Muriel Medard

Our work on understanding the potential of peering among cellular providers will appear in IEEE TCCN. The study sheds light on the viability of settlement-free peering as an alternative roaming agreements among the cellular providers. Our framework suggests that the providers select regions where they will treat each other's customers equal to their subscribed customers -- without charging roaming fees which is the current practice. Anindo Mahmood Shahzeb Mustafa Sayanta Seth, Ph.D Mostafizur Rahman

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Our paper, "A Conceptual Framework for Applying Large Language Models in Smart Grid Cybersecurity," is now available on IEEE Xplore. The paper provides a conceptual starting point for exploring how the complementary capabilities of Large Language Models (LLMs) and Digital Twins (DTs) can be effectively integrated to address the complex, evolving cybersecurity challenges in Smart Grids and thus enhance their cybersecurity posture. Thanks to all co-authors : Chenghong Gu , Satish Sharma and Dr. Rohit Bhakar.

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Check out our recent publication in IEEE Wireless Communications Letters entitled " GumbelRIS: End-to-End CNN-Based 2-Bit Phase Optimization for Large-Scale RIS-Aided MIMO Systems". The work, led by our brilliant PhD researcher Kinza Shafique and with the insightful contribution of Dr. Haitham Saleh, shows that the proposed technique outperforms metaheuristics and learning-based baselines across varying RIS sizes and channel conditions and generalizes well without retraining. https://lnkd.in/dTjrUetd #RIS #MIMO #6G 

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Our report from the SAGAI workshop (with IEEE S&P 2025) is now out: https://lnkd.in/g39ZG9GQ It defines the "systems security" approach for AI agents and highlights the research challenges that arise when applying systems principles. This is version 1, and a version 2 is coming soon with additional insights!

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The July 28, 2025 issue of the RISC Institute's weekly Media Bulletin--𝘚𝘤𝘪𝘦𝘯𝘤𝘦 𝘪𝘯 𝘍𝘭𝘶𝘹: 𝘗𝘰𝘭𝘪𝘤𝘺, 𝘗𝘰𝘸𝘦𝘳, 𝘢𝘯𝘥 𝘵𝘩𝘦 𝘗𝘶𝘳𝘴𝘶𝘪𝘵 𝘰𝘧 𝘗𝘳𝘰𝘨𝘳𝘦𝘴𝘴-- is now available at tx.ag/RMB728. Here are some key themes featured in this week's issue: - 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗙𝘂𝗻𝗱𝗶𝗻𝗴 = 𝗡𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: Cuts to university research threaten the innovation pipeline critical to U.S. defense and global leadership. - 𝗔𝗜 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝘀 𝗩𝗮𝗹𝘂𝗲𝘀 + 𝗜𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁: To outpace China, the U.S. must invest in AI while ensuring systems reflect democratic principles. - 𝗘𝗾𝘂𝗶𝘁𝘆 𝗮𝗻𝗱 𝗔𝗰𝗰𝗲𝘀𝘀 𝗶𝗻 𝗦𝗰𝗶𝗲𝗻𝗰𝗲: NIH and NSF are pushing for fairer access to research, limiting excessive fees and expanding AI infrastructure. Subscribe for free at 𝘁𝘅.𝗮𝗴/𝗥𝗜𝗦𝗖𝗯𝘂𝗹𝗹𝗲𝘁𝗶𝗻𝘀𝘂𝗯𝘀𝗰𝗿𝗶𝗯𝗲

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New Perspective in Nature Reviews Electrical Engineering on Deep learning software stacks for analogue in-memory computing-based accelerators. Analogue in-memory computing (AIMC) is a promising approach to enhance the efficiency of deep learning inference workloads. Corey Lammie, Abu Sebastian and colleagues (from IBM Research Europe) discuss how the integration of AIMC with digital processing units can facilitate the execution of various deep neural network models. The authors also highlight the unique challenges posed by AIMC, including the inherent stochastic nature of AIMC tiles, the need for weight stationarity and pipelined execution, which need to be addressed for achieving optimal performance. Read the full article here: https://lnkd.in/eXX7T9Ey

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Delighted to share news of SiFive collaboration with NVIDIA to bring NVLink Fusion to SiFive high-performance RISC-V compute solutions. SiFive customers can now seamlessly integrate our customizable RISC-V compute subsystems with NVIDIA AI Infrastructure to enable new data center AI solutions: #riscv https://lnkd.in/gk4rKsac

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Incredible news for Sweden’s tech landscape! 🇸🇪 A consortium of top Swedish companies—AstraZeneca, Ericsson, Saab, SEB, and more—are teaming up with NVIDIA to build a sovereign AI supercomputer. This is a game-changing opportunity to accelerate innovation, boost competitiveness, and build cutting-edge AI capabilities right here in Sweden. Huge thanks to the Wallenberg family for making this bold vision a reality. The future of AI in Sweden just got a massive boost! 🚀 #AI #Innovation #Sweden #Wallenberg #NVIDIA #TechLeadership https://lnkd.in/d86aGtCp

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🚨New publication alert!🚨 We have a new paper, "From Intent to Accountability: Exploring the Role of Mental States in Robot Accountability", accepted to IEEE ARSO 2025! Mental states, such as beliefs, intentions, and desires, have been considered key elements of human agency, indicating one’s capacity to act deliberately and with awareness. Thus, these mental states have been treated as crucial factors in assessing human accountability. However, it remains unclear whether these mental states are equally important to robot agency and, by extension, to robot accountability. To explore this tension, Boyoung Kim, Qin Zhu, Elizabeth Phillips, PhD, and I investigated how participants judged the relevance of mental states in determining the accountability. of an industrial robotic arm or a humanoid robot compared to a human after a workplace accident in which a worker was injured. Our results showed that participants viewed desires, beliefs, and intentions as significantly less relevant when assessing the accountability of robots than humans, and robots were judged as less accountable overall. These findings suggest a need to move beyond human-centered views of agency– particularly those based on assumptions about mental states– when discussing the accountability of robots. To find out more, read the paper! https://lnkd.in/d2e4D8-u

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In our latest journal paper, we share the blueprint of a radar-based system that can monitor walking patterns in home environments, potentially transforming how we care for older adults. The paper has been published in IEEE Transactions on Radar Systems: https://lnkd.in/gJi3Fzrh Walking patterns are incredibly valuable indicators of health, but it has not feasible for doctors to observe them regularly. That's why we created a system using MIMO FMCW radar technology that can continuously track movement even in cluttered and realistic living spaces (not just within a lab setting). Think of it as a smart home feature that watches over your loved ones' wellbeing through their natural daily movements. We tested our system at University of Waterloo with participants walking at different speeds and step lengths, and the results are promising. The technology successfully captured walking speed, step count, and step length while filtering out the "noise" from furniture and other household objects. This could mean around-the-clock health monitoring without intrusive cameras or wearable devices, giving families peace of mind and healthcare providers valuable data for early detection of health changes. This work brought together several talented researchers: Hajar Abedi, @Jenna Hall, @Ji Beom Bae, Plinio Morita, Alexander Wong, and Jennifer Boger. Together, we have been working toward a future where technology enables better aging in place. Fun Fact: We have have had many of our radar systems for health monitoring at the #MIRADA - A living lab at the Schlegel-UW Research Institute for Aging (RIA). We plan to add more and we are always happy to showcase our demos. Would love to hear your perspectives! #HealthTech #AgingInPlace #RadarTechnology #DigitalHealth #Research #Innovation #Healthcare

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We just published this paper on IEEE Trans. on Vehicular Technology -x-x- Y. Zhang, J. Chen, H. Wei, M. G. Simões and H. Zhang, "Data-Driven Lyapunov-Based Model Predictive Control for Improved Trajectory Tracking in Multi-Wheel-Independent-Drive Electric Vehicle," in IEEE Transactions on Vehicular Technology, doi: 10.1109/TVT.2025.3587541 Abstract - This paper proposes a data-driven Lyapunov-based Model Predictive Control (LMPC) method for multi-wheel independent-drive electric vehicles to enhance the trajectory tracking accuracy while ensuring the vehicle stability. To improve the accuracy of the vehicle dynamics model, we first develop a temporal residual network to learn the residual between the nominal vehicle dynamics and the actual vehicle dynamics from a lot of training data offline. The temporal residual network predicts the vehicle dynamics residual online based on the vehicle states within a past time window. Then, by combining the nominal vehicle dynamics model with the temporal residual network, a more accurate compensation model is obtained. Building on this, we propose a novel data-driven control strategy specifically optimized for trajectory tracking. To ensure vehicle stability, a Lyapunov-based constraint based on the designed backstepping controller is incorporated into the data-driven LMPC. Subsequently, theoretical analysis is presented to validate the stability of the system. In the Carsim & Simulink co-simulation environment, we validated the effectiveness of the proposed temporal residual network and tracking control algorithm through open-loop and closed-loop simulations. keywords: Vehicle dynamics; Predictive models; Accuracy; Tires; Trajectory tracking; Residual neural networks; Neural networks; Wheels; Predictive control; Motors; Multi-wheel vehicle; Deep learning; Data-driven modeling; Lyapunov-based MPC; Trajectory tracking

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A New Step Toward Quantum-Enhanced Optical Communication Excited to share that we’ve published a new paper together with my student, Gokul Manavalan. 🚀 In this work, we show that quantum neural networks can effectively correct highly distorted optical signals and recover the original information with remarkable accuracy. To make this approach practical, we also introduce a “quasi-quantum” model that runs on standard computers while delivering performance close to true quantum systems. These results highlight a scalable path for bringing quantum and quantum-inspired ideas into next-generation optical communication technologies. https://lnkd.in/dDegFkX9

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