Special Talks by Invited Speakers and Panel Discussions to Highlight Future of Cybersecurity ��

Khalifa University hosted top research scientists that presented flagship activities and discussed current challenges of interest for the UAE and the international community in incorporating advanced machine learning techniques into the next generation of intelligent systems and mobile networks at the third Center for Cyber-Physical Systems (C2PS) Symposium.��

The symposium titled “Next Generation Secure Networks and Systems” was held at Khalifa University Main Campus on 20 June 2022. Experts, from industry and academia, discussed how to provide advanced distributed services at unprecedented scale, with low latency and high throughput, while guaranteeing data protection, robustness in the face of attacks, and resilience to recover from failures.��

Prof. Dr. Ernesto Damiani, Director, C2PS, said: “We are delighted to organize this symposium to highlight the need to adopt and standardize advanced solutions to ensure cybersecurity for the next generation of intelligent systems and mobile networks. We believe presentations by visiting experts will benefit UAE industry stakeholders and those involved in research of relevant systems.”��

The Keynote speech on “Edge Intelligence over Wireless: Present and Future” was delivered by Dr. Mehdi Bennis, Head of the Intelligent Connectivity and Networks/Systems Group (ICON) Faculty of Information Technology and Electrical Engineering, Center for Wireless Communications, University of Oulu, Finland. The day’s events included invited talks by top speakers including Dr. Merouane Debbah, Chief Researcher, AI Cross-Center Unit and Digital Science Research Center at the Technology Innovation Institute (TII), Dr. Ticky Thakkar, Chief Researcher, Secure Systems Research Center (TII), and Dr. Antonio Lioy, Professor of Computer Security at Politecnico di Torino, as well as technical presentations by C2PS researchers. A panel discussion on “Securing Intelligent Cyber-Physical Systems” was moderated by Dr. Damiani.

Other speakers from C2PS included researchers and faculty members from Khalifa University, Dr. Chan Yeun, Dr. Naoufel Werghi, Dr. Rabeb Mizouni, Dr. Hadi Otrok, and Dr. Paschalis C. Sofotasios, and Dr. Hanane Lamaazi.

C2PS is part of the overall research line under the Robotics and Intelligent Systems Institute. C2PS research covers key areas like edge-cloud computation and blockchain, mobile network and 5G, data analytics and applied artificial intelligence, as well as cybersecurity and privacy.

Clarence Michael
English Editor Specialist
20 June 2022

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The WomenTech Global Awards is the biggest event that gathers women working in tech. This year, 1,712 candidates from 151 countries competed in 16 categories.��

Postdoctoral Fellow Dr. Hanane Lamaazi of Khalifa University’s Center for Cyber-Physical Systems (C2PS) was one of the amazing women recognized at the WomenTech Global Awards 2021. The event was organized by the WomenTech Network, the world’s largest community for women in tech with more than 5,700 ambassadors worldwide.��

Dr. Lamaazi received the Gold Award in the category WomenTech Community Award (Public Vote) where she was voted #3 in the “Global Top 10 Community Award”, #3 in “Global Top 5 Unique Profile Engagement”, and top 2 in “Global Top 5 LinkedIn Engagement”. This award is in recognition of her outstanding contribution and engagement with the WomenTech Community. It also acknowledges her work and role as a valued scientific researcher in the field of Internet of Things (IoT) and emerging technologies such as artificial intelligence (AI), crowdsensing, and edge computing.��

The WomenTech Global Awards is held every year following the Women in Technology Conference, the flagship event of the WomenTech Network. The conference is considered the world’s largest for women in technology and the awards highlight and celebrate the contributions of women, minorities, and their allies working in the tech industry.����

Anna Radulovski, WomenTech Network CEO & Founder, said, “After the WomenTech Global Conference 2021, we received tons of positive feedback, many sharing about their hardships with uncertainty, job security, and work-life balance while working remotely and how the community inspired them to overcome them. We understand the value of recognizing small and major victories while simultaneously adjusting to a digital-first environment. This is why we wish to shine a light on accomplished and aspiring female tech leaders, as well as allies, who are working toward a more equitable and inclusive world.”��

Dr. Lamaazi is a distinguished and prolific researcher who has received international attention from the scientific community. She has on her credit more than 20 research articles in international journals and refereed conference proceedings. Her work has more than 400 citations on Google Scholar and more than 300 citations on Scopus, with an H-index of 10. Dr. Lamaazi has worked and co-authored papers with highly reputed scientists in the field of computer science and computer networks.�� She provides exceptional support to new researchers for both Master’s and PhD students by offering her expertise in research and academic writing skills. She is also a reviewer for some of the top scientific journals namely, Ad Hoc, IEEE Sensors, IEEE Access, ComCom, ComNet, and IJCS.��

Her most recent article, published in the Future Generation Computer Systems journal, stems from a project she led at t KU’s Center for Cyber-Physical Systems. Her recent research is focused on deploying emerging technologies. In collaboration with her team, she proposed a new data-driven framework that integrates an engine for data assessment. The framework deploys smart mobile edges as decision-makers where the selection of workers, in a heterogeneous mobile crowdsensing (MCS) environment, is based on their outcomes and the requested task requirements.����

Regardless of the challenges in her personal and professional lives, Dr. Lamaazi’s mission is to help women and girls, especially in the tech community, harness their talent and intellectual prowess so they can positively affect their society. “Be deaf, blind, and keep silent to all the negativity around you. Work hard, write your own story in your own way, and let your success define the fighter you are. At the end, it’s earned, not given,” Dr. Lamaazi advised.��

To know more about the WomenTech Network, visit their website .��

Ara Maj Cruz
Creative Writer
13 January 2022

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By Dr. Ernesto Damiani

The area of cybersecurity has expanded in scope, relevance and impact in our increasingly ICT-based society. In the first of six webinars aiming to strengthen the opportunities for bilateral cooperation between Italy and the United Arab Emirates, I was joined by experts to identify Cybersecurity gaps and opportunities that emerge with the continuing progress of IT developments like Artificial Intelligence.

As Noah Radford, Chief of Global Affairs for the Dubai Future Foundation, explained, it’s no secret that the UAE has experienced meteoric growth over the last 20 years, as the country has become a world leader in a variety of sectors, and as any complex system grows, so too does the number of challenges it must overcome. As we look towards the next 20 years, we must ask ourselves how we will tackle the questions that arise in a way which helps to benefit not just the UAE, but the region, and the world.

The future is certain to bring about a new paradigm in cybersecurity, driven by the fear of the damages that cybersecurity attacks can cause. Cyberattacks are estimated to cost the world USD$ 6 trillion this year, and a key figure in that calculation is the unprecedented rise of connected devices. The Internet of Things is the new era, with devices connected to the Internet enabling a more customized user experience. This does, however, also increase the number of devices at risk of cyberattacks, making cybersecurity a concern not just for businesses and industries, but also the average smartphone user.

While numerous protection schemes have proved to be useful and effective in certain situations against known attack threats, one of the biggest challenges is coping with the unknowns. Automation is already being explored as a tool to combat cyberattacks. Salvatore Fiorillo, Senior Consultant at Dubai Electronic Security Center (DESC), explained that 69 percent of business CEOs believe AI will be required to respond to cyberattacks, while 80 percent of executives in telecommunications believe they will be depending on AI in cybersecurity. Artificial Intelligence is one of the technologies that can be used to close the gap between knowledge-based threat detection and unknown or rapidly changing threats. AI could even foresee potential maliciousness in actors before they are known, offering great capabilities to overcome and help solve numerous challenges.

As cyberattacks start to target nation-states, countries around the world are instituting cybersecurity departments, with the UAE appointing its first Minister for Artificial Intelligence in October 2017 in its defense against cyber warfare. Fiorillo highlighted the impact a cyber attack can have on a country and how much a government relies on networked systems, citing the 2007 cyber attacks on Estonia as an example. Dr. Roberto Baldoni, Deputy Director General of the Department of Information for Security for Italy, agreed, explaining that the essential functions and services of a nation are digital, with energy, finance, welfare, defense and transport all at risk from cyberattacks. Creating a cyber-resilient nation is of paramount importance.

Dr. Mohamed Al-Kuwaiti, Head of Cyber Security for the UAE Government, Supreme Council for National Security, and Khalifa University alum, compared cybersecurity to the Covid-19 pandemic currently facing the world. People and organizations have suffered greatly from the coronavirus pandemic, with many critical lessons learned that can be applied to a potential global cyber pandemic. The start of the biological pandemic showed how unpreparedness around public health can have devastating effects, and this can be analogous to cybersecurity, with attention turning to protecting home users and remote workers.

“We hope to continue and move that hygiene that we adopted from the biological pandemic to the cyberspace,” Dr. Al-Kuwaiti explained. “Today, we can’t leave our homes without a mask or a sanitizer as a prevention measure. We make sure we don’t come into contact with anyone who could pose a risk. Cybersecurity is similar. We can quarantine an area of a network should a virus intrude. We can isolate such attacks and reduce the ‘infection’ rate between systems. The culture of building a very resilient network relies on all sectors from academia to industry.”

Following Dr. Al-Kuwaiti’s assertion that digital transformation is at the heart of the UAE’s national strategy, I wanted to share what we at Khalifa University are doing to research cybersecurity, particularly in the Robotics and Intelligent Systems Institute. In the last decade, the UAE has been investing heavily in transitioning from an oil-dependent economy to a Knowledge Economy. At the RISI, we’re aiming to coordinate the work done at KU in all ICT-related areas and boost its value for applications. Interestingly, we’re seeing that while AI can be extremely useful when dealing with cybersecurity solutions, it can be a double-edged sword. AI algorithms can be targeted too. To understand new threats, we as users need a clearer understanding of the lifecycle behind machine learning-based decision making and how systems are trained in the first place. Additionally, you can’t mention AI and not discuss blockchain these days. We are working on the idea of mapping threats to features of Distributed Ledger Technology, like blockchain. We can then use this technology as a security control framework to guarantee security to our machine learning data assets.

At Khalifa University, we’re proud to showcase our faculty expertise, especially in cybersecurity and its related fields as we continue to seek to expand the scope of our technology research, resulting in patents and technology transfer to start-ups.

Innov-Italy UAE aims at improving the opportunities for bilateral cooperation between the UAE and Italy in six high-innovation sectors, including cybersecurity, space, smart cities and sustainable mobility, life sciences, food technologies, and renewable energy.

Dr. Ernesto Damiani is Professor of Electrical Engineering and Computer Science, Senior Director of the Robotics and Intelligent Systems Institute & Director of the Center for Cyber Physical Systems (C2PS) at Khalifa University.

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Dr. Faisal Khan, Assistant Professor of Mathematics and a Principle Investigator in the Center for Cyber-Physical Systems (C2PS) at Khalifa University, will bring international attention to KU’s expertise in quantum computing at a mini-symposium he is organizing on Wednesday, 12 February 2020 in Seattle, Washington, USA, during the Society for Industrial and Applied Mathematics’ (SIAM) Conference on Parallel Processing for Scientific Computing.

Quantum computers can in principle be millions of times faster than conventional computers, and the current first generation of these machines can solve certain industrial optimization problems significantly faster than traditional computers. For example, in October 2019, Google’s quantum processor solved a problem in 200 seconds that a state-of the-art supercomputer would have require 10,000 years to solve.

Quantum computers are capable of such powerful, high-speed analysis and computation because unlike conventional computing, quantum computing is not limited to two bit values, 0 or 1. Rather a qubit can be 0 or 1, or have properties of both of these values simultaneously, which is called superposition.

Dr. Khan, who heads the University’s Quantum Computing Research Group, will showcase the fundamental contributions he and other KU faculty are making to the field of quantum computing; a market which is expected to exceed US$495 million by 2023, according to a report by market research analysts Markets and Markets.

His presentation, titled “Nash embedding: A roadmap to realizing quantum hardware” will describe “an approach to engineer hardware for quantum computers that – unlike current ‘synthetic’ or ‘quasi-quantum’ hardware prototypes – is robust against classical noise arising from the environment in a mathematically and physically precise way,” Dr. Khan explained. The approach is based on the work of the Noble Laureate, John Nash, in differential geometry.

The symposium participants include individuals who are at the forefront of research in the field of quantum computing and its applications to industry. They will be answering questions like: What are quantum computers (QCs) today and what will they be like in the next five to 15 years? In what mathematical models should subject-matter experts formulate their problems so applications will benefit from QCs in a sustainable way? How will subject-matter experts develop applications for QCs? What are to be considered best practices in developing and programming quantum computing architectures? And what opportunities for quasi-automatic transformation by new compiler-like tools can exploit the power of well-matched mathematical models?

By organizing a mini-symposium that will facilitate dialogue among some of the world’s leading quantum computing researchers and academics, Dr. Khan is helping to position the UAE as a reference for knowledge and innovation in quantum computing.

Erica Solomon
Senior Editor
27 January 2020

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At its first symposium on September 12, the Center for Cyber-Physical Systems (C2PS) convened center researchers, potential research partners, guest speakers from institutions around the world, and organizations involved in the AI industry to discuss applied artificial intelligence and cybersecurity.

The projects undertaken at the center were proudly presented and framed in the context of how they respond to the major challenges of Industry 4.0, the exponential growth in the size of ambient data, particularly in the context of the Internet of Everything, and the need to ultimately shift from assisted to autonomous intelligence paradigms. Techniques for establishing trust relations among internet-of-everything (IoE) devices, edge processors, cloud-based applications, and other components of the cyber-physical systems (CPS) ecosystem were also highlighted.

“We aim to create understanding and empowerment through support and development of existing technological capabilities and responsibility for global standardization,” said Dr. Ernesto Damiani, C2PS Director. “In doing so, we are improving quality of life, as well as the cyber technology experience for users in the long term.”

After opening remarks from Dr. Arif Al Hammadi, Executive Vice President, and Dr. Steve Griffiths, Senior Vice President of Research and Development, explaining the university’s commitment to researching the complete range of technological areas underlying CPS and supporting the secure technological innovations required to achieve the Abu Dhabi Economic Vision 2030, Dr. Damiani opened the symposium with a presentation on the open problems in artificial intelligence and security.

“We are privileged to live in such a dynamic time where emerging technologies create endless opportunities for value creation,” he said.

“Looking back to the last decade, we can easily highlight the game changers—the discoveries that ushered in a new framework for thinking, spurred scientific enquiry, and revolutionized our lives. Thanks to such discoveries, we no longer assert that something is technologically impossible; we only wonder how long before it will fit in the hand of a child.

“The Internet of Things (IoT) promises to add efficiency at all layers of our globalized society’s fabric. From industry, to business, government, and even entertainment, IT is going to change our lives for the better, enabling a smarter, sustainable future.”

Delegates were offered a glimpse of this future through many presentations, including that of key note speaker Dr. Fakhri Karray, Visiting Professor and Director of the Waterloo University’s Center for Pattern Analysis and Machine Intelligence. Dr. Karray explained the advances in intelligent mobility and how the goal is to design more efficient, more intelligent, and safer transportation systems better suited to the latest advances in information and communication technologies. He laid out the challenges and opportunities in designing the next generation autonomous vehicles and building the more sustainable cities of the future.

Following Dr. Karray, Dr. Naoufel Werghi, Associate Professor at C2PS, introduced the concept of visual data representation and its importance in the process of facial identification. He explained that face recognition applications and distinguishing features within the spectrum of biometric modalities have been rigorously researched, but that there are new challenges to facial data that need to be researched. Dr. Werghi emphasized the vital role of face shape representation when dealing with 3D images and addressed the problem of people identification in fully arbitrary and extreme conditions.

Fellow Research Scholar in C2PS, Dr. Song-Kyoo Kim followed, introducing a framework for how to appropriately adopt and adjust machine learning (ML) techniques to construct electrocardiogram-based (ECG) biometric authentication schemes. The proposed framework can help investigators and developers on ECG-based biometric authentication mechanisms define the boundaries of required datasets and get training data with good quality.

Dr. Ibrahim Elfadel, Professor of Electrical Engineering and Computer Science, was joined by Dr. Rupesh Karn, Postdoctoral Fellow, to survey the field programmable gate array (FPGA) virtualization challenges, and the various solutions proposed by academia and industry to address them. They explained the pressing performance demands of AI workloads have led data centers and cloud service providers to deploy heterogeneous hardware fabrics, including CPUs, GPUs and FGPAs that offer users a wide spectrum of performance and cost options. They concluded that FPGAs provide more hardware flexibility, higher performance, and lower power footprint, but that they present distinct challenges to the deployment of a lightweight virtualization layer that does not hamper the advantages of their bare-metal usage.

Lunch was followed by a presentation from visiting professor Dr. Moataz Ahmed, Associate Professor of Information and Computer Science at King Fahd University of Petroleum and Minerals, on artificial lifts in the oil industry and how automation of their monitoring can improve performance and prevent financial losses. Importantly, he explained how just a one percent improvement in their performance could provide over half a million additional barrels of oil each day worldwide, and that various machine learning methods could be used to monitor conditions, detect anomalies, identify issues, and predict failures in artificial lift devices.

With the tremendous advances in ubiquitous computing, mobile crowd sourcing (MCS) has become an appealing part of IoT, explained KU’s Dr. Rabeb Mizouni, Associate Professor of Computer Engineering, and Engineer Menatella Abououf. They detailed how in MCS systems, workers collect data with a certain quality of service (QoS) and get incentivized in return, but that MCS systems are vulnerable to misbehavior, with workers submitting false or fake reports to degrade the QoS or maximize their profit with minimal costs. They presented a selection approach based on game-theory in their presentation, in which their model detects and eliminates misbehavior.

The final presentation was delivered by visiting scholar Dr. Emanuele Bellini, contributor to the European Virtual Institute for Integrated Risk Management. Dr. Bellini noted that it is cumbersome to evaluate the credibility of messages transmitted on an open and vast network, and that a decentralized trust management system, made possible through block chain technology, can authenticate the messages received from other systems. His talk focused on the adoption of block chain in trust and reputation management systems implementation, highlighting significant trends and providing valuable recommendations.

A panel discussion rounded off the event, with Dr. Damiani closing the symposium.

The C2PS Symposium brought together some of the most innovative minds in cyber-physical systems and computer technology sectors, reflecting KU’s commitment to creating an environment that encourages the sharing of ideas about key areas of science and engineering, which can lead to further innovation and useful collaborations.

Jade Sterling
News and Feature Writer
25 September 2019

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Winning the Best Paper Award at the IEEE International Conference on Cognitive Computing, Dr. Ibrahim Elfadel, Professor of Electrical and Computer Engineering, and his group use novel algorithms to better predict information saturation in artificial neural networks.

Artificial intelligence (AI) systems have achieved state-of-the-art performance in many machine learning tasks, but are yet to outperform the human brain, not least because they keep forgetting previously learned information. In a paper which won the Best Paper Award at the IEEE International Conference on Cognitive Computing, Milan, Italy, in July 2019, Dr. Ibrahim Elfadel, Professor of Electrical Engineering and Computer Science and Principal Investigator with the KU Center for Cyber Physical Systems, Dr. Rupesh Raj Karn, Postdoctoral Fellow, and Dr. Prabhakar Kudva, IBM Research Staff Member address this important problem of forgetful systems.

Artificial neural networks (ANN) are computing systems inspired by biological neural networks found in animal brains. Such systems learn to perform tasks by considering examples, generally without being programmed with task-specific rules. In image recognition, for example, an ANN may learn to identify images that contain cats by being trained on example images that have been manually labelled as “cat” or “not cat” and then using these the trained network to identify cats in other images. They do this without any prior knowledge of what constitutes a cat—i.e. that they have tails, whiskers and fur—by generating identifying characteristics from the examples they process.

However, when building a system or adding new capabilities, increasing the number of tasks required means that the system must preserve the inference accuracy based on the original data while incrementally training on additional data. For example, a robot may be delivered to a customer’s house with a set of default object recognition capabilities, but new site-specific object models may needed for the robot to navigate in the presence of objects not included in the original training set.

“Traditional machine learning models have typically assumed that all the training data is available prior to the model building phase,” explained Dr. Elfadel. “Very often, this is not the case.”

ANNs, especially those with multiple interconnected layers of neurons, also known as Deep Neural Networks (DNNs), have a higher capacity for progressive learning than other traditional machine learning models, mainly due to the potentially large number of parameters which can be tuned to incrementally build more accurate models. “However, even progressive learning on such DNNs cannot go on forever,” said Dr. Elfadel.

Programming AI to Not Forget with Task Progressive Learning

Catastrophic forgetting is the tendency of an ANN to completely and abruptly forget previously learned information upon learning new information. This makes continual learning difficult. While an ANN is based on the design of the human brain, there’s a fundamental difference between the two: humans leverage prior experiences to acquire new knowledge, but an AI system almost always needs to start from scratch. Granting ANNs with this ability is a cognitive computing conundrum.

“You can think of it this way: in an ANN (and possibly also in the human brain) memory data is encoded diffusively in the weights of the connections between the neurons,” explained Dr. Elfadel. “It is not easy to pin down the memory cells undergoing catastrophic forgetting. Nor is it easy to pin down what is being forgotten among already stored data.”

One possible solution is task progressive learning. This should effectively transfer knowledge across a series of tasks, incorporating prior knowledge at each layer by reusing old computations in learning new ones. Progressive networks are designed to retain a pool of pre-trained models throughout training and learn lateral connections to extract useful features for new tasks—much like the human brain does.

“Task progressive learning without catastrophic forgetting using artificial neural networks has demonstrated viability and promise,” said Dr. Elfadel. “Due to the large number of ANN hyper-parameters, a model already trained over a group of tasks can further learn a new task without forgetting the previous ones.”

Several algorithms have been proposed for progressive learning, including synaptic weight consolidation, ensemble, rehearsal, and sparse coding.

Detecting Information Saturation in ANNs

“One major problem with such methods, however, is that they fail to detect the congestion in the ANN shared parameter space to indicate the saturation of the existing network and its inability to add new tasks using progressive learning,” explained Dr. Elfadel. “The detection of such saturation is especially needed to avoid the catastrophic forgetting of old trained tasks and the concurrent loss in their generalization quality.

An ANN is based on a collection of connected units called artificial neurons, with each connection able to transmit a signal to other neurons. An artificial neuron that receives a signal then processes it and signals other neurons connected to it. These connections have a “weight” that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection.

“In all these methods, the set of ANN weights needed to accommodate the new tasks grow with their number. Intuitively, the ANN should become congested as soon as the set size is too high relative to the total number of weights. This intuitive congestion measure is clearly correlated with the onset of catastrophic forgetting.”

“In progressive learning, a tuning criterion is typically applied over the trajectory of ‘important’ ANN parameters in weight space so that their contours do not deviate much with respect to those defined by older tasks,” explained Dr. Elfadel. “The basic idea is that in an ANN, congestion should be detected when all of the parameters become ‘important’ for the training of older tasks. Once this is achieved, a barrier to progressive learning is created, and any further learning of new tasks would result in the catastrophic forgetting of older tasks.”

The paper proposes a methodology for ANN congestion detection based on computing the Hessian of the ANN loss function at the optimal weights for a group of previously learned tasks. In mathematics, the Hessian describes the local curvature of a function of many variables.

Predicting Saturation with Heuristic Algorithms

“Since the Hessian calculation is compute-intensive, we provide Hessian approximation heuristics that are computationally efficient,” said Dr. Elfadel. “The algorithms are implemented and analyzed in the context of two cloud network security datasets with results showing that the proposed metrics give an accurate assessment of the ANN progressive learning capacity for these datasets. Furthermore, the results show that progressive learning capacity is very much data-dependent with the network security data sets exhibiting higher congestion thresholds for progressive learning than the more traditional image data sets used in DNNs.”

The paper describes how a snapshot of the parameters is taken after each progressive training phase, with the rank of the loss function Hessian measured at these parameters. Closeness to full rank is indicator of a congestion risk in the ANN and of possible catastrophic forgetting.

“Our work provides a way to measure congestion and can be applied to several incremental learning paradigms such as multi-task continual learning, transfer learning, and progressive learning, to measure the risk of catastrophic forgetting with the learning of newer tasks,” said Dr. Elfadel. “We are very pleased with this award and grateful to the KU Institute for Artificial Intelligence and Intelligent Systems and its Center of Cyber Physical Systems for facilitating our participation in this IEEE conference. We hope that our techniques will become part of the automated machine learning design toolbox of data scientists and cognitive system designers.”

Jade Sterling
News and Features Writer
6 October 2019

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The Cyber-Physical System Center (C2PS) hosted its second open symposium, to mark the one-year anniversary of the Center, on Thursday, 21 November at the Main Campus.

Held under the theme “5G and Emerging Distributed Architecture,” the symposium provided a forum for C2PS researchers and potential research partners to share knowledge and ideas about the future of computing and communications.

C2PS researchers presented projects related to two of its four themes, including Networks and Communication Technology, and Computation Architecture.

Dr. Sami Muhaidat, Associate Professor of Communication Engineering, and Dr. Arafat Al-Dweik, Associate Professor of Electrical Engineering and Computer Science spoke about the Networks and Communication Technology theme. They addressed several major challenges preventing the realization of next generation wireless networks, including the high energy and spectral efficiency, low latency, and massive connectivity.

Dr. Davor Svetinovic, Associate Professor of Electrical and Computer Engineering, and Eng. Ruba Alkadi, Research Associate of C2PS, presented on projects related to the Computation Architecture theme. They addressed the importance of selecting the proper platform, infrastructure, and technologies to facilitate and support, at any scale, the required computing, storage, and networking functionalities for CPS and IoT ecosystems.

International experts were invited to address important topics in blockchain, RF-powered radio networks and 6G challenges. International guest speakers included Dr. Mohamed-Slim Alouini, Associate Dean of King Abdullah University of Science and Technology, and Dr. Muhammad Ali Imran, Vice Dean at Galsgow College of UESTC, UK.

The Symposium closed with an engaging panel session moderated by Dr. Ernesto Damiani,�� Senior Director of Artificial Intelligence and Intelligent Systems Institute, Director of C2PS Center, and Professor of Electrical and Computer Engineering.

Erica Solomon
Senior Editor
21 November 2019

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