- International Microwave & Antennas Symposium (IMAS 2024) October 21-24, 2024 I Marrakech, Morocco
Quantum Computing Workshop
Title: “Understanding Quantum Computing” (Part I and II)
Abstract:
Prof. Abbas Omar will present a two-part series on the shift from classical to quantum computing, driven by the limitations of traditional logic gates at molecular scales, as highlighted by Moore’s Law. The sessions will provide an introduction to quantum computing concepts and hardware, focusing on the implementation of qubits using superconducting circuits like Transmons. Key topics will include the fundamental principles of quantum mechanics that underlie quantum computing and the challenges posed by external influences on quantum systems, offering insights into how these factors impact the performance and reliability of quantum computers.
Title: “Superconducting RF Circuits for Potential Use in Quantum Computer Applications”
Abstract:
Prof. Raafat Mansour will provide an overview of superconducting qubits from a circuit perspective, exploring Josephson junctions and Superconductor Quantum Interference Devices (SQUIDs). The presentation will discuss the RF circuits used for qubit control and readout, highlighting the potential of Niobium-based superconducting RF circuits to replace conventional RF systems. Emphasis will be placed on the design and operational characteristics of these circuits, which have been developed to operate at cryogenic temperatures (4K) and are essential for the effective control of superconductor-based qubits in quantum computing applications.
Title: “Navigating the Design Challenges of Superconducting Quantum Systems”
Abstract:
Dr. Mohamed Hassan’s video presentation will explore the design challenges associated with superconducting quantum systems, focusing on the role of quantum amplifiers in enhancing signal fidelity and enabling sensitive readout operations. The talk will cover the complexity of integrating various system components, managing noise sources, and optimizing performance metrics within superconducting quantum circuits. Dr. Hassan will demonstrate how Quantum EDA techniques, specifically tailored for quantum circuits, can facilitate the design process by providing tools for simulation, verification, and optimization. These techniques are crucial for developing robust and scalable superconducting quantum systems, advancing the field of quantum computing and information processing.
This workshop addresses the transition from classical to quantum computing, driven by the limitations of traditional logic gates at molecular scales as predicted by Moore’s Law. Quantum computers, governed by the principles of Quantum Mechanics, offer solutions to computational problems beyond the reach of classical systems. The workshop will focus on key quantum computing concepts, including the role of qubits and their implementation using superconducting circuits such as Transmons, and the challenges posed by external influences on quantum systems.
Additionally, the workshop will cover the design and implementation of superconducting qubits, with an emphasis on Josephson junctions and Superconductor Quantum Interference Devices (SQUIDs). It will examine these qubits from a circuit perspective, discussing the RF circuits necessary for their control and readout, and explore the potential of Niobium-based superconducting RF circuits to replace conventional systems.
Further, the workshop will explore the design challenges of superconducting quantum systems, focusing on the role of quantum amplifiers in enhancing signal fidelity and the complexity of integrating various system components. The discussion will highlight how Quantum EDA techniques can facilitate the design, simulation, verification, and optimization of quantum circuits, paving the way for scalable and robust superconducting quantum systems.
Satellite and Space Communication Workshop
Title: “Role of Satellite and Space Networks in Emerging 5G/6G Communication Infrastructure”
Abstract:
Dr. Ramesh Gupta will discuss the integration of satellite networks into the emerging 5G/6G communication infrastructure. As 5G expands, creating opportunities for global connectivity, integrating cellular networks with satellite systems becomes crucial. This presentation will provide an overview of the evolution, technology, and system drivers of satellite networks using GEO, MEO, and LEO constellations, focusing on their role in addressing the increasing demand for high-speed data transfer and flexible on-demand connectivity.
Title: “Millimeter-Wave and Terahertz Sensors, Spectrometers, and Radars for Space Applications”
Abstract:
Dr. Goutam Chattopadhyay will present an overview of NASA’s developments in sensors, radiometers, spectrometers, and radars for space applications at millimeter-wave and terahertz frequencies. This talk will highlight compact, low-power instruments for planetary missions, including Mars and Europa. Recent advancements in differential absorption radars for Earth and Mars will be discussed, providing insights into the design and implementation of these innovative sensors
Title: “The Role of Advanced Microelectronics and Heterogeneous Integration for Aerospace Communications and Sensing Systems”
Abstract:
Dr. Tim Lee will explore the semiconductor industry’s response to the end of Moore’s Law scaling, including innovations in FinFETs, Gate-All-Around devices, and 2.5D/3D heterogeneous integration. This presentation will examine the impact of these technologies on aerospace communications and sensing systems, particularly the development of high-power density devices based on GaN for RF and millimeter-wave systems. Dr. Lee will also review key technology roadmaps and government initiatives promoting on-shoring of critical microelectronics technologies.
Title: “Space Surveillance in a Congested and Contested Domain”
Abstract:
Dr. Mohamed Abouzahra, along with co-authors J. Stambaugh, G. Hogan, and M. Schoenfeld, will address the challenges of space surveillance in an increasingly congested and contested domain. As the number of satellites in orbit grows exponentially, space domain awareness becomes essential for safeguarding space assets. This presentation will cover recent space threat developments, advancements in space surveillance sensors, and prototype technologies aimed at enhancing space domain awareness to protect satellite services and ensure operational safety in space.
This workshop explores critical advancements and challenges in space surveillance, semiconductor innovations, and the development of cutting-edge sensors and instruments for space applications. As space becomes increasingly congested and contested, the importance of effective space surveillance to safeguard operations is paramount. Additionally, the workshop delves into NASA’s efforts in creating millimeter-wave and terahertz sensors, spectrometers, and radars for Earth and planetary science, with a focus on compact, low-power instruments designed for future Mars missions. Moreover, the semiconductor industry’s response to the end of Moore’s Law scaling limits is examined, highlighting innovations such as FinFETs, Gate-All-Around (GAA) devices, and 2.5D/3D heterogeneous integration. These advancements aim to enhance performance, reduce power consumption, and manage costs, with particular emphasis on the development of high-power density devices for RF and millimeter-wave systems. The workshop also reviews key technology roadmaps and government initiatives aimed at driving the future of semiconductor technologies and supporting national economic and defense needs.
Biomedical Applications Workshop
Title: “Towards Higher Accuracy in Vital Sign Detection Using MIMO and Deep Learning”
Abstract:
Prof. Aly E. Fathy will discuss advancements in non-contact vital sign monitoring, highlighting technologies that enable remote monitoring of heart rate (HR) and respiratory rate (RR). The integration of Multiple-Input Multiple-Output (MIMO) systems, particularly using millimeter-wave technology, offers enhanced accuracy and reliability over traditional single-antenna systems. The presentation will cover a 77-GHz FMCW radar system with 192 MIMO channels for capturing subtle cardiac and respiratory signals, and the use of advanced signal processing techniques such as MIMO-MRC, novel wavelet methods, and Convolutional Neural Networks (CNN) for improved channel classification and detection accuracy.
Title: “Applications of Machine Learning to Physiological Radar”
Abstract:
Prof. Victor Lubecke will explore the use of Doppler radar technology for monitoring physiological states and activities, including non-invasive measurement of cardiopulmonary vital signs. The presentation will review how machine learning techniques, such as Convolutional Neural Networks and Support Vector Machines, are applied to enhance pattern recognition in physiological radar systems. Applications in healthcare, security, and automation, as well as emerging trends in machine learning for physiological radar, will be discussed.
Title: “Revolutionizing Geriatric Care: Wireless Sensors and Digital Twin Technologies for Ambient Health Monitoring”
Abstract:
Prof. George Shaker will discuss the development of non-invasive radio-based sensors powered by AI for monitoring health-related modalities, including vital signs, sleep apnea, respiratory diseases, gait, and glucose levels. The presentation will cover system development and validation campaigns for these sensors, with demonstrations in realistic environments such as hospitals and long-term care homes. Future developments in RF and mm-Wave radar technology aimed at enabling AI-powered health-monitoring cognitive platforms will also be explored.
Title: “Human-Centered Sensing Using mmWave Radars”
Abstract:
Dr. Rong Zheng will present on human-centric sensing using mmWave radars, focusing on indoor mapping, vital sign monitoring, and human pose estimation. The talk will highlight the advantages of mmWave radars, including privacy preservation and non-intrusiveness, and discuss the challenges of adopting these technologies in age-in-place applications. Key aspects of human activities, such as ‘what,’ ‘where,’ and ‘how well,’ will be analyzed through data captured by mmWave radars, offering insights into applications ranging from augmented reality to smart homes and smart manufacturing.
This workshop will focus on the latest advancements in non-invasive vital sign detection technologies’, with a particular emphasis on microwave and RF techniques. Participants will delve into the methodologies behind these technologies and their expanding applications in healthcare and medical diagnostics.
The workshop will begin with an introduction to the fundamental principles of microwave and RF vital sign detection, explaining how these technologies enable the monitoring of physiological parameters. Insights into the design and implementation of vital sign detection systems will be provided, covering both hardware and software components that are essential for accurate and reliable performance. A detailed examination of signal processing techniques will follow, highlighting methods used to accurately monitor and analyze vital signs in various scenarios.
Participants will also explore the practical applications of these technologies in healthcare settings, including their use in diagnostics and patient monitoring, which are critical for improving patient outcomes and operational efficiency in clinical environments. The integration of these detection systems with wearable and portable devices will be discussed, emphasizing how such integrations can enhance the usability and accessibility of vital sign monitoring in everyday life.
Finally, the workshop will look into emerging trends and future innovations in the field of vital sign detection. This section will highlight potential breakthroughs and new directions that could shape the future of healthcare technology, offering participants a glimpse into the next generation of non-invasive monitoring solutions
AI and GPR tools for landmine detection
Sultan Abughazal is an Associate Researcher at the Directed Energy Research Center at
the Technology Innovation Institute (TII), a cutting-edge UAE-based scientific research
center. He is responsible for developing Machine Learning (ML) models that can detect
patterns and perform detection and classification tasks on electromagnetic data.
He is combining his experience in GIS, ML, and Computer Vision to develop Machine
Learning methods for Ground Penetrating Radar (GPR) technology and enhance the
detection of buried objects.
Santiago is a Senior RF and Electronics Researcher at the Technology Innovation Institute
in Abu Dhabi, where he has worked for the last five years on several research projects
related to the generation, detection, reception, processing, and analysis of RF signals.
Some examples are TEMPEST video interface emanations analysis, GNSS vulnerability
identification, and, more recently, ground penetrating RADAR (GPR) applied to subsurface
target detection and classification
In November 1987, he joined the Department of Electrical and Computer Engineering, Royal Military College of Canada, Kingston, ON, Canada, where he has been a Professor since 1990. He has authored or coauthored over 200 journal articles, several books, and chapters in books, over 450 refereed conference papers, holds several patents, has chaired several national and international conferences, and has given plenary talks at many conferences. In 1977, he held a Government of Canada Visiting Fellowship at the Communications Research Center, Ottawa. In 2003, he was awarded the Royal Military College of Canada “Excellence in Research” Prize and the RMCC Class of 1965 Teaching Excellence Award in 2012. In October 2012, he received the Queen’s Diamond Jubilee Medal from the Governor-General of Canada in recognition of his contribution to Canada. He was a recipient of the 2014 IEEE Canada RA Fessenden Silver Medal for Ground Breaking Contributions to Electromagnetics and Communications and the 2015 IEEE Canada J. M. Ham Outstanding Engineering Education Award. In May 2015, he received the Royal Military College of Canada Cowan Prize for excellence in research. He was also a recipient of the IEEE-AP-S of the Chen-To-Tai Distinguished Educator Award in 2017. He has supervised and co-supervised over 90 Ph.D. and M.Sc. theses at the Royal Military College and Queen’s University, several of which have received the Governor General of Canada Gold Medal Award, the Outstanding Ph.D. Thesis of the Division of Applied Science, as well as many best paper awards in major international symposia. He served as the Chair for Canadian National Commission, URSI from 1999 to 2008, Commission B from 1993 to 1999, and has a cross-appointment at Queen’s University, Kingston. In May 2002, he was awarded the Tier 1 Canada Research Chair in electromagnetic engineering which has been renewed in 2016. He was elected by the URSI to the Board as the Vice President in August 2008 and 2014, and to the IEEE Antennas and Propagation AdCom. In 2019, he was elected as the 2020 President-Elect for IEEE AP-S, and will serve as its President in 2021. He has served as an associate editor for many IEEE and IET journals and an IEEE-APS Distinguished Lecturer. He was appointed as a member of the Canadian Defense Advisory Board of the Canadian Department of National Defense in January 2011. He is a Fellow of the Engineering Institute of Canada and the Electromagnetic Academy. He is also an International Union of Radio Science Fellow
This workshop will explore the integration of Artificial Intelligence (AI) and Ground-Penetrating Radar (GPR) technologies for enhancing landmine detection. The workshop is split into two sessions. The first one cover the theoretical foundations of GPR and machine learning, providing participants with a deep understanding of the principles and methodologies behind these technologies. The second one focus on hands-on machine learning, offering practical experience in applying AI tools to real-world GPR data.
The scope of this workshop is to train attendees with both the knowledge and skills necessary to tackle the complex challenges of landmine detection.
Outline
First Session: Theoretical GPR and ML Part (ET 90 minutes)
- GPR Basics (~20 minutes max)
- GPR applications and advantages
- General description of a GPR system and its components
- GPR Antenna configurations (Monostatic, Bistatic)
- GPR principle of operation (brief explanation of physical phenomena)
- Methods for UWB signal generation and RF design considerations
- GPR data (A-scans, B-scans, other forms of presenting the information)
- GPR Postprocessing (~20 minutes max)
- Main characteristics of GPR signals and challenges to retrieve information from them.
- Techniques for processing GPR signals: Background removal, Singular Value Decomposition
- GPR Hyperbolic signatures
- Final thoughts about GPR data labelling for ML models training
- Machine Learning paradigms (Supervised and Unsupervised) (~5 min).
- Machine Learning tasks (Classification, Segmentation, Anomaly Detection) (~5 min).
- GPR Data as Time Signals (~20 minutes)
- Classification and Anomaly Detection.
- Principal Component Analysis
- Support Vector Machines
- Neural Networks, Multi-layer Perceptron (MLP)
- Recurrent Neural Networks (Quick intro to RNN focusing on the intuition)
- Transformer architecture
- GPR Data as Images (~20 minutes)
- Classification, Segmentation and Anomaly Detection.
- Auto-encoder architectures
- ResNet architecture
- Transformer architecture
- Model explainability analysis
Second Session: Hands-on ML Part (ET 90 minutes)
- Setting up the exercise on Google Colab. The exercise is to use Python to apply what was explained in the workshop. The note provided will be almost complete and the exercise will mostly be us going through the code with the audience
- Introducing the exercise dataset and familiarizing the audience with it
- Running the exercise in the same sequence that was given in the ML part of the first session:
- Introducing PyTorch, SciPy, matplotlib, and transformers packages (compare PyTorch to TensorFlow?).
- Running PCA and SVM demonstrations.
- Building a data loader in PyTorch (using an existing data loader versus building your own).
- Building a model in PyTorch (using an existing model versus building your own).
- Building an MLP in PyTorch.
- The PyTorch training loop (introduce the ML boilerplate).
- Demonstration of auto-encoders.
- Demonstration of ResNet architecture.
- Demonstration of Transformer architecture.
- Model Explainability.