“Human-Centric Computing” by Prof. Jan Rabaey

The world as we know it is going through some major upheavals: climate change, pandemics and technology-induced societal changes are upsetting our world-picture with no real end in sight. Hence, an extremely relevant question is how ‘we humans’ are going to cope with this rapid evolution. One plausible answer is for us to use those same technologies to evolve ourselves, and to equip us with the necessary tools to interact with, survive, and prosper in spite of (or in light of) these changes.

Various wearable devices have been or are being developed to do just that. However, their potential to create a whole new set of human experiences is still largely unexplored. To be effective, functionality cannot be centralized and needs to be distributed to capture the right information at the right place. This requires a human intranet, a platform that allows multiple distributed input/output and information processing functions to coalesce and form a single application. In this presentation, we focus on the computational aspects of such an intranet, tasks that are complicated by the extreme energy and form-factor limitations imposed on the wearable (or implanted) devices. An important aspect is that the human intranet should not only be able to learn from experience, but capable of dealing with changes in both the environment and in itself. Moreover, it should be able to do so on a continuous base. Computational models, architectures and circuits that enable such capabilities at ultra-low energy and small form factor are hence needed. A glimpse of what may be possible will be presented.

Jan Rabaey is a Professor in the Graduate School in the EECS Department at the University of California at Berkeley, where he held of the Donald O. Pederson Distinguished Professorship for over 30 years before retiring. Before joining the faculty at UC Berkeley, he was a research manager at IMEC from 1985 until 1987. He is a founding director of the Berkeley Wireless Research Center (BWRC) and the Berkeley Ubiquitous SwarmLab, and has served as the Electrical Engineering Division Chair at Berkeley twice. In 2019, he also became the CTO of the System-Technology Co-Optimization (STCO) Division of IMEC, Belgium.

Prof. Rabaey has made high-impact contributions to a number of fields, including advanced wireless systems, low power integrated circuits, mobile devices, sensor networks, and ubiquitous computing. His current focus is of the interaction between the cyber and the biological world (amongst many other things.

He is the recipient of major awards, amongst which the IEEE Mac Van Valkenburg Award, the European Design Automation Association (EDAA) Lifetime Achievement award, the Semiconductor Industry Association (SIA) University Researcher Award, and the SRC Aristotle Award. He is an IEEE Fellow, a member of the Royal Flemish Academy of Sciences and Arts of Belgium, and has received a number of honorary doctorates. He has been involved in a broad variety of start-up ventures.

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“Sensor interfacing in the edge: small, sound, smart! ” by Prof. Gerald Gielen

The continuous progress of CMOS semiconductor technology fuels the technological revolution towards a smart world that immersivly impacts our daily life, work and play. The Internet of Things, personalized healthcare monitoring, autonomous driving, industry 4.0, etc. are but a few examples. Sensors and sensor interfaces with intelligence in the edge play a key role in all applications where the physical and the cyber worlds meet. This presentation will focus on core challenges in the design of future electronic circuits for such applications, where cost, power and reliability are major issues besides raw performance. The key to achieve solutions with small area (cost) and low power is to design the analog functions in a highly digital manner. Also ways to build intelligence in the edge will be discussed. This will be illustrated with some practical design examples.

Georges G.E. Gielen received the MSc and PhD degrees in EE from the KU Leuven, Belgium, in 1986 and 1990, respectively. He currently is Full Professor in the MICAS research division at the Department of Electrical Engineering (ESAT) at KU Leuven. From August 2013 till July 2017 he was also appointed at KU Leuven as Vice‐Rector for the Group of Sciences, Engineering and Technology, and he was also responsible for academic Human Resource Management.

He was visiting professor in UC Berkeley and Stanford University. Since 2020 he is Chair of the Department of EE.

His research interests are in the design of analog and mixed‐signal integrated circuits, and especially in analog and mixed‐signal CAD tools and design automation.

He is a frequently invited speaker/lecturer & coordinator/partner of several (industrial) research projects in this area, including several European projects. He has (co‐)authored 10 books and more than 600 papers in edited books, international journals and conference proceedings. He is a 1997 Laureate of the Belgian Royal Academy of Sciences, Literature and Arts in the discipline of Engineering. He is Fellow of the IEEE since 2002, and received the IEEE CAS Mac Van Valkenburg award in 2015 and the IEEE CAS Charles Desoer award in 2020. He is an elected member of the Academia Europaea.

Please sign up and join us on Tuesday, January 19, 2021 at 11:00 (Israel Standard Time).

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“Machine Learning and Optimization for Communications and Deep Networks”

In recent years, many remarkable achievements have been made in the field of machine learning. While most of the initial successes were related to image, speech and language recognition, a recent important development has been the application of these techniques to other areas. In particular, communications systems can benefit from applying these techniques. For example, algorithms such as Monte Carlo Markov Chain and Monte Carlo Tree Search have been successfully used in the design of MIMO (i.e., multiple antenna) transceivers. In addition, highly quantized implementations, such as binarized networks, have led to implementations that are well-suited to power-limited mobile platforms. In addition, metaheuristic optimization techniques such the genetic algorithm and others have been used to automatically find highly efficient deep learning architectures, eliminating the need for lengthy and tedious manual experimentation. This lecture will describe these approaches and present some recent design examples. Relationships between the algorithms will be emphasized, and important computational issues will be highlighted. Finally, opportunities for future research in these areas will be suggested.

Gerald Sobelman is a Professor in the Department of Electrical and Computer Engineering at the University of Minnesota, and he has served as the Director of Graduate Studies for the Graduate Program in Computer Engineering at the University of Minnesota. He received a B.S. degree in physics from the University of California, Los Angeles, and M.S. and Ph.D. degrees in physics from Harvard University. He has been a postdoctoral researcher at The Rockefeller University, and he has held senior engineering positions at Sperry Corporation and Control Data Corporation.

Prof. Sobelman is currently a Distinguished Lecturer of the IEEE Circuits and Systems Society. He has been a member of the technical program committees for several IEEE conferences. He was Chair of the Technical Committee on Circuits and Systems for Communications of the IEEE Circuits and Systems Society, and he has also served as an Associate Editor for IEEE Transactions on Circuits and Systems I and for IEEE Signal Processing Letters. In addition, he has chaired sessions at international conferences in the areas of communications and VLSI architectures.

Prof. Sobelman has presented short courses at a number of industrial and academic sites. He has authored or co-authored more than 150 technical papers and 1 book, and he holds 12 U.S. patents.

Please sign up and join us on Tuesday, January 5, 2021 at 15:00 (Israel Standard Time).

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“Reconfigure the World: Adaptive-Transfer-Function and Multi-Band RF Filtering Devices for Emerging Wireless Systems”

Next-generation multi-purpose wireless-communications (e.g., 5G) and multi-mode remote-sensing systems demand highly-versatile RF front-ends capable of supporting them. As a result, a lot of interest has recently been detected in the development of advanced high-frequency electronics featuring increased levels of spectral adaptivity and multi-band operation. In particular, a considerable attention is being dedicated to the design of fully-reconfigurable single/multi-band RF bandpass filtering devices as key blocks to perform the adaptive-signal-band-selection process required by these systems. On the other hand, the ever-growing saturation of the radio-spectrum resource has led to critical electromagnetic-coexistence scenarios between the plurality of co-located RF systems that exploit it. In this case, the availability of fully-controllable multi-notch RF filters to suppress spectrally- and power-agile interferers is very desirable. The purpose of this seminar is to present an overview of recent contributions in the research field of RF filtering devices with highly-reconfigurable and multi-band transfer function. This includes both multi-passband and multi-band stop components for multi-channel-selection and multi-interference-mitigation applications, respectively. Furthermore, their operational and design foundations, as well as a rich variety of experiment demonstrators in different bands and high-frequency technologies (e.g., planar, 3-D, lumped-element, acoustic-wave, and integrated ones), will be shown.

Roberto Gómez-García was born in Madrid, Spain, in 1977. He received the degree in telecommunication engineering and the Ph.D. degree in electrical and electronic engineering from the Polytechnic University of Madrid, Madrid. Since 2006, he has been an Associate Professor with the Department of Signal Theory and Communications, University of Alcalá, Alcalá de Henares, Madrid. He has been, for several research stays, with the C2S2 Department, XLIM Research Institute, University of Limoges, Limoges, France, the Telecommunications Institute, University of Aveiro, Aveiro, Portugal, the U.S. Naval Research Laboratory, Microwave Technology Branch, Washington, DC, USA, and Purdue University, West Lafayette, IN, USA. His current research interests include the design of fixed/tunable high-frequency filters and multiplexers in planar, hybrid, and monolithic microwave-integrated circuit technologies, multifunction circuits and systems, and software-defined radio and radar architectures for telecommunications, remote sensing, and biomedical applications, in which he has authored/co-authored around 100 journal papers (80 in IEEE journals and 35 as first author) and 140 conference articles.

Dr. Gómez-García was the recipient of the “2016 IEEE Microwave Theory and Techniques Society (MTT-S) Outstanding Young Engineer Award” and is an “IEEE Circuits and Systems Society Distinguished Lecturer” for 2020-2021 He was an Adjunct Part-Time Professor during 2017-2019 at the University of Electronic Science and Technology of China, Chengdu, China, and Invited Visiting Professor during 2018/2019 at Gdansk University of Technology, Gdansk, Poland. He was an Associate Editor of the IEEE Transactions on Microwave Theory and Techniques from 2012 to 2016 and the IEEE Transactions on Circuits and Systems-I: Regular Papers from 2012 to 2015, a Senior Editor of the IEEE Journal on Emerging and Selected Topics in Circuits and Systems from 2016 to 2017, and a Guest Editor of the 2013 and 2018 IEEE Journal on Emerging and Selected Topics in Circuits and Systems “Special Issue on Advanced Circuits and Systems for CR/SDR Applications” and “Special Issue on Wireless Sensing Circuits and Systems for Healthcare and Biomedical Applications”, the IET Microwaves, Antennas, and Propagation 2013 “Special Issue on Advanced Tunable/Reconfigurable and Multi-Function RF/Microwave Filtering Devices”, and the IEEE Microwave Magazine 2014 “Special Issue on Recent Trends on RF/Microwave Tunable Filter Design” and 2019 “Special Issue on Wireless Sensors for Bio-Medical Applications”. He is currently an Associate Editor of the IEEE Microwave and Wireless Components Letters, IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology, the IEEE Access, the IET Microwaves, Antennas, and Propagation, and the International Journal of Microwave and Wireless Technologies. He is also TCC-5 Topic Editor for the IEEE Journal of Microwaves, and a Reviewer for several IEEE, IET, EuMA, and Wiley journals. He serves as a member of the Technical Review Board for several IEEE and EuMA conferences. He is also a member of the IEEE MTT-S Filters (MTT-5), the IEEE MTT-S RF MEMS and Microwave Acoustics (MTT-6), the IEEE MTT-S Wireless Communications (MTT-23), the IEEE MTT-S Biological Effects and Medical Applications of RF and Microwave (MTT-28), and the IEEE CAS-S Analog Signal Processing Technical Committees.

Please sign up and join us on Tuesday, December 1, 2020 at 11:00 (Israel Day Time).

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“From Transistors to Swarm Systems: The Evolution of Design Methods and Tools in the last 40 Years”

Giovan Battista Vico, a philosopher and historian who lived across the XVII and XVIII centuries, was the first to note in his masterpiece “Scienza Nuova” (New Science) that the history of man and his endeavors follow a cyclical pattern. Economies, as well as the power of nations, have exhibited a clear and cyclical behavior. Electronic Design Automation (EDA) has not escaped this fundamental law. EDA started in the late 1960s when large companies such as IBM and Bell Laboratories were developing new products based on Integrated Circuit technology. The ICs of the time had only a few tens of transistors but the design costs were raising and the need to obtain circuit right the first time became clear. The scientific content of tools and methods for ICs ranged from physics to mathematics in a mix that is rare to see in any other engineering field.

EDA technology advances have oscillated between verification and synthesis, the perception in the mind of the electronic design community of EDA has been rising and falling in a regular pattern, EDA companies have risen and declined, the consideration of the financial community for EDA has been periodically increasing and decreasing, and the algorithms used in EDA have swung from general purpose techniques borrowed from mathematics, computer science, operation research, and artificial intelligence, to ad hoc techniques that leverage the nature of the specific design problem to be solved. Prof. Sangiovanni-Vincentelli will show that progress is achieved when new methodologies crystallize, with new tools and techniques acting as catalysts, that the construction of layers of abstraction are the steps that have helped us reach new heights.

His take in this talk is that the great success of Electronic Design Automation to enable the design of chips with more than 1 Billion transistors over a span of 40 years can be replicated in other sectors including traditional industries such as construction, and novel sectors such as synthetic biology, if its essential elements are distilled appropriately. He will show how they are approaching these extensions and what challenges they are facing.

Throughout the talk, Prof. Sangiovanni-Vincentelli will intersperse considerations about his scientific and industrial journey from a theory-oriented professor to an “entrepreneur”.

Alberto Sangiovanni-Vincentelli is the Edgar L. and Harold H. Buttner Chair of EECS, University of California, Berkeley, where he is Special advisor to the Dean of Engineering for Entrepreneurship and Chair of the Faculty Advisors to the Berkeley Accelerator, SkyDeck. Awards (among others): Kaufman for pioneering contributions to EDA; IEEE/RSE Maxwell Medal “for groundbreaking contributions that have had an exceptional impact on the development of electronics and electrical engineering or related fields” and the EDAA Lifetime Achievement Award. He co-founded Cadence and Synopsys, the two leading EDA companies and is Member of the Board of Directors of Cadence, KPIT, ISEO, ExpertSystem, QuantumMotions (Chairman), Phoelex (Chairman), Cy4Gate, Exein and Cogisen. He consulted for several companies including Intel, IBM, ST, Mercedes, BMW, UTC, Lendlease and GM. He is the Chairman of the International Advisory Council, Milano Innovation District. He is member of the US National Academy of Engineering. He is an IEEE and ACM Fellow. He was awarded an Honorary Doctorate from Aalborg University, from KTH (Sweden) and from IAG (Krakow, Poland). He published 1,120 papers and 19 books and graduated over 100 Doctorate Students.
Please sign up and join us on Tuesday, November 24, 2020 at 11:00 (Israel Day Time).
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“Flexible Interference Robust CMOS Radio Receivers”

The radio spectrum is becoming more and more crowded, and radio receivers are typically interference limited. As there is a demand for multi-mode flexible radio devices, traditional dedicated narrowband filtering no longer satisfies. During the last decade, several new radio receiver architectures and circuits have been proposed which offer more flexibility than traditional receivers with dedicated fixed filtering, while still achieving good sensitivity and robustness for interference. Different names have been used to refer to these receivers, e.g. reconfigurable receiver, multi-band receiver, wideband receiver, SAW-less receiver, software defined radio receiver or cognitive radio receiver. These receivers have in common that they all aim for a high dynamic range while relying less on fixed filters. This talk reviews several proposed concepts, e.g. linearization techniques, noise and distortion cancelling, Low Noise Transconductance Amplifiers followed by current-mode mixing, mixer-first receivers, frequency-translated N-path filtering, harmonic rejection and spatial interference rejection.

Eric Klumperink received his PhD from Twente University in Enschede, The Netherlands, in 1997 where he is currently an Associate Professor. He teaches Analog and RF CMOS IC Design and guides research projects focussing on Software Defined Radio and Beamforming. Eric served as Associate Editor for IEEE TCAS-I, TCAS-II and the IEEE Journal of Solid-State Circuits (JSSC), as TPC member of ISSCC (2011-2016) and the RFIC Symposium (2011-2020), and as SSC Distinguished Lecturer (2014/2015). He holds >10 patents, authored and co-authored >175 refereed journal and conference papers. He was recognized as top paper contributor to ISSCC, for >20 papers over 1954-2013, and was a co-recipient of the ISSCC 2002 and the ISSCC 2009 “Van Vessem Outstanding Paper Award”. Eric is an IEEE Fellow.

Please sign up and join us on Thursday, November 5, 2020 at 11:00 (Israel Daylight Time).

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“State-of-the-Art Automotive Radar System Architectures and What Else We Can Do with Them” webinar by Prof. Gardill

Automotive Radar operating in the 77 GHz and 79 GHz bands is the largest market for mmWave systems. Consequently, a de-facto standard system architecture has evolved which is used by most devices on the market and under current development. Modern automotive radars are to a large extent software defined and enable adaptive selection of waveform parameters as well as dynamic utilization of RF subsystems such as transmit and receive channels. This flexibility is the key-enabler for implementing multi-purpose radar sensors, which can realize functions from adaptive cruise control down to automated parking all in one device. Together with the high-volume of automotive radars also comes a rapid cost-reduction. Consequently, they become more and more attractive for solving various other sensing challenges: something else they have originally been designed for.

After reviewing the state-of-the art system architecture of automotive radar sensors, this presentation will introduce some novel ideas and applications how performance of that automotive “mass-product” can be further improved and how their flexibility allows for a widespread use, far beyond the traditional adaptive cruise control.

Markus Gardill is professor for Satellite Communication Systems at the chair of computer science VII – robotics and telematics at the university of Würzburg.
He received the Dipl.-Ing. and Dr.-Ing. degree in systems of information and multimedia technology/electrical engineering from the Friedrich-Alexander-University Erlangen-Nürnberg, Germany, in 2010 and 2015, respectively, where he was a research assistant, teaching fellow, and later head of the team for radio communication technology.
Between 2015 and 2020 he was R&D engineer and research cluster owner for optical and imaging metrology systems at Robert Bosch GmbH. Later he joined InnoSenT GmbH as head of the group radar signal processing & tracking, developing together with his team new generations of automotive radar sensors for advanced driver assistance systems and autonomous driving.
His main research interest include radar and communication systems, antenna (array) design, and signal processing algorithms.
His particular interest is space-time processing such as e.g. beamforming and direction-of-arrival estimation, together with cognitive and adaptive systems. He has a special focus on combining the domains of signal processing and microwave/electromagnetics to develop new approaches on antenna array implementation and array signal processing. His further research activities include distributed coherent/non-coherent networks for advanced detection and perception, machine-learning techniques for spatial signal processing, highly-flexible software defined radio/radar systems, and communication systems for NewSpace.
Markus Gardill is member of the IEEE Microwave Theory and Techniques Society (IEEE MTT-S).
He served as co-chair of the IEEE MTT-S Technical Committee Digital Signal Processing (MTT-9), regularly acts as reviewer and TPRC member for several journals and conferences, and currently serves as associate editor of the Transactions on Microwave Theory and Techniques. He is a Distinguished Microwave Lecturer (DML) for the DML term 2018-2020 with a presentation on signal processing and system aspects of automotive radar systems.

Please sign up and join us on Monday, October 19, 2020 at 11:00 (Israel Daylight Time).

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“Active Electronic Transceivers for THz Communication Systems” webinar by Prof. Ingmar Kallfass

The presentation focuses on the design of analog transmit and receive frontends for THz wireless communication systems. The high performance mm-Wave monolithic integrated circuits, implemented in GaAs metamorphic high electron mobility transistor technologies with cutoff frequencies beyond 1 THz, integrate quadrature up- and down conversion channels for either direct/zero-IF or heterodyne architectures, LO frequency generation stages along with power amplifiers and low-noise amplifiers operating at 240 and 300 GHz RF frequencies. On the system level, these transceiver components have enabled data transmission experiments with 64 Gbit/s bit rates over 850 m link distance and up to 100 Gbit/s over 15 m indoor distances, both, as pure electronic transmit and receive frontends, and in the prospective combination of photonic transmitters with electronic receivers.

Ingmar Kallfass received the Dipl.-Ing. degree in Electrical Engineering from University of Stuttgart in 2000, and the Dr.-Ing. degree from University of Ulm in 2005. In 2001, he worked as a visiting researcher at the National University of Ireland, Dublin. In 2002, he joined the department of Electron Devices and Circuits of University of Ulm as a teaching and research assistant. In 2005, he joined the Fraunhofer Institute for Applied Solid-State Physics. From 2009 to 2012, he was a professor at the Karlsruhe Institute of Technology. Since 2013, he holds the chair for Robust Power Semiconductor Systems at the University of Stuttgart, where his major fields of research are compound semiconductor based circuits and systems for power and microwave electronics.

Please sign up and join us on Wednesday, September 23, 2020 at 16:00 (Israel Day Time). A link to the Zoom session will be provided after registration.
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“Evolution of cellular RFICs (2G to 5G)” webinar by Dr. Venumadhav (Venu) Bhagavatula

Cellular technology has witnessed five generations of evolution – the mobile UE-era ushered in by 2G (GSM/EDGE), to the future smart-phones that will powered by the enhanced spectral efficiency of 5G. Each ‘G’ improved the user experience while introducing new hardware design challenges. I compare 2/3/4/5G system requirements, derive key TX/RX/LO circuit specifications, and highlight the differences in circuit topologies suited for these contrasting specifications. Using this framework, circuit techniques to handle a diverse range of problems such as low phase-noise oscillators, improved blocker tolerance, single-RB linearity will be introduced.

Venumadhav (Venu) Bhagavatula received the B.E. degree in electronics and communication from the University of Delhi, New Delhi, India, the M.Tech. degree in electronic design technology from the Indian Institute of Science, Bangalore, India, and the Ph.D. degree in electrical engineering from the University of Washington, Seattle, WA, USA, in 2005, 2007, and 2013. Since 2014 he has been with the Advanced Circuit Design group at Samsung Semiconductors Inc., San Jose, CA, USA. His research interests include RF/mm-wave and low-power mixed signal circuits. He currently serves as a technical program committee member for the ISSCC.

Please sign up and join us on Wednesday, September 9, 2020 at 16:00 (Israel Day Time). A link to the Zoom session will be provided after registration.

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“Mixed-Signal Computing for Deep Neural Network Inference” – webinar by Prof. Boris Murmann from Stanford University, USA

Modern deep neural networks (DNNs) require billions of multiply-accumulate operations per inference. Given that these computations require relatively low precision, it is feasible to consider analog arithmetic, which can be more efficient than digital in the low-SNR regime. However, the scale of DNNs favors circuits that leverage dense digital memory, leading to mixed-signal processing schemes for scalable solutions. This presentation will investigate the potential of mixed-signal approaches in the context of modern DNN processor architectures, which are typically limited by data movement and memory access. We will show that dense mixed-signal fabrics offer new degrees of freedom that can help alleviate these bottlenecks. In addition, we will derive asymptotic efficiency limits and highlight the challenges associated with data conversion interfaces (D/A and A/D) as well as programmability. Finally, these findings are extended to in-memory computing approaches (SRAM and RRAM-based) that are bound by similar constraints.

Boris Murmann is a Professor of Electrical Engineering at Stanford University. He joined Stanford in 2004 after completing his Ph.D. degree in electrical engineering at the University of California, Berkeley in 2003. From 1994 to 1997, he was with Neutron Microelectronics, Germany, where he developed low-power and smart-power ASICs in automotive CMOS technology. Since 2004, he has worked as a consultant with numerous Silicon Valley companies. Dr. Murmann’s research interests are in mixed-signal integrated circuit design, with special emphasis on sensor interfaces, data converters and custom circuits for embedded machine learning. In 2008, he was a co-recipient of the Best Student Paper Award at the VLSI Circuits Symposium and a recipient of the Best Invited Paper Award at the IEEE Custom Integrated Circuits Conference (CICC). He received the Agilent Early Career Professor Award in 2009 and the Friedrich Wilhelm Bessel Research Award in 2012. He has served as an Associate Editor of the IEEE Journal of Solid-State Circuits, an AdCom member and Distinguished Lecturer of the IEEE Solid-State Circuits Society, as well as the Data Converter Subcommittee Chair and the Technical Program Chair of the IEEE International Solid-State Circuits Conference (ISSCC). He is the founding faculty co-director of the Stanford SystemX Alliance and the faculty director of Stanford’s System Prototyping Facility (SPF). He is a Fellow of the IEEE.

Please sign up and join us on Monday, August 17, 2020 at 17:00 (Israel Day Time). A link to the Zoom session will be provided after registration.

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