraged to overcome current limitations and push the boundaries of what is achievable in AM.

Objectives of the special session:
  • To present cutting-edge research and technological advancements in the integration of robotics and automation with additive manufacturing.
  • To explore the practical applications and case studies demonstrating the impact of robotics and automation on improving AM processes.
  • To discuss the challenges, opportunities, and future directions in the development of smart manufacturing systems.
  • To foster interdisciplinary collaboration between researchers, industry professionals, and policymakers to drive innovation in this rapidly evolving field.
  • Robotics and Automation in Additive Manufacturing
    - The role of robotics and automation in enhancing AM capabilities
    - Integration of mechatronics for precise control and automation in AM
    - Utilization of machine vision systems for real-time monitoring and quality control
    - Objectives and significance of the session
  • Robotic Systems for Additive Manufacturing
    - Design and control of robotic systems for AM
    - Multi-axis robotic arms and their applications in AM
    - Collaborative robots (cobots) in AM environments
  • Automation Techniques for Additive Manufacturing
    - Automated material handling and feeding systems
    - Integration of sensors and IoT for process monitoring and control
    - Automated post-processing and finishing techniques
  • Advanced Manufacturing Processes
    - Hybrid manufacturing combining additive and subtractive processes
    - Real-time adaptive manufacturing using robotics
    - Innovations in multi-scale, multi-material and multi-functional 3D printing
  • Applications and Case Studies
    - Industrial applications of robotics and automation in AM (e.g., aerospace, automotive, medical)
    - Case studies demonstrating successful implementation of robotics and automation in AM
    - Challenges and lessons learned from real-world deployments
  • Future Trends and Research Directions
    - Emerging technologies of robotics and automation in AM
    - AI and machine learning for optimizing AM processes
    - Future research challenges and opportunities
  • Panel Discussion and Q&A
    - Open discussion with session speakers and audience
    - Addressing questions and exploring collaborative research possibilities


Topics of the Session:
  • Topic 1 Design and optimization of robotic systems for AM
  • Topic 2 Multi-axis and flexible robotic arms for complex 3D printing tasks
  • Topic 3 Collaborative robots (cobots) in additive manufacturing environments
  • Topic 4 Automated material handling and delivery systems for AM
  • Topic 5 Sensor integration and IoT for real-time monitoring and control in AM
  • Topic 6 Automated post-processing and finishing techniques
  • Topic 7 Hybrid additive-subtractive manufacturing processes
  • Topic 8 Real-time adaptive manufacturing using robotics and AI
  • Topic 9 Multi-material and multi-functional 3D printing innovations
  • Topic 10 Industrial applications of robotics and automation in AM
  • Topic 11 Case studies of successful robotics integration in AM
  • Topic 12 AI and machine learning for process optimization in AM
  • Topic 13 Future trends and emerging technologies in robotics and AM
  • Topic 14 Challenges and opportunities in scaling robotic AM solutions

Conclusion:
This special session on "Robotics and Automation for Additive Manufacturing" will offer valuable insights into the latest advancements and future trends in this dynamic field. By bringing together experts from academia, industry, and government, the session aims to foster innovation, collaboration, and the dissemination of knowledge to drive the future of additive manufacturing.
Organizing Committee
Name Affiliation Email
Dr. Charlie C.L. Wang The University of Manchester, United Kingdom changling.wang@manchester.ac.uk
Dr. Yong Chen University of Southern California yongchen@usc.edu

Special Session 9


Title of the proposal Artificial intelligence, system control and applications
Introduction and topics
Outline of the Session:
The session titled “Artificial Intelligence, System Control and Applications” aims to explore the intersection of artificial intelligence (AI) and system control, focusing on how AI technologies are revolutionizing the design, optimization, and implementation of control systems across various industries. As AI continues to advance, its applications in system control have become increasingly sophisticated, leading to enhanced efficiency, adaptability, and functionality in complex systems. This session will delve into both theoretical and practical aspects, providing a platform for discussing innovative research, emerging trends, and real-world applications.

Key objectives of the session include:
  • a) Exploring the integration of AI techniques in traditional control systems: How machine learning and other AI methodologies can augment or replace classical control strategies.
  • b) Discussing advanced control architectures enabled by AI: The design and implementation of novel control systems that leverage AI for improved performance and robustness.
  • c) Showcasing application domains: Highlighting specific case studies and applications where AI-driven control systems are making a significant impact.
  • d) Encouraging interdisciplinary collaboration: Fostering dialogue between experts in AI, control theory, and various application domains to spur future innovations.


Topics of the Session:
  • Topic 1 Autonomous Systems and Intelligent Agents
    a) Designing and implementing AI-based control strategies for autonomous systems that require real-time decision-making and interaction with their environment.
    b) Examples from drones, self-driving cars, and automated manufacturing systems.
  • Topic 2 Human-Machine Collaboration in Control Systems
    a) Investigating how AI can facilitate more intuitive and effective interactions between humans and automated control systems.
    b) Studies on human-in-the-loop control systems and the role of AI in enhancing operator decision-making.
  • Topic 3 Real-World Applications and Case Studies
    a) Presentation of real-world applications demonstrating the successful integration of AI in control systems.
    b) Examples from industries such as energy, healthcare, transportation, and manufacturing.
  • Topic 4 Future Trends and Research Directions
    a) Discussing emerging trends, challenges, and potential research directions in the field of AI and system control.
    b) Insights into how advancements in AI technologies could shape the future of control systems.
Organizing Committee
Name Affiliation Email
Dr. Fengwei Gu School of Computer Science and Technology, Harbin University of Science and Technology, China gufengwei123@126.com
Dr. Ao Li School of Computer Science and Technology, Harbin University of Science and Technology, China ao.li@hrbust.edu.cn
Dr. Gongfa Li Wuhan University of Science and Technology, China ligongfa@wust.edu.cn
Dr. Uche Ogenyi University of Portsmouth, UK uchenna.ogenyi@port.ac.uk

Special Session 10


Title of the proposal Challenges and Opportunities in Clinical Translation of Robotic Rehabilitation Technology
Introduction and topics
Outline of the Session:
The special session will investigate the complex clinical translation roadmap from conceptualizing robotic rehabilitation technologies to their clinical adoption. It will address challenges at each stage, from identifying clinical needs to achieving regulatory approval and widespread clinical use. Attendees will explore the multifaceted challenges and opportunities in technical development, regulatory compliance, and integration into diverse healthcare systems in different regions. By bringing together experts from different disciplines, this session aims to foster a comprehensive understanding of the opportunities and challenges in clinical translation, facilitate the development and adoption of effective robotic rehabilitation technologies to ultimately improve patient outcomes.

  • Introduction and Welcome (3 minutes)
    Introduction by the session organizer, overview of the session's theme and objectives.
  • Speaker Presentations (15 minutes)
    Each speaker presents their topic, followed by a brief Q&A session.
  • Panel Discussion (30 minutes)
    Moderated discussion among the speakers from interdisciplinary perspectives, and future directions. Participants to ask questions and engage with the speakers.
  • Closing Remarks (2 minutes)
    Summary of key points discussed and final thoughts by the session organizer.


Topics of the Session:
  • Topic 1 From Lab to Clinic: Real-World Implementation of Robotic Rehabilitation Devices
    a) Overview of the key challenges faced during the transition from research to clinical practice.
    b) Success stories and lessons learned from real-world implementations.
    Speaker: TBC
  • Topic 2 Technical Requirements and Engineering Challenges in Developing Rehabilitation Robots
    a) Detailed exploration of the technical challenges in designing and manufacturing effective rehabilitation robots.
    b) Case studies on how innovative robotic solutions are designed to overcome engineering challenges including advances in sensor technology, machine learning, and human-robot interaction.
    Speaker: TBC
  • Topic 3 Navigating the Regulatory Landscape: From Prototype to Clinically Approved Device
    a) Regulatory approval process for medical devices in different regions.
    b) Case studies of best practices for gaining regulatory approval.
    Speaker: Prof Edward Draper and Prof. Peter Arnold, University of Leeds
  • Topic 4 Global challenges in Clinical Adoption of Robotic Rehabilitation Technologies
    a) Analysis of how cultural and economic barriers including attitudes towards technology, language barriers, affordability, insurance coverage, and varying healthcare infrastructures impact clinical adoption.
    b) Discuss strategies for overcoming challenges in different countries.
    Speaker: Dr Aiqin Liu on relevant works from AMS Networking grant 2024.
  • Topic 5 A clinician's perspective on Rehabilitation Robots
    a) Clinical effectiveness and patient outcomes from case studies
    b) Challenges and barriers to adoption from clinical practice and patient acceptance
    Speaker: TBC
Organizing Committee
Name Affiliation Email
Dr. Aiqin Liu University of Leeds a.liu@leeds.ac.uk
Dr. Shane Xie University of Leeds s.q.xie@leeds.ac.uk

Special Session 11


Title of the proposal Biomedical signal processing and health informatics
Introduction and topics
Outline of the Session:
The fields of Biomedical Signal Processing and Health Informatics are pivotal in the advancement of healthcare technologies and systems. These areas focus on the acquisition, analysis, and interpretation of complex biological signals and the integration of human-centered data to improve health outcomes. However, the implementation of sophisticated techniques in biomedical signal processing and the holistic management of health informatics data remains challenging. This Special Session is intended to create an international forum for researchers and practitioners to share the latest research achievements and innovative ideas in these domains. We invite theoretical and applied submissions that aim to advance the understanding and application of cutting-edge methodologies, including advanced signal processing, machine learning, neural networks, wearable technology, and other interdisciplinary approaches.

Topics of the Session:
This Special Session will gather papers with topics of interest including, but not limited to:
  • Topic 1 Advanced signal processing techniques for the analysis of biomedical signals, such as ECG, EEG, EMG, and PPG.
  • Topic 2 AI-driven methods for the diagnosis and prognosis of medical conditions based on biomedical signals.
  • Topic 3 Development of wearable devices and sensors for continuous health monitoring and data collection.
  • Topic 4 Integration of health informatics data with electronic health records (EHRs) for personalized medicine and healthcare.
  • Topic 5 Privacy-preserving methods and secure data transmission in the collection and analysis of biomedical and human informatics data.
  • Topic 6 Development of assistive technologies and rehabilitation systems based on biomedical signals.
This Special Session aims to provide a platform for the dissemination of innovative research findings, encouraging cross-disciplinary collaboration and the exploration of novel solutions to current challenges in biomedical signal processing and human informatics.
Organizing Committee
Name Affiliation Email
Dr. Bo Sheng Distinguished Lecturer at Shanghai University, Shanghai, China shengbo@shu.edu.cn
Dr. Tianzhe Bao Assistant Prof. at University of Health and Rehabilitation Sciences, Shandong, China tianzhe.bao@uor.edu.cn
Dr. Chao Wang Lecturer at Shanghai University, Shanghai, China elcw@shu.edu.cn

Special Session 12


Title of the proposal AI-Enabled Human Behavior Detection for Human-Robot Interaction
Introduction and topics
Outline of the Session:
Human behavior detection is critical to creating intuitive and effective human-robot interactions (HRI), paving the way for robots to be able to perceive, make decisions, and act in a collaborative manner. Artificial intelligence (AI) can enhance the understanding and responses of robots working alongside humans. The theme of this session is integrating smart sensors, computer vision, intelligent detection, behavioral modeling, and machine learning technologies to enable robots to interact and collaborate with humans intelligently and safely. The session aims to bring together researchers, practitioners, and industry experts to share their findings and insights and discuss the importance and potential of intelligent/AI-enabled human behavior detection in enhancing HRI. By addressing the challenges of accurately interpreting human actions and intentions, the session will emphasize the development of algorithms that ensure robots can adapt to dynamic environments and diverse human behaviors.

Topics of the Session:
  • Topic 1 Machine learning for human behavior recognition
  • Topic 2 Wearable sensors and ambient intelligence
  • Topic 3 Real-time detection and adaptation
  • Topic 4 Multimodal data fusion techniques
  • Topic 5 Predictive models and intent recognition systems
  • Topic 6 Human behavior modeling in HRI
  • Topic 7 Human-robot interface for HRI
  • Topic 8 Statistical HRI modelling
  • Topic 9 Non-verbal human-robot communication
  • Topic 10 Cyber-Physical Design for Human Abnormal Behavior Detection
This Special Session aims to provide a platform for the dissemination of innovative research findings, encouraging cross-disciplinary collaboration and the exploration of novel solutions to current challenges in biomedical signal processing and human informatics.
Organizing Committee
Name Affiliation Email
Dr. Xin Zhang Shenyang Institute of Automation, Chinese Academy of Sciences, China zhangxin@sia.cn
Dr. Yinlong Zhang Shenyang Institute of Automation, Chinese Academy of Sciences, China zhangyinlong@sia.cn
Dr. Gustavo Lahr Hospital Israelita Albert Einstein, Brazil Gustavo.Lahr@einstein.br
Dr.Jiahui Yu Zhejiang University, China jiahui.yu@zju.edu.cn

Special Session 13


Title of the proposal Digital Transition and Digital Entrepreneurship in the Era of AI and IoT: Implications for Modern Managers
Introduction and topics
Outline of the Session:
As Artificial Intelligence (AI), Internet of Things (IoT) and their integrations are reshaping the business world, business leaders and policymakers are devoting their resources and efforts in understanding advanced digital technologies, implementing new ways to manage and regulate new businesses, and facilitating organizations to adapt to the new business environment. The conjuncture of new digital technologies and managerial efforts present unique opportunities and challenges to business of all levels, including individuals, organizations, and the ecosystem that call for scholars and practitioners to investigate with multifaceted approaches and managerial perspectives.
This session aims to foster a rich dialogue among management scholars, industry practitioners, and policymakers to share insights, challenges, and best practices in leveraging digital technologies for entrepreneurial success and supply chain excellence. Participants are expected to delve into various aspects of digital entrepreneurship, focusing on how AI and IoT can drive innovation, enhance decision-making, and create sustainable competitive advantages. Submissions that explore case studies, theoretical frameworks, and practical applications are anticipated to advance the field of digital transformation and digital entrepreneurship. We look forward to receiving innovative and impactful research contributions that advance our understanding of digital entrepreneurship in the era of AI and IoT.

Topics of the Session:
  • Topic 1 Entrepreneurial Innovation with AI and IoT
  • Topic 2 Digital Transformation in Supply Chain Management
  • Topic 3 Data Analytics and Decision-Making
  • Topic 4 Strategic Partnerships and Ecosystem Development
  • Topic 5 Talent Management and Skills Development
  • Topic 6 Human-Centric AI and IoT Applications
Organizing Committee
Name Affiliation Email
Dr. Yi-Chun Huang National Kaohsiung University of Science and Technology peterhun@nkust.edu.tw
Dr. Min-Li Yang National Kaohsiung University of Science and Technology minly@nkust.edu.tw
Dr. Cheng-Feng Lee National Kaohsiung University of Science and Technology jflee@nkust.edu.tw
Dr. Szu-Yin Lin National Kaohsiung University of Science and Technology szu1104@nkust.edu.tw
Dr. Dan-Wei Wen National Kaohsiung University of Science and Technology marianwen@nkust.edu.tw