سخنرانان کلیدی

تعداد بازدید:۱۱۸۵

 

سخنران ویژه مراسم افتتاحیه

 

 

جناب آقای دکتر

علی خاکی صدیق

 

 

 

 

معاونت محترم آموزشی وزارت علوم، تحقیقات و فن آوری

 

سخنرانی های کلیدی کنفرانس:

 

Artificial Intelligence in Autonomous and Surgical Robotics

Abstract:

Artificial intelligence has found its permanent role among cutting-edge researches in various applications. As a major part of each autonomous robot, a camera plays a significant role to extract rich information on the surrounding environment.  Object detection and tracking is a necessary task for the autonomous robot to maneuver suitably in unstructured environment. In the first part of this presentation, the development, implementation, and optimization of deep learning approaches especially for object detection and tracking are addressed. The focus is applications used for autonomous robots and vehicles, while some of the related accomplished industrial projects are introduced.  Application of Artificial intelligence is not limited to industrial applications. Surgical robotics is another hot research topic, which is boosted by AI in different areas of applications. Among them, we focus on intraocular surgery in this presentation. Since the human eye is a highly delicate organ with minuscule anatomic structures, the ocular surgeries are needed to be performed under extra precision and high manipulation capabilities. This fact underlines the importance of assistive technologies in eye surgical procedures. In this presentation recent breakthroughs along with new areas in which haptic systems and assistive technologies might provide a viable solution to overcome current challenges are reviewed, some of our products in robotic surgery, and haptic assisted eye surgery trainings will be reviewed in this presentation.

Biography:

Hamid D. Taghirad has received his B.Sc. degree in mechanical engineering from Sharif University of Technology, Tehran, Iran, in 1989, his M.Sc. in mechanical engineering in 1993, and his Ph.D. in electrical engineering in 1997, both from McGill University, Montreal, Canada. He is currently the University Vice-Chancellor for Global strategies and International Affairs, Professor and the Director of the Advanced Robotics and Automated System (ARAS), Department of Systems and Control, Faculty of Electrical Engineering,  K. N. Toosi University of Technology, Tehran, Iran. He is a senior member of IEEE, and Editorial board of International Journal of Robotics: Theory and Application, and International Journal of Advanced Robotic Systems. His research interest is robust and nonlinear control applied to robotic systems. His publications include five books, and more than 250 papers in international Journals and conference proceedings.

Professor Hamid D. Taghirad

Professor and the Director of the Advanced Robotics and Automated System (ARAS),

Department of Systems and Control,

Faculty of Electrical Engineering, 

K. N. Toosi University of Technology,

Tehran-Iran

 

Autonomous Systems for Medicine for Healthier Communities

Abstract:

Surgical, therapeutic, diagnostic, and rehabilitative interventions can be significantly enhanced using computer-integrated robotic systems with real-time decision-making capabilities that work under the direct, shared, or supervisory control of medical professionals (surgeons, therapists and physicians). Incorporating appropriate levels of autonomy in systems for healthcare delivery has the potential to lower the mental and physical loads on clinicians while improving the reliability, precision and safety of the interventions for patients. For example, an autonomous system can help to build computerized models of a medical intervention, learned through demonstration by human experts, and transfer the learned skills to a robot that is in charge of providing intelligent assistance to surgeons or therapists. In this seminar, Dr. Mahdi Tavakoli, Professor at the University of Alberta, discusses several applications of medical robotics and their related challenges, and offers solutions based on combining the capabilities of humans with the precision, accuracy, and fast decision-making capabilities of machines.

Biography:

Mahdi Tavakoli is a Professor in the Department of Electrical and Computer Engineering, University of Alberta, Canada. He received his BSc and MSc degrees in Electrical Engineering from Ferdowsi University and K.N. Toosi University, Iran, in 1996 and 1999, respectively. He received his PhD degree in Electrical and Computer Engineering from the University of Western Ontario, Canada, in 2005. In 2006, he was a post-doctoral researcher at Canadian Surgical Technologies and Advanced Robotics (CSTAR), Canada. In 2007-2008, he was an NSERC Post-Doctoral Fellow at Harvard University, USA. Dr. Tavakoli’s research interests broadly involve the areas of robotics and systems control. Specifically, his research focuses on haptics and teleoperation control, medical robotics, and image-guided surgery. Dr. Tavakoli is the lead author of Haptics for Teleoperated Surgical Robotic Systems (World Scientific, 2008). He is a Senior Member of IEEE and an Associate Editor for IEEE/ASME Transactions on Mechatronics, Journal of Medical Robotics Research, and Mechatronics.

Professor Mahdi Tavakoli

Professor in the Department of Electrical and Computer Engineering,

University of Alberta,

Edmonton-Canada

 

 

Time-Delay Origins of Fundamental Limits and Tradeoffs Between Risk of Large Fluctuations and Network Connectivity

Abstract:

In this talk, we visit a class of consensus networks, with particular emphasis on applications related to autonomous vehicle platooning and synchronous power networks, and introduce a notion of risk to assess robustness of such networks in presence of communication time-delay and external disturbances. We show that risk of large fluctuations in measurable outputs can be quantified as functions of Laplacian eigen-spectrum. We present several hard limits and fundamental tradeoffs among the risk measures, network connectivity, communication time-delay, and statistics of exogenous stochastic disturbance. Simultaneous presence of disturbance and time-delay in networks  exhibits some idiosyncratic behavior, for instance, weakening (improving) network connectivity may result in lower (higher) levels of risk. Such phenomena impose counter-intuitive challenges in design of optimal networks that are subject to time-delay and external stochastic disturbances.

Biography:

Nader Motee received his B.Sc. degree in Electrical Engineering from Sharif University of Technology in 2000, M.Sc. and Ph.D. degrees from University of Pennsylvania in Electrical and Systems Engineering in 2006 and 2007, respectively. From 2008 to 2011, he was a postdoctoral scholar in the Control and Dynamical Systems Department at Caltech. He is currently a Professor in the Department of Mechanical Engineering and Mechanics at Lehigh University. His research interests include distributed control systems and real-time robot perception. He is a past recipient of several awards including the 2019 Best SIAM Journal of Control and Optimization Paper Prize, the 2008 AACC Hugo Schuck best paper award, the 2007 ACC best student paper award, the 2008 Joseph and Rosaline Wolf best thesis award, a 2013 Air Force Office of Scientific Research Young Investigator Program award, a 2015 NSF Faculty Early Career Development award, and a 2016 Office of Naval Research Young Investigator Program award.

Professor Nader Motee

Professor in the Department of Mechanical Engineering and Mechanics

Lehigh University

 Bethlehem, Pennsylvania

USA

 

 

Artificial Intelligence for Industry and Envirenment

Abstract:

Adaptability and advanced services for industrial manufacturing require an intelligent technological support for understanding the production process characteristics also in complex situations. Quality control is specifically one of the activities in manufacturing which is very critical for ensuring high-quality products and competitiveness on the market. Similarly, protection of the environment requires ability to adjust the understanding of the current status by considering the natural dynamics of the environment itself and the natural phenomena. Artificial intelligence can provide additional flexible techniques for designing and implementing monitoring and control systems both for industrial and environmental applications, which can be configured from behavioral examples or by mimicking approximate reasoning processes to achieve adaptable systems. This talk will analyze the opportunities offered by artificial intelligence technologies to support the realization of adaptable operations and intelligent services in industrial applications, specifically focusing on manufacturing processes and quality control, as well as in environmental monitoring, especially for land management and agriculture.

Biography:

Vincenzo Piuri has received his Ph.D. in computer engineering at Politecnico di Milano, Italy (1989). He is Full Professor in computer engineering at the Università degli Studi di Milano, Italy (since 2000). He has been Associate Professor at Politecnico di Milano, Italy and Visiting Professor at the University of Texas at Austin and at George Mason University, USA. His main research interests are: artificial intelligence, computational intelligence, intelligent systems, machine learning, pattern analysis and recognition, signal and image processing, biometrics, intelligent measurement systems, industrial applications, digital processing architectures, fault tolerance, dependability, and cloud computing infrastructures. Original results have been published in more than 400 papers in international journals, proceedings of international conferences, books, and book chapters. He is Fellow of the IEEE, Distinguished Scientist of ACM, and Senior Member of INNS. He is President of the IEEE Systems Council (2020-21), and has been IEEE Vice President for Technical Activities (2015), IEEE Director, President of the IEEE Computational Intelligence Society, Vice President for Education of the IEEE Biometrics Council, Vice President for Publications of the IEEE Instrumentation and Measurement Society and the IEEE Systems Council, and Vice President for Membership of the IEEE Computational Intelligence Society. He is Editor-in-Chief of the IEEE Systems Journal (2013-19), and Associate Editor of the IEEE Transactions on Cloud Computing, and has been Associate Editor of the IEEE Transactions on Computers, the IEEE Transactions on Neural Networks, the IEEE Transactions on Instrumentation and Measurement, and IEEE Access.  He received the IEEE Instrumentation and Measurement Society Technical Award (2002) and the IEEE TAB Hall of Honor (2019). He is Honorary Professor at: Obuda University, Hungary; Guangdong University of Petrochemical Technology, China; Northeastern University, China; Muroran Institute of Technology, Japan; and the Amity University, India.

Professor Vincenzo Piuri

FIEEE

Professor in the Department of Computer Science

Università degli Studi di Milano

Milan- Italy

 

 

Autonomous Synchronization of Heterogeneous Multi-Agent Systems

Abstract:

In this talk, we will introduce a new type of synchronization problem for heterogeneous multi-agent systems (MASs), called autonomous synchronization. In this problem, neither the synchronized agent dynamics nor the synchronized states are specified a priori, instead, they are autonomously determined by the inherent properties and the initial states of agents, thus providing an MAS with more degrees of adaptability and higher synchronization efficiency. To achieve autonomous synchronization, a novel dynamics update law and a synchronizing control law are proposed and the sufficient solvability conditions are explicitly revealed in both continuous-time and discrete-time settings. Moreover, in the continuous-time setting, a core technical problem is the so-called asymptotic decoupling of stable modes for a linear time varying system containing stable and unstable modes. The necessary and sufficient conditions are derived for this problem based on the newly developed techniques for analyzing matrix exponential and state transition matrix. 

Biography:

Zhiyong Chen received the B.E. degree from the University of Science and Technology of China, and the M.Phil. and Ph.D. degrees from the Chinese University of Hong Kong, in 2000, 2002 and 2005, respectively. He worked as a Research Associate at the University of Virginia during 2005-2006. He joined the University of Newcastle, Australia, in 2006, where he is currently a Professor and Head of School of Electrical Engineering and Computing. He was a Changjiang Chair Professor with Central South University, Changsha, China. His research interests include non-linear systems and control, biological systems, and multi-agent systems. He is/was an associate editor of Automatica, IEEE Transactions on Automatic Control, and IEEE Transactions on Cybernetics.

Professor Zhiyong Chen

Professor and head of school of Electrical Engineering and Computing

University of Newcastle

Australia

 

 

Cyber Security Trends in the World of Internet of Things. Cloud and Big Data

Abstract:

The developments in the Internet of Things (IoT), cloud services and data analytics, over the last two decades, on the one hand, have continued to open up new opportunities, but on the other hand, are posing several major challenges in cyber security and privacy. For instance, the dramatic growth in the deployment of IoT in a range of business sectors, such as in healthcare, transportation, or electricity grids, have introduced IoT enabled attacks on such critical infrastructures. It is essential that these systems should be able to counteract these attacks, but they also need to be resilient to ensure continuous provision of critical services.

In this talk, we will discuss the various attacks in IoT systems and cloud infrastructures, and then consider cyber security technologies and machine learning techniques can be deployed to mitigate these attacks and realize adaptable secure systems. We will conclude with some open research challenges in cyber security in these areas.

Biography:

Prof Vijay Varadharajan has held the Global Innovation Chair in Cyber Security at the University of Newcastle since March 2017. He is also the Director of Advanced Cyber Security Engineering Research Centre (ACSRC) at Newcastle. Previously he was Microsoft Chair Professor in Innovation in Computing at Macquarie University (2001-2017). At Macquarie, he conceived the concept of an interdisciplinary institute in Cyber Security and was the founder of the Optus MQ Cyber Security Hub. Prior to this he was Dean of School of Computing and IT at University of Western Sydney (1996-2000).

Professor Vijay Varadharajan

Global Innovation Chair Professor

Director: Advanced Cyber Security Engineering Research Centre (ACSRC)

 

University of Newcastle

Australia

 

 

Fusing predictive control and machine learning towards safe autonomous systems

Abstract:

New technologies like self-driving cars, robots, and the massive impact of digitalization change every aspect of our lives. This leads to an ever-increasing need for autonomous systems that can adapt and learn to account for changing conditions. Simultaneously, the available data and information increase at a breathtaking rate, driven by digitalization and concurrent systems monitoring.  Control and decision-making often lie at the core of many of the involved technologies and underlying functionalities.  Autonomous systems require high flexibility in the controller design and application. Additionally, an increasing complexity to describe and handle these systems occurs. Machine learning and artificial intelligence are seen as critical technologies to tackle the challenges. However, the use of machine learning methods in control and automation is still in its infancy. One of the main reasons for this is the need for the dependable, explainable, and safe operation of autonomous systems, especially for systems in immediate interactions with humans. We focus on model predictive control (MPC) combined with machine learning approaches. Fusing predictive control with machine learning approaches is promising, as it allows to adapt to changes and to use data-driven or hybrid models. We outline results towards the fusion of predictive control and learning approaches, focusing on guarantees of performance and stability. After a brief introduction, we present different strategies that guarantee stable and safe operation and outline their application towards robotics, driving, and chemical processes.

Biography:

Prof Rolf Findeisen received the MSc degree in Chemical Engineering from the University of Wisconsin–Madison, Madison, WI, USA, and a Diploma degree from the University in Stuttgart in Engineering Cybernetics in 1997, and the Dr.-Ing. degree from the University of Stuttgart, Stuttgart, Germany, in 2005. He was a Research Assistant with the Automatic Control Laboratory, ETH Zurich, Switzerland, and a Researcher with the Institute for Systems Theory and Automatic Control, University of Stuttgart. Prof. Findeisen heads the Systems Theory and Automatic Control Laboratory, Otto-von-Guericke University Magdeburg, Germany, as a full chaired Professor. He had research stays and guest professorships at the Massachusetts Institute of Technology Cambridge, EPF Lausanne, the University of California at Santa Barbara, Imperial College London, NTNU Trondheim, Norway.

Prof Findeisen was the IPC Co-Chair of the IFAC World Congress 2020, IEEE Control Systems Society International Affairs Chair from 2012-2015. He is currently the Chair of the TC on Chemical Process Control of IFAC, and the TC on Process Control of the IEEE CSS. He is a member of the reviewing board of the German research foundation (DFG). Prof. Findeisen delivered multiple plenary and keynote talks. He has served as editor and associate editor of various journals, e.g., IEEE Control Systems Magazine, IEEE Transactions on Networked Systems, J. Optimal Control Applications and Methods and Processes.

Prof Findeisen’s research interests include the areas of control and monitoring of autonomous systems, predictive control, machine learning, fusing learning and control, cyber-physical systems, uncertainty, robustness. Fields of applications span from mechatronics, aerospace systems to chemical and biotechnological processes, robotics, energy systems, and systems medicine.

Professor Rolf Findeisen

Institute for Automation Engineering (IFAT)
  Laboratory for Systems Theory and Automatic Control
  Otto-von-Guericke University 


  Magdeburg - Germany

 

 

Artificial Intelligence and Energy

Abstract:

Artificial Intelligence (AI) is suffering a great impact in the industry and society. According to the White Paper from the European Comission, “AI refers to systems that display intelligent behaviour by analysing their environment and taking actions – with some degree of autonomy – to achieve specific goals. AI-based systems can be purely software-based, acting in the virtual world (e.g., voice assistants, image analysis software, search engines, speech and face recognition systems) or AI can be embedded in hardware devices (e.g., advanced robots, autonomous cars, drones or Internet of Things applications). The speak will cover the following questions: Do we know what is Artificial Intelligence (AI)?; Is there any international consensus about AI?; What is the way of&to the AI?; What is everyone doing on AI? AI&Energy: what is happening?. The AI applied to Energy will be addressed, analysing the main scientific contributions over the time per countries, methods employed, topics covered, etc. Finally, the case of the Wind Energy will be presented, one of the main industries in Renewable Energy and Sustainability

Biography:

Fausto works at UCLM as Full Professor (Accredited as Full Professor from 2013), Spain, Honorary Senior Research Fellow at Birmingham University, UK, Lecturer at the Postgraduate European Institute, and he has been Senior Manager in Accenture (2013-2014). He obtained his European PhD with a maximum distinction. He has been distinguished with the prices: Runner Prize for Management Science and Engineering Management Nominated Prize (2020), and Advancement Prize (2018), First International Business Ideas Competition 2017 Award (2017); Runner (2015), Advancement (2013) and Silver (2012) by the International Society of Management Science and Engineering Management (ICMSEM); Best Paper Award in the international journal of Renewable Energy (Impact Factor 3.5) (2015).  He has published more than 150 papers (65 % ISI, 30% JCR and 92% internationals), some recognized as: “Applied Energy” (Q1, as “Best Paper 2020”), “Renewable Energy” (Q1, as “Best Paper 2014”); “ICMSEM” (as “excellent”), “Int. J. of Automation and Computing” and “IMechE Part F: J. of Rail and Rapid Transit” (most downloaded), etc. He is author and editor of 25 books (Elsevier, Springer, Pearson, Mc-GrawHill, Intech, IGI, Marcombo, AlfaOmega,…), and 5 patents. He is Editor of 5 Int. Journals, Committee Member more than 40 Int. Conferences. He has been Principal Investigator in 4 European Projects, 6 National Projects, and more than 150 projects for Universities, Companies, etc. His main interest are: Artificial Intelligence, Maintenance, Management, Renewable Energy, Transport, Advanced Analytics, Data Science. He is being expert in the European Union in AI4People (EISMD), and ESF. He is Director of www.ingeniumgroup.eu. 

Professor Fausto Pedro García Márquez

Full Professor at Castilla-La Mancha University, Ciudad Real-Spain


  

 

 

 

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