Emerging Technologies in Cyber-Physical Systems: A Global Seminar Series

Obuda University, Doctoral School of Applied Informatics and Applied Mathematics

Course description

The 12-week long international seminar series is organized by Obuda University with the contribution of four universities:

  • Universidad Autónoma de Nuevo León – UANL (Mexico)
  • University of Portsmouth – UoP (UK)
  • Obuda University – OU
  • National Taiwan University of Science and Technology (NTUST)

with one 70-80 minute online seminar per week. The topics cover multiple areas such as emerging technologies, artificial intelligence, soft computing, medical technologies, robotics, embodied AI, cryptography, emerging technologies in material sciences. The series will be organized within the IEEE SMCS framework.

Course objectives

Spanning three months, the series will feature a rigorous schedule of weekly lectures by prominent professors of 4 countries, each meticulously curated to cover a spectrum of cutting-edge topics listed above. By bringing together a distinguished cadre of lecturers delegated by each participating university, the seminar aims to foster a rich exchange of ideas, stimulate innovation, and facilitate international collaborations.

The seminar series are to explore and discuss advancements, trends, challenges, and applications related to cyber-physical systems (CPS) and emerging technologies within this field. Cyber-physical systems involve the integration of computational algorithms and physical components, often interconnected through networks, enabling them to interact and collaborate. These systems find applications in various domains such as healthcare, transportation, manufacturing, energy, and more.

Key objectives of this course are multiple and diverse to serve both the professional development of young researchers and the development of soft skills. Our purpose is to provide opportunities for:

  • knowledge dissemination;
  • to foster community building of researchers, practitioners, industry experts, and enthusiasts interested in cyber-physical systems;
  • to raise awareness about the significance and potential impact of cyber-physical systems on society, economy, and technology;
  • to foster interdisciplinary dialogue among experts from diverse fields such as computer science, engineering, mathematics, physics, biology, and social sciences;
  • to identify and address challenges, limitations, risks, and ethical considerations associated with the development and deployment of cyber-physical systems;
  • to provide global perspective by featuring speakers, presenters, and participants from different countries, regions, and cultural backgrounds, facilitating a rich and diverse exchange of ideas and experiences.

Details

  • Language: English
  • Target group: graduate research students both PhD and MSc
  • Assessment: online exam
  • Pre-requisites: Advanced English
  • Hours per week: 1 or 2

Weekly breakdown

2024 May1st week (29. 04. – 05. 05.)May 2nd12:00PM (CEST)Annamaria Varkonyi-Koczy:
Anytime Information Processing – A Possible Way of Handling Data, Time and Resource Shortages
OUTeams
2024 May2nd week (06. 05. – 12. 05.)May 8th01:00PM (CEST)Griselda Quiroz Compeán:
Brain machine interfaces to control assistive devices
UANLTeams
2024 May3rd week (13.05. – 19. 05.)May 15th01:00PM (CEST)Stavros Shiaeles:
Protecting IoT Obsolete Devices in Critical Infrastructures –
H2020 CyberTrust Project
UoPTeams
2024 May4th week (20. 05. – 26. 05.)May 22nd01:00PM (CEST)Chao-Lung Yang:
Computer-Vision Human Action Recognition in Manufacturing
NTUSTTeams
2024 June1st week (27. 05. – 02. 06.)May 29th01:00PM (CEST)Tom GedeonOUTeams
2024 June2nd week (03. 06. – 09. 06.)June 05th12:00PM (CEST)Romeo Sánchez Nigenda:
Design and evaluation of AI models and algorithms
for generating personalized learning trajectories
UANLTeams
2024 June3rd week (10. 06. – 16. 06.)June 12th01:00PM (CEST)Mohamed Bader:
Beyond Theory: Machine Learning and AI in Action
for Early Behaviour and Outcome Prediction
UoPTeams
2024 June4th week (17. 06. – 23. 06.)June 19th01:00PM (CEST)Po Ting Lin:
Human-Robot Collaboration with Advanced AI Technologies
NTUSTTeams
2024 June5th week (24. 06. – 31. 06.)June 26th01:00PM (CEST)Eva Dulf:
Fractional calculus in modern control systems
OUTeams
2024 July1st week (01. 07. – 07. 07.)July 03rd01:00PM (CEST)Octavio García Salazar:
Formation flight of multiple UAVs
UANLTeams
2024 July2nd week (08. 07. – 14. 07.)July 10th01:00PM (CEST)Rinat KhusainovUoPTeams
2024 July3rd week (15. 07. – 21. 07.)July 17th01:00PM (CEST)Wei-Chen Lee:
Smart Manufacturing and Cybersecurity
NTUSTTeams

Course materials

Speakers’ Profiles

Title: Brain machine interfaces to control assistive devices

Abstract: Brain-machine interfaces are computational algorithms that interpret neural activity and convert it into signals to control assistive devices such as prostheses or exoskeletons. In this talk we will discuss the process of designing brain-machine interfaces, from the design of experiments to measure electroencephalographic and kinematic signals, to the implementation of algorithms to relate these signals and generate control signals for assistive devices.

Bio: Griselda Quiroz Compeán is an electronic engineer with graduate studies in control and dynamic systems at IPICYT-CONACYT, MX. Since 2009 she is a full time research professor at the School of Mechanical and Electrical Engineering (FIME) of the Universidad Autónoma de Nuevo León (UANL). She is part of the national system of researchers of Mexico. Her work has been reported in more than 20 scientific articles, more than 30 participations in international conferences, she has developed 10 funded research projects and has directed 18 theses at bachelor, master, and doctoral level. Her research interests are in mathematical modeling and control of physiological systems and their applications in brain-machine interface design, design and control of motor assistance devices and mathematical modeling and control of glucose in diabetes. Griselda is an active member of the PIIT Nuevo León Women IDi Committee, of the IEEE Monterrey Section and is a mentor for STEM women, certified by the British Council. In addition, she is currently the coordinator of special projects of the International Relations Secretariat of FIME-UANL.

Title: Design and evaluation of AI models and algorithms for generating personalized learning trajectories.

Abstract: Education research is seeking to revolutionize how students learn. Imagine a dynamic and personalized learning plan that adapts and evolves for each student, like a roadmap to student success. In this talk, we will present a conceptual framework based on Artificial Intelligence techniques and Mathematical Programming to model curriculum information in order to generate personalized learning trajectories. We will explore how these approaches can adapt to subjective factors in the educational process, such as student stress and learning effects. Additionally, we will discuss open research problems and opportunities to develop personalized learning paths to enhance learning in autonomous and digital environments.

Bio: Romeo Sanchez is a professor affiliated with the School of Mechanical and Electrical Engineering (FIME) at the Autonomous University of Nuevo Leon (UANL), Mexico. Romeo holds a Ph.D. in Computer Science from Arizona State University. He is the leader of the Computational Intelligence research group and the academic coordinator of the Artificial Intelligence Engineering program. His research interests include automated planning and scheduling, agent optimization and heuristic search control, intelligent decision support, and distributed systems engineering. His most recent work has focused on developing planning models for education and transportation domains and applying classification algorithms to medical problems.

Title: Formation flight of multiple UAVs

Abstract: The robust consensus of the multiple quadrotors for formation flight is proposed as a solution for the multiagent system (MAS) problem. The Newton-Euler formulation is used in order to describe the mathematical model of the N quadrotors considered as agents and a nonlinear sliding mode control stabilizes the translational and rotational dynamics of each agent so that this control algorithm drives the general sliding manifold to zero in finite time. This general sliding manifold consists of a sliding surface for the navigation of each agent and an auxiliary sliding surface for the consensus of the MAS. Then, the robust consensus algorithm guarantees that the MAS executes the formation flight and pursuit in the trajectory tracking even in presence of disturbances. Finally, real-time experiments show that the MAS successfully reaches the consensus.

Bio: Octavio Garcia Salazar obtained a B.Sc. in electronic engineering and an M.Sc. in electrical engineering with specialization in robotics at the Technological Institute of La Laguna, Torreon Coahuila, Mexico, in 2000 and 2003, respectively. He obtained a Ph.D. in control systems at the University of Technology of Compiègne, France, in 2009. From January 2010 to December 2011, he held a post as a CNRS postdoctoral researcher in autonomous systems at the laboratory LAFMIA UMI 3175 CNRS-CINVESTAV Mexico. From January 2012 to December 2012, he was a visiting researcher at CINVESTAV Monterrey. Since January 2013, he is professor-researcher at the Faculty of Mechanical and Electrical Engineering of the Autonomous University of Nuevo Leon, San Nicolas de los Garza Nuevo Leon, Mexico. His research interests are guidance, navigation, and control of UAVs, UAS, flight dynamics, avionics, and robotics.

Title: Protecting IoT Obsolete Devices in Critical Infrastructures – H2020 CyberTrust Project

Abstract: The H2020 Cyber-Trust project was an ambitious European initiative focused on enhancing cybersecurity for the Internet of Things (IoT) ecosystems. The project, which involves a consortium of partners from various sectors, aimed to create a robust framework for the detection, analysis, and mitigation of cyber threats targeting IoT devices and networks. It leveraged cutting-edge technologies such as blockchain, artificial intelligence, and advanced data analytics to provide comprehensive cybersecurity solutions. The url of the project can be found here https://cyber-trust.eu/ A significant aspect of the Cyber-Trust project is the development and implementation of an advanced Intrusion Detection System (IDS). The IDS within the Cyber-Trust framework is designed to address the unique challenges posed by IoT environments, which include diverse device types, varying communication protocols, and resource constraints. This presentation is focused on the IDS research work done and we will explore how machine learning was utilised along with blockchain and graph theory in order to create a novel solution to mitigate zero-day attacks. 

Bio: Dr. Stavros Shiaeles (male) is Assoc. Prof. in Cybersecurity, at University of Portsmouth. He has extensive research experience that spans several critical areas within the cybersecurity domain. His work has notably contributed to the advancement of knowledge in network security, malware detection, and the development of robust cybersecurity measures against advanced persistent threats (APTs). Dr. Shiaeles has a strong publication record, featuring in respected journals and conferences, underscoring his commitment to advancing the state of cybersecurity through rigorous research. In addition to his academic prowess, Dr. Shiaeles holds several professional certifications such as CEH, CAST611, CCNSP and COBIT5, that attest to his expertise and practical skills in cybersecurity and demonstrate his comprehensive understanding of both the theoretical and practical aspects of securing digital infrastructures against increasingly sophisticated cyber threats.