Fall 2021 IEEE IMS Virtual Distinguished Lecturer Webinar Series

The "IEEE IMS Virtual Distinguished Lecturer Webinar Series" allows us to continue providing IMS members with our respected and reputable Distinguished Lecturer program. Registration is completely free and limited to the first 100 registrants per event. In the case you are unable to register, you can also attend the webinar concurrently via Facebook Live, or access the webinar recording following the event.

Webinars are 60-minutes long, including 15 minutes for Q&A. We are thrilled to offer you the opportunity to attend these webinars, and we encourage your participation!

Questions? Contact us at: [email protected].

Daniel Watzenig

Professor, Graz University of Technology

Virtual Vehicle Research

Austria

Daniel Watzenig

Biography

Daniel Watzenig was born in Austria. He holds a doctorate in electrical engineering and was awarded the venia docendi (adjunct professorship) for electrical measurement science and signal processing from Graz University of Technology, Austria. He is CTO and Head of the Electronics Systems and Software Department at Virtual Vehicle Research Graz. In addition, he was appointed as a Full Professor of Multi-Sensor Perception of Autonomous Systems at the Institute of Computer Graphics and Vision, Faculty of Computer Science and Biomedical Engineering, Graz University of Technology, Austria.

His research interests focus on sense & control of autonomous vehicles, sensor fusion, reinforcement learning and decision making under uncertainty. He is the author or co-author of over 200 peer-reviewed papers, book chapters, patents, and articles. He is the Editor-in-Chief of the SAE Int. Journal on Connected and Automated Vehicles (SAE JCAV). Since 2019 he is invited guest lecturer at Stanford University, USA, teaching multi-sensor perception for autonomous systems (Principles of Robot Autonomy). He is the founder of the Autonomous Racing Graz Team. Since 2024 he is Vice Chair and Member of the Executive Committee of the IEEE Austria Section. He is IEEE Distinguished Lecturer in the field of autonomous vehicles, Board Member of the INSIDE Industry Association (European Initiative on Intelligent Digital Systems) and Member of the Academic Advisory Council of PAVE (global Partners for Automated Vehicle Education). He has been a consultant and appointed expert for military robotics for the Armaments and Defense Technology Agency of the Austrian Armed Forces since 2019.

Affiliation(s)

Professor, Graz University of Technology

Virtual Vehicle Research

Austria

September 23, 2021 at 9:00 am ET

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Autonomous Driving in 2021 - Challenges, Progress, and Recent Advances

About Dr. Watzenig's Webinar

Autonomous driving is seen as one of the pivotal technologies that considerably will shape our society and will influence future transportation modes and quality of life, altering the face of mobility as we experience it by today. Many benefits are expected ranging from reduced accidents, optimized traffic, improved comfort, social inclusion, lower emissions, and better road utilization due to efficient integration of private and public transport. Autonomous driving is a highly complex sensing and control problem. State-of-the-art vehicles include many different compositions of sensors including radar, cameras, and lidar. Each sensor provides specific information about the environment at varying levels and has an inherent uncertainty and accuracy measure. Sensors are the key to the perception of the outside world in an autonomous driving system and whose cooperation performance directly determines the safety of such vehicles. The ability of one isolated sensor to provide accurate reliable data of its environment is extremely limited as the environment is usually not very well defined. Beyond the sensors needed for perception, the control system needs some basic measure of its position in space and its surrounding reality. Real-time capable sensor processing techniques used to integrate this information have to manage the propagation of their inaccuracies, fuse information to reduce the uncertainties and, ultimately, offer levels of confidence in the produced representations that can be then used for safe navigation decisions and actions.

Eros Pasero

Politecnico of Turin

Italy

Eros Pasero

Biography

Eros G. Pasero is Professor of Electronics at the Politecnico of Turin since 1991 after a four year appointment as Professor at the University of Roma, Electronics Engineering. He was also Visiting Professor at ICSI, UC Berkeley, CA in 1991, Professor of digital electronics and electronic systems at Tongji University, Shanghai, China in 2011, 2015 and 2017, and Professor of digital electronics and electronic systems at TTPU (Turin Tashkent Politechnic University), Tashkent, Uzbekistan since 2012 to 2014 where he was also vice rector in the first period of 2014.

Prof. Pasero established in 1990 the Neuronica Lab where hardware and software neurons and synapses are studied practical applications; innovative wired and wireless sensors are also developed for biomedical, environmental, and automotive applications. Data coming from sensors are post processed by means of artificial neural networks.

Prof. Pasero is now the President of SIREN, the Italian Society for Neural Networks; he was v. General Chairman of IJCNN2000 in Como, General Chairman of SIRWEC2006 in Turin, general Chairman of WIRN2015, WIRN2016 and WIRN2017, WIRN 2018 and WIRN 2019 in Vietri. He holds 6 international patents (two were the first silicon European neurons and synapse together Texas Instruments). He was supervisor of tenths of international Ph.D and hundredths of Master students and he is author of more than 100 international publications.

Together his group he was awarded with the 1982 CILEA-Sperry award for complex application systems and local distributed architecture”, with the ASSIPE Design-In-Award in 2003 and 2004, with premio "Innova S@alute2017" at the “forum dell'innovazione per la salute” on September 2017; he was IEEE key note speaker at 2014 Symposium series on Computational Intelligence in Orlando, Fl, USA; Distinguished Lecturer of the 2016 IEEE Medical Information Summer School, Distinguished Lecturer of the 2017 IEEE school "Smarter Engineering for Industry 4.0"

Affiliation(s)

Politecnico of Turin

Italy

September 30, 2021 at 10:00 am ET

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Medicine 4.0: When New Technologies Work with A.I.

About Dr. Pasero's Webinar

Industry 4.0 is considered the great revolution of the past few years. New technologies, the Internet of things, the possibility to monitor everything from everywhere changed both plants and the approaches to the industrial production. Medicine is considered a slowly changing discipline. The human body model is a difficult concept to develop. But we can identify some passages in which medicine can be compared to industry. Four major changes revolutionized medicine:

Medicine 1.0: James Watson and Francis Crick described the structure of DNA. This was the beginning of research in the field of molecular and cellular biology
Medicine 2.0: Sequencing the Human genome. This discovery made it possible to find the origin of the diseases.
Medicine 3.0: The convergence of biology and engineering. Now the biologist’s experience can be combined with the technology of the engineers. New approaches to new forms of analysis can be used.
Medicine 4.0: Digitalization of Medicine: IOT devices and techniques, AI to perform analyses, Machine Learning for diagnoses, Brain Computer Interface, Smart wearable sensors.

Medicine 4.0 is definitely a great revolution in the patient care. New horizons are possible today. Covid 19 has highlighted problems that have existed for a long time. Relocation of services, which means remote monitoring, remote diagnoses without direct contact between the doctor and the patient. Hospitals are freed from routine tests that could be performed by patients at home and reported by doctors on the internet. Potential dangerous conditions can be prevented. During the Covid emergency everybody can check his condition and ask for a medical visit (swab) only when really necessary. This is true telemedicine. This is not a whatsapp where an elder tries to chat with a doctor. This is a smart device able to measure objective vital parameters and send to a health care center. Of course Medicine 4.0 requires new technologies for smart sensors. These devices need to be very easy to use, fast, reliable and low cost. They must be accepted by both people and doctors.

In this talk we’ll see together the meaning of telemedicine and E-Health. E-health is the key to allowing people to self monitor their vital signals. Some devices already exist but a new approach will allow to everybody (especially older people with cognitive difficulties) to use these systems with a friendly approach. Telemedicine will be the new approach to the concept of hospital. A virtual hospital, without any physical contact but with an objective measurement of every parameter. A final remote discussion between the doctor and the patient is still required to feel comfortable. But the doctor will have all the vital signal recorded to allow him to make a diagnosis based on reliable data.

Another important aspect of medicine 4.0 is the possibility of using AI both to perform parameter measurement and to manage the monitoring of multiple patients. The new image processing based on Artificial Neural Networks allows doctors to have a better and faster analysis. But AI algorithms are also able to manage intensive care rooms with several patients reducing the number of doctors involved in the global monitoring of the situation.

Yang Liu

University of Iowa

United States

October 14, 2021 at 2:00 pm ET

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Optical Imaging, Computer Vision and Augmented Reality for Medical Applications

About Dr. Liu's Webinar

Optical Instrumentation, computer vision, and augmented reality are powerful platform technologies. In this lecture, we will discuss how these technologies can be used for medical applications. I will give an overview of the technologies and current challenges relevant to medical and surgical settings. The recent advances in image acquisition, computer vision, photonics, and instrumentation present scientific community with the opportunity to develop new systems to impact healthcare. Leveraging an integrated design, advantages of hardware and software approach can be combined, and shortcomings can be complemented. I will present new approaches of fluorescence imaging for surgical applications. We will discuss hardware instrumentation, algorithm development, and system deployment. New development of multimodal imaging and image registration will also be discussed. For example, combination of real-time intraoperative optical imaging and CT-based surgical navigation represent a promising approach for clinical decision support. Integration of 3D imaging and augmented reality provide surgeons with an intuitive way to visualize surgical data. In addition to technological development, I will discuss clinical translation of systems and cross-disciplinary collaboration. Interdisciplinary approaches to solve complex problems in surgically relevant settings will be described.