Elodie Viau
Biography & Abstract
Issa Batarseh
Vincenzo Piuri
Leslie Ying
Ghaleb Abdulla
Abdallah A. Chehade
Areen Alsaid
Dario De Santis
John shen
Nasser Kutkut
Antonio Luque
Elodie Viau is the ESA Director of Telecommunications and Integrated Applications. Elodie Viau was born in Angers, France. She gained her MSc degree in telecommunications from Télécom SudParis in 2007, an MSc in Space Studies and Management from the International Space University in 2008 and an MBA from the Open University in the UK in 2018.
For the past 12 years, Elodie Viau has worked for SES, one of the world’s leading satellite owners and operators, based in Betzdorf, Luxembourg. She began her career with SES on a two-year Leadership Development Programme, working in a variety of roles on four missions within SES subsidiaries in Luxembourg, the Netherlands and USA.
In 2010, Elodie moved to SES Technology, Space Systems and Operations, in Toulouse, France, as a Satellite Programmes Senior Engineer. Here she served as Deputy Programme Manager for six satellites (ASTRA 1N, 2F, 2E, 2G, 5B and SES-6) built by Airbus Space. Between 2014 and 2018, Elodie was the Programme Manager for the SES-10, SES-12 and SES-14 satellites built by Airbus Space.
In 2018, Elodie moved back to Luxembourg to become Senior Manager and then Director of SES New Space Segment Development and, until recently, she was Vice-President for SES Technology Programme Management.
In this keynote speech, Elodie Viau will explore how her Telecommunications and Integrated Applications Directorate at the European Space Agency (ESA) is boosting development of satellite communication systems for space and non-space sectors to improve connectivity on Earth, and even on the Moon. The speech will cover innovative ESA programs including space for 5G and 6G, safety and security, as well as lunar, optical and quantum communications.
Issa Batarseh is currently a Professor of electrical engineering in the Department of Electrical and Computer Engineering at UCF and serving as the director of the Florida Power Electronics Center. His research interests focus on power electronics and high-frequency, smart grid-tied PV energy conversion systems. His research team has been leading the design, development, and commercialization of smart microinverters and EV chargers. He has co-founded three start-up companies. He is a Fellow of the IEEE and AAAS, member of the National Academy of Inventors (NAI) and has been inducted into the Florida Inventors Hall of Fame. Dr. Batarseh is a Registered Professional Engineer in the State of Florida.
In this talk, Dr. Batarseh will discuss the emerging disruptive technologies in solar and energy storage. He will present his research team’s efforts in solar energy conversion and power electronics integration in future energy storage systems. The talk will introduce new high efficiency multi-port inverter design with advanced GaN devices. He will discuss emerging PV+storage system integration technology to enable more resilient and interactive power grid. The talk will give an overview of current research activities of the Florida Power Electronics research group at the University of Central Florida.
Vincenzo Piuri has received his Ph.D. in computer engineering at Polytechnic of Milan, Italy (1989). He is Full Professor in computer engineering at the University of Milan, Italy (since 2000). He has been Associate Professor at Polytechnic of Milan, Italy and Visiting Professor at the University of Texas at Austin, USA, and visiting researcher 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, cloud computing infrastructures, and internet-of-things. Original results have been published in 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 IEEE Region 8 Director-elect (2021-22), 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 has been Editor-in-Chief of the IEEE Systems Journal (2013-19). He is 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; Amity University, India; and Galgotias University, India.
Recent years have seen a growing interest among users in the migration of their applications to the Cloud/Fog/Edge computing and Internet-of-Things environments. However, due to high complexity, Cloud/Fog/Edge-based and Internet-of-Things infrastructures need advanced components for supporting applications and advanced management techniques for increasing the efficiency.
Adaptivity and autonomous learning abilities become extremely useful to support configuration and dynamic adaptation of these infrastructures to the changing needs of the users as well as to create adaptable applications. This self-adaptation ability is increasingly essential especially for non-expert managers as well as for application designers and developers with limited competences in tools for achieving this ability.
Artificial intelligence is a set of techniques which greatly can improve both the creation of applications and the management of these infrastructures.
This talk will discuss the use of artificial intelligence in supporting the creation of applications in cloud/fog/edge and IoT infrastructures as well as their use in the various aspects of infrastructure management.
Dr. Leslie Ying is the Furnas Chair Professor of Biomedical Engineering and Electrical Engineering at the University at Buffalo, the State University of New York. She received her B.E. in Electronics Engineering from Tsinghua University, China in 1997 and both her M.S. and Ph.D. in Electrical Engineering from the University of Illinois at Urbana – Champaign in 1999 and 2003, respectively. Prior to joining University at Buffalo in 2012, she was a faculty of Electrical Engineering and Computer Science at the University of Wisconsin – Milwaukee. Her research interests include magnetic resonance imaging, compressed sensing, image reconstruction, and machine learning. She has contributed to the advancement of various biological and medical imaging modalities using computational methods. Dr. Ying received a CAREER award from the National Science Foundation in 2009. She was elected as an Administrative Committee member of IEEE Engineering in Medicine and Biology Society in 2013-2015. She was an Associate Editor of IEEE Transactions on Biomedical Engineering, a Deputy Editor of Magnetic Resonance in Medicine, and an editorial board member of Scientific Reports. She has been the Editor-in-Chief of IEEE Transactions on Medical Imaging since 2019. She is a Fellow of AIMBE.
Machine learning has recently attracted a lot of attention in biomedical imaging. It has shown success in biomedical image classifications but has only very recently been used for image reconstruction with unique features. In this talk, I will start with compressed sensing (CS), a strategy for reconstruction from sub-Nyquist sampled data. Several machine-learning-based methods will be introduced within the conventional CS framework. I will then explain how the optimization algorithm underlying CS can be unrolled to a deep artificial neural network, such that parameters and prior models can be learned from training samples. Finally, end-to-end convolutional neural networks will be presented based on the training data with little knowledge of the imaging system. Connections among different networks will be discussed with their benefits and limitations highlighted. Although most examples provided will be from MRI, the frameworks are generalizable to image reconstruction problems for most imaging modalities. The talk will be concluded with future outlooks.
Ghaleb Abdulla is a senior Member of Technical Staff at Lawrence Livermore National Laboratory (LLNL), a Department of Energy research laboratory. Since joining LLNL in 2000, Dr. Abdulla embraced projects that depend on teamwork and data sharing. His tenure includes establishing partnerships with universities seeking LLNL’s expertise in HPC and large-scale data analysis. He supported approximate queries over large-scale simulation data sets for the AQSim project and helped design a multi-petabyte database for the Large Synoptic Survey Telescope. Dr. Abdulla used machine learning (ML) to inspect and predict optics damage at the National Ignition Facility and leveraged data management and analytics to enhance HPC energy efficiency. He served as the lead for the Operational Data Analytics team under the Energy Efficient HPC Working Group. He also led the Cancer Registry of Norway project developing personalized prevention and treatment strategies through pattern recognition, ML, and time-series statistical analysis of cervical cancer screening data and was awarded the DOE Secretary’s Appreciation Award for his work to help with the Cancer moonshot presidential initiative. Dr. Abdulla served as the PI of the Earth System Grid Federation (ESGF) —an international collaboration that manages a global climate database for more
than 25,000 users on six continents. He chaired the ESGF international Executive committee and served as member of the Working Group on Coupled Modelling (WGCM) Infrastructure Panel (WIP) that operates under the World Climate Research Program (WCRP).
He also served as the director for the Institute for Scientific Computing Research (ISCR) at LLNL. He established a data science internship program and helped several universities create data science curriculum targeted to graduate students who can help with scientific data analytics.
In 2020 Dr. Abdulla was chosen as one of the 50 for 50 spotlights which highlights the most influential graduates from Virginia Tech computer science department.
Currently he serves as Deputy program manager for WCI data infrastructure and leads the data infrastructure and analytics team.
Managing and analyzing scientific and simulation data is a challenge due to growing data sizes and the need to subset and fuse different variables from different data sets before running an evaluation metric. Computer and climate scientists are collaborating to enable large-scale data analytics and while there are success stories, the new high-resolution models require more distributed computing resources to build complex data analysis and machine learning workflows. The high-resolution data produced by climate models is distributed in nature and the scientists working on analyzing the data are located in different locations around the globe, yet they need to collaborate and work on the data. A federated data management system will enable data sharing and collaboration, however, the machinery and tools to enable large scale and distributed scientific data analysis are still lacking. The traditional workflow involves querying a data archive using the indexed metadata. Once the files are located, the scientist needs to download the data into a local machine and perform the analysis. Instead, we developed tools to support a distributed system for data analytics and Machine Learning, i.e. server-side or edge computing.
In this talk, I will describe the Earth System Grid Federation (ESGF) software stack, architecture, hosted data, and discuss use cases. I will also describe the ESGF Compute Node (ECN) which allows scientists to build and run data analytics algorithms. The current architecture allows users to log into the Jupyter hub on our server using a GitHub account. Using the Jupyter hub, the user has a choice to either spawn a Unix shell with the ability to access all the regular tools such as python and the climate analysis libraries or spawn a Jupyter notebook with the ability to use ESGF user interface to search for relevant data sets, use basic sub-setting, re-grinding and data reduction constructs to minimize data movement.
Abdallah A. Chehade received the B.S. degree in mechanical engineering from the American University of Beirut, Beirut, Lebanon, in 2011 and the M.S. degree in mechanical engineering, the M.S. degree in industrial engineering, and the Ph.D. in industrial engineering from the University of Wisconsin-Madison in 2014, 2014, and 2017, respectively. Currently, he is an assistant professor in the Department of Industrial and Manufacturing Systems Engineering at the University of Michigan-Dearborn. His research interests are safety of AI, reliability, deep learning, data fusion for process modeling and optimization of data-analysis. Dr. Chehade is a member of INFORMS, IEEE, and IISE.
Internet of Things (IoT) technologies are now becoming available in various complex and connected systems including vehicles. While IoT technologies result in high-dimensional data environments that provide an unprecedented opportunity for smart condition monitoring and predictive analytics of complex systems; they also pose critical challenges. Data for each complex system are collected from multiple streams that are often correlated and each data stream contains only partial information about the degradation process of the system. Second, data from one complex system may not be sufficient to extrapolate its degradation profile and it is critical to transfer knowledge between different connected systems. In this talk, we present a set of statistical and deep learning techniques for smart and connected systems to address challenges related to warranty data analytics, remaining useful life estimation, and safety of artificial intelligence systems.
Areen Alsaid is a research scientist at Ford Motor Company. Prior to joining Ford, Areen completed her Ph.D. in Industrial and Systems Engineering from the University of Wisconsin-Madison in 2020, and MS in Industrial Engineering and Management Systems from the University of Central Florida in 2016. Her research interests lie in estimating the user state and developing effective mitigation strategies to smooth the interaction between humans and technology. Her present focus is on estimating users’ emotional state through physical manifestations and contextual information, to develop adaptive personalized vehicle automation. Areen’s work has been published in several high impact journals including Human Factors and Expert Systems.
Technological change is accelerating today at an unprecedented rate. Technologies are transforming societies by offering unapparelled advantages. One example is self-driving vehicles. Self-driving vehicles promise safer roads, improved mobility, and environmental benefits. The same is true for other technologies, however, users’ lack of trust and acceptance may threaten their success and potential.
In this talk, I will discuss why now, it is more important than ever to consider the human at different product development stages. With examples from the automotive and robotic industries, I will discuss how technologies can fail because of failure to consider the human needs. I will also talk about the future of human-computer interaction, and how to anticipate the changing needs of the user in this ever-changing fast-paced world to achieve efficient, effective, safe, and pleasant interactions.
As the Principal of Product Management for Cisco Webex Strategic Integrations, Dario is currently leading a cross-functional team focused on enabling Hybrid Work through the integration of the Webex Platform with leading third-party Cloud tools.
Prior to his current role, as part of the Workplace Transformation initiative, Dario led a product team in San Jose CA, focused on fostering emerging workflows through intelligent Webex wearable devices.
Since he joined Cisco in 2016, he led several product initiatives aiming at redefining desk and meeting room experiences through AI, combined with innovative devices.
Previously, Dario worked at Covisint (now part of OpenText) as the Product Manager of their IoT Cloud platform from scratch to market and led both Product and Engineering teams at noHold (2015 Gartner Cool Vendor), a pioneer in offering NLP-based Virtual Assistants for Customer Service.
He has a BS and MS in Computer Science and Management, along with an MBA from SDA Bocconi School of Management where he specialized in strategy and innovation.
As we begin to emerge from the global pandemic, one thing is for certain: the future of work will be forever changed.
In the last couple of years, we clearly saw which companies thrived and which ones struggled to pivot to a remote reality. Companies that had already invested in cloud technology and collaboration tools didn’t miss a beat. Those who did not have to figure out what they needed and implement those tools in real-time which, in some cases, meant pausing certain parts of the organization. We recognize that every organization in every industry is facing both extraordinary challenges and exciting opportunities as a result of the pandemic.
In this keynote speech, we will examine the relevant trends and driving forces of the new Hybrid Work era, identifying the impact that Communication and Collaboration technologies have in enabling productivity “everywhere”, as well as being a source of competitive advantage.
Dr. John Shen is Grainger Chair Professor of Electrical and Power Engineering at Illinois Institute of Technology, Chicago, USA. He has more than 30 years of industrial, academic, and entrepreneurial experience in power electronics and power semiconductor devices with over 300 publications and 18 issued U.S. patents in these areas. He has been involved in circuit breaker research since 2013, and is an inventor of several patents and an author of 25 publications on the subject. He serves as PI of an ARPA-E CIRCUITS project on low-voltage solid-state circuit breakers and co-PI on an ARPA-E BREAKERS project on MVDC hybrid circuit breakers. He is a recipient of the 2012 IEEE Region 3 Outstanding Engineer Award, the 2012 E. T. Walton Fellowship from Science Foundation of Ireland, and the 2020 Illinois Institute of Technology Senior Faculty Sigma Xi Research Award. He has served the IEEE Power Electronics Society (PELS) in various capacities including Vice President of Products, AdCom member, Chair of Distinguished Lecturers Program, Deputy Editor-in-Chief of IEEE Power Electronics Magazine, Guest Editor-in-Chief of the IEEE Transaction on Power Electronics and the IEEE Journal of Emerging and Selected Topics in Power Electronics. He has been on the organizing or technical program committee of over 30 international conferences in the field, and served as the General Chair of the 2016 Energy Conversion Congress and Exposition (ECCE2016) and the 2018 International Symposium on Power Semiconductor Devices & IC’s (ISPSD2018). He is a Fellow of IEEE and the U.S. National Academy of Inventors.
DC power is coming back, long after having lost the War of Currents more than 100 years ago. DC offers higher efficiency, better stability, and easier accommodation of renewable generation and energy storage than the conventional AC power, and finds applications in LVDC (<1kV), MVDC (<40kV), and HVDC (100’s kV) power systems. However, one major barrier for adopting DC power is the lack of effective DC circuit protection technologies. A wide range of DCCB technologies have been investigated for different applications. Presently, solid-state circuit breakers (SSCBs) can quickly interrupt a DC fault current within tens of microseconds but suffer from high conduction losses and weight and cost penalties associated with the cooling and semiconductor components, especially for high power applications. The most distinct advantage of semiconductor switches is their capability of switching current during fault interruption while the most distinct disadvantage is their nonnegligible on-resistance when conducting current. Unfortunately, they are used in SSCBs in the worst way possible—continuously dissipating power except during infrequent fault interruption. Numerous hybrid circuit breaker (HCB) schemes have been proposed to offer an on-state resistance 2-3 orders of magnitude lower than that of SSCBs. All the HCBs are of parallel type, in which an electronic path is in parallel with a main mechanical switch. The fault current in the mechanical switch is initially commutated to the electronic path to create artificial current zero crossings in various forms to aid the opening of the mechanical switch. The electronic path will then be interrupted with varistors (MOV) clamping the transient voltage surge and absorbing the residual electromagnetic energy. However, these HCB solutions offer only a moderate fault response time of several milliseconds. This may be too slow to limit the fast-rising fault current in low-impedance DC power networks. The most distinct disadvantage of all the HCBs is the relatively long opening time of the mechanical switch to achieve a sufficiently wide gap for sustaining the DC voltage, during which the fault current continues to rise through the electronic path. This talk will provide a review and performance comparison on the state of the art DCCB solutions in a systematic way. It will also highlight the fundamental challenges faced by the DCCB technologies and shed some light on future research directions.
Nasser Kutkut received the B.Sc. degree in electrical engineering from the Jordan University of Science and Technology, Jordan, in 1989, the M.Sc. degree in electrical engineering from the University of Illinois, Chicago, in 1990, the Ph.D. degree in electrical engineering and the M.B.A. degree in management and entrepreneurship, both from the University of Wisconsin, Madison, WI, in 1995 and 2001, respectively, and the Doctorate in Business Administration in entrepreneurship and marketing from Grenoble Ecole de Management, Grenoble, France, in 2013. Between 1995 and 1998, he was a Senior Scientist with Soft Switching Technologies, Middleton, WI, USA, where he was involved in the design and development of power electronic converters and systems. Between 1998 and 2008, he was the founder and CEO of Power Designers, LLC, in Madison, WI, USA, where he successfully developed and commercialized a line of advanced high frequency and high efficiency fast and opportunity chargers and battery monitors for the industrial motive power battery market. Between 2008 and 2015, he was with the University of Central Florida where he was a Lecturer at the Department of Management, College of Business. Between 2015 and 2019, he was partner and CTO of Advanced Charging Technologies in Orlando, FL, where he led the development of the industry’s first line of industrial IoT battery chargers and battery monitors. Since 2017, he has been the founder and CEO of Smart Charging Technologies LLC in Orlando, FL, a high-tech firm specializing in innovative IoT energy management solutions and energy management services.
Dr. Kutkut is a serial entrepreneur and has more than 25 years of technology leadership and management experience developing and commercializing innovative battery management technologies for motive and stationary power battery markets. He has a wide array of business expertise in the areas business start-ups, sales and marketing strategy development, technology and product development, as well as extensive technical expertise in the areas of renewable energy power systems, battery charging and monitoring technologies for motive power applications. He is a holder of 23 issued U.S. and international patents and has published more than 80 papers in leading technical and trade journals.
The Industrial Internet of Things (IIoT), often referred to as Industry 4.0, refers to the fourth industrial revolution of connected products, machines, services and humans through the cloud. The emerging 5G network is rapidly improving the performance of connected devices and is further driving rapid growth of IIoT applications. This rapid growth of IIoT applications is increasing the need for smarter and more flexible power conversion systems (AC/DC, DC/DC, and DC/AC). Traditional power converters designed and optimized for static applications with preset load conditions can no longer serve the needs of ever changing IIoT needs.
The design of power conversion systems for IIoT applications requires a radical change in design thinking to meet the growing and everchanging needs of IIoT load demands. A combination of cloud intelligence, continuous monitoring, and remote command and control will allow for data logging and aggregation exposing historical faults and transient events and allowing for real time parameters’ adjustments to maximize production capacity and efficiency on-the-fly.
To achieve that, various design considerations need to be considered including design modularity, redundancy, and flexibility, digital controls with wireless communication, over the air (OTA) firmware updates to continuously improve operation and controls, fault monitoring and diagnostics, as well as cloud integration for real time remote monitoring and parameter adjustments.
Antonio Luque currently holds the position of Associate Professor in the Department of Electronics Engineering, University of Seville. He has authored 20 journal papers, 40 conference papers, 3 book chapters, and a textbook, in addition to supervising two Ph.D. students. He has been invited researcher and teacher at the Swiss Federal Institute of Technology Lausanne (Switzerland), Auburn University (AL, USA), Delft University of Technology (Netherlands), Jade University (Germany), Harbin Institute of Technology (China), and Tech Institute of Monterrey (Mexico). In IEEE he is currently serving, among other positions, as 2021-2022 Director of Region 8 (Europe, Middle East, and Africa).
The market for electronics devices and circuits applied to medical and biomedical fields is expected to continue growing during the next decade at least. This talk will explore some if the ways that electronic devices, and in particular MEMS, can be applied. It will showcase a particular device, called a lab-on-a-chip whose final aim is to replace a complete lab for drug synthesis or substance analysis in a single chip. An application of a lab-on- chip for radiopharmaceuticals synthesis will be presented in detail, and opportunities for international collaboration highlighted.
A/Professor Farhad Shahnia received his Ph.D. in Electrical Engineering from Queensland University of Technology (QUT), Brisbane, in 2012. He is currently an A/Professor at Murdoch University. Before that, he was a Lecturer at Curtin University (2012-15), a research scholar at QUT (2008-11), and an R&D engineer at the Eastern Azarbayjan Electric Power Distribution Company, Iran (2005-08). He is currently a Fellow member of Engineers Australia, Senior Member of IEEE, and member of the Australasian Association for Engineering Education.
Farhad’s research falls under Distribution networks, Microgrid, and Smart grid concepts. He has authored one book and 11 book chapters and 100+ peer-reviewed scholarly articles in international conferences and journals, as well as being an editor of 6 books. Farhad has won 5 Best Paper Awards in various conferences and has also received the IET Premium Award for the Best Paper published in the IET Generation, Transmission & Distribution journal in 2015.
One of his articles was listed under the top-25 most cited articles in the Electric Power System Research Journal in 2015 while one of his 2015 journal articles has been listed under the top-5 most-read articles of the Australian Journal of Electrical and Electronics Engineering. He was the recipient of the Postgraduate Research Supervisor Award from Curtin University in 2015 and the Australia-China Young Scientist Exchange Award from the Australian Academy of Technology and Engineering in 2016.
Farhad is currently a Subject Editor, Deputy Subject Editor, and Associate Editor of several journals including IEEE Access, IET Generation, Transmission & Distribution, IET Renewable Power Generation, IET Smart Grid, IET Energy Conversion and Economics, and International Transaction on Electrical Energy Systems and has served 35+ conferences in various roles such as General, Technical, Publication, Publicity, Award, Sponsorship, and Special Session Chairs.
Farhad is currently the Chair of the IEEE Western Australia Section and a member of IEEE’s Industrial Electronics Society (IES)’s Technical Committees of Smart Grid and Energy Storage.
Electricity systems around the world are experiencing a radical transition as the consequence of replacing fossil fuels, used for electricity production, with sustainable and cleaner energies. The growing penetration of renewable energies requires smarter techniques capable of handling the uncertainties of these intermittent sources. Along with this change, traditionally centralized power systems are also converting into distributed self-sufficient systems, often referred to as microgrids, that can operate independently. This talk will focus on remote area microgrids as a hot research topic in Australia and Southeast Asia that have hundreds of remote and off-grid towns and communities, and islands. It is expected that remote area microgrids will strongly benefit these remote locations in the forthcoming years. This talk will briefly introduce the progress of research in this field around the world and Australia, and will also discuss some of the technical challenges associated with the interconnection of neighboring microgrids as a key step to improve their survivability in the course of unexpected imbalances between the demand and the available generation from intermittent renewable resources.