Seyda Ertekin

Want to know about basics of metasurface. Check out our book chapter titled "Metasurface: An Insight Into Its Applications" published at Wiley. Special thanks to Fahad Ahmed for excellent contribution. See full chapter at: https://lnkd.in/dX_6jRWp

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Quantum Internet - Please check our paper published on IEEE Network magazine. https://lnkd.in/e7ueWYVW Uman Khalid Junaid ur Rehman, Ph.D. Saw Nang Paing Haejoon Jung We discuss the potential of the near-term quantum networks using noisy intermediate-scale quantum (NISQ) technologies. It highlights the architectural and operational principles necessary for developing these quantum networks and emphasizes their application in enhancing quantum computing, communication, and sensing. The paper provides a comparative analysis of network performance improvements and addresses technical challenges that must be overcome to realize practical and effective quantum networks. Overall, the paper identifies the advancements and ongoing efforts towards achieving a functional quantum internet, delineating a clear path from current capabilities to future possibilities.

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The following link provides full-text access to a view-only version of our recently published paper: https://rdcu.be/dWkex School of Civil Engineering, College of Engineering, University of Tehran

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100+ Citations for One of Our Published Papers The paper titled “Semiconductor technologies for 5G implementation at millimeter wave frequencies – Design challenges and current state of work,” which we published in 2021, has crossed 100 citations on Google Scholar (83 on Scopus). In this paper, we discussed in detail how evolving semiconductor technologies are contributing toward employing underutilized millimeter wave (mmW) frequencies for 5G cellular network implementation. Anybody who is working in the area of hardware design for future cellular network implementation will find this paper useful. The paper has been co-authored by Dr. RAJNISH SHARMA and Dr. Rajendra Pratap, Ph.D., under whom I completed my PhD at Chitkara University. It was published by Elsevier in the journal entitled ‘Engineering Science and Technology, an International Journal’ - https://lnkd.in/gkMcNbF9 #ChitkaraU #Elsevier #Research #semiconductor #5G Chitkara University Publications Chitkara University

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🏆 Congratulations to Research Scientist Shiran Dudy (pictured below), Postdoctoral Research Fellow Ibrahim Said Ahmad, and Principal Research Scientist Àgata Lapedriza on their Best Paper Award in Affective Computing and Intelligent Interaction at this year’s #ACII2024 Awards Ceremony! 👏   The group’s paper "Analyzing Cultural Representations of Emotions in LLMs through Mixed Emotion Survey" explores a growing interest in #academia to use #LLMs to simulate and study human behaviors, and how LLMs represent emotions across different cultures.   Read more about their research here: https://bit.ly/4huRYv9 #AI #artificialintelligence #research #tech #generativeAI #genAI #AIresearch #emotions #science

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I am pleased to announce our recent collaboration with the esteemed Prof. Zahid Hasan group at #Princeton University's Laboratory for Topological Quantum Matter. Our joint effort has led to a remarkable discovery, detailed in the prestigious #Nature Journal, unveiling an unprecedented form of topological quantum behavior within elemental solid crystals composed of arsenic (As) atoms. Termed as "hybrid topology," this newly identified quantum state showcases a fusion of edge and surface states within arsenic crystals, presenting a paradigm-shifting revelation in quantum phenomena. Leveraging cutting-edge imaging methodologies, our findings represent a significant stride forward in the realm of quantum materials research, promising profound implications for the development of innovative quantum devices and technologies." https://lnkd.in/gATsQmfr

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Thank Saint Louis University School of Science and Engineering for sharing our work! This dual recognition, being named a finalist for both #GordonBell (general track) and #GordonBell for #Climate Modelling, highlights the critical role of the #PaRSEC task-based runtime system, co-developed with University of Tennessee, Knoxville and a key focus of my research, in advancing complex scientific applications. 𝐄𝐱𝐚𝐬𝐜𝐚𝐥𝐞 𝐆𝐖𝐀𝐒: a finalist for #GordonBell, in partnership with KAUST (King Abdullah University of Science and Technology), Massachusetts Institute of Technology, and NVIDIA. By implementing mixed-precision computations and relying on PaRSEC, Exascale GWAS significantly enhances Kernel Ridge Regression (KRR), a critical technique for analyzing genetic data, achieving a performance improvement of five orders of magnitude over the state-of-the-art CPU-only REGENIE, the current leading software for similar tasks. More details: https://lnkd.in/gEUKwYd6. 𝐄𝐱𝐚𝐬𝐜𝐚𝐥𝐞 𝐂𝐥𝐢𝐦𝐚𝐭𝐞 𝐄𝐦𝐮𝐥𝐚𝐭𝐨𝐫: a finalist for #GordonBell for #Climate Modelling, in partnership with KAUST (King Abdullah University of Science and Technology), NSF NCAR - The National Center for Atmospheric Research, University of Notre Dame, and NVIDIA. This exascale climate emulator is to address the growing computational and storage demands of high-resolution Earth System Models. By leveraging advanced numerical methods with the PaRSEC dynamic runtime system, the resulting pipeline, stochastically models spatio-temporal variations in climate data, boosts computational efficiency, greatly enhances the accuracy of climate emulators, and provides critical insights for understanding climate change and extreme weather patterns. More details: https://lnkd.in/gqs_QgHr. Many thanks to our 𝐄𝐱𝐚𝐬𝐜𝐚𝐥𝐞 𝐆𝐖𝐀𝐒 team (Hatem Ltaief, Rabab Alomairy, Ph.D., Jie Ren, Lotfi SLIM, Thorsten Kurth, Benedikt Dorschner, Salim Bougouffa, Rached Abdelkhalek, and David Keyes), our 𝐄𝐱𝐚𝐬𝐜𝐚𝐥𝐞 𝐂𝐥𝐢𝐦𝐚𝐭𝐞 𝐄𝐦𝐮𝐥𝐚𝐭𝐨𝐫 team (Sameh Abdulah, Allison Baker, George Bosilca, Stefano Castruccio, Marc Genton, David Keyes, Zubair Khalid, Hatem Ltaief, Yan Song, Gera Stenchikov, Ying Sun), and the 𝐏𝐚𝐑𝐒𝐄𝐂 team (George Bosilca, Thomas Herault, Aurelien Bouteiller, and Joseph Schuchart)!

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I'm happy to share that our paper, "On the Efficacy and Vulnerabilities of Logic Locking in Tree-Based Machine Learning," has been accepted for publication in IEEE Transactions on Circuits and Systems-I. This work and collaboration were initiated by Prof. Hussam Amrouch at Technical University of Munich and led by Brunno Alves de Abreu and Guilherme Paim. In this paper, we demonstrate that when logic locking is applied to circuits used in real-world applications—beyond the typical ISCAS and ITC benchmarks, such as tree-based machine learning structures—new vulnerabilities in logic locking emerge that were previously unaccounted for. You can read more here: https://lnkd.in/dvhVyHEU Khalifa University, College of Computing and Mathematical Sciences at Khalifa University, New York University Abu Dhabi,Paulo Flores,Ozgur Sinanoglu, Sergio Bampi, University of Lisbon, Federal University of Rio Grande do Sul #LogicLocking #MachineLearning #CircuitSecurity #ICDesign #Cybersecurity #HardwareSecurity #Semiconductor #ResearchPublication #IEEE #TreeBasedML #DesignForTrust

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I'm thrilled to share that our latest paper, "Systematic Review of Software Engineering Uses of Multi-Criteria Decision-Making Methods: Trends, Bibliographic Analysis, Challenges, Recommendations, and Future Directions," has been published in Applied Soft Computing (Q1, IF 8.7)! 🔗 Check out the paper here: https://lnkd.in/dyB5svSq This comprehensive review delves into the fascinating field of multi-criteria decision-making (MCDM) and its impactful applications in software engineering. We cover the latest trends, provide an in-depth bibliographic analysis, and discuss the challenges and future directions in this dynamic area. For those interested in how MCDM theory has contributed to advancing software engineering, this paper is a must-read! Happy reading! 📚💡 #Research #SoftwareEngineering #MCDM #DecisionMaking #AppliedSoftComputing #AcademicPublication #Engineering #Innovation #FutureDirections

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Check out our latest work on Multi-Task Learning, written by my undergraduate student Daniel Mao, alongside coauthors Yifan Wu, Maximilian Gilles, and Alexander Wong. In this study, we conducted an empirical investigation of multi-task learning in the context of vision for robotic bin picking, utilizing Multi-modal RGB+Depth inputs and addressing seven diverse objectives, including regressions, classifications, and mask predictions. Our findings reveal that not all MTL methods are effective in practice. Our experimental results offer the community deeper insights into the fundamental nature of MTL problems. https://lnkd.in/gyG_ixaX #MTL #Deeplearning

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Glad to share my newly published paper on the role of generative AI in the development of Brain-Computer Interfaces (BCIs). #AI #BCI #innovation #healthcare https://lnkd.in/dPSHvQkj

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I will be presenting our paper "Estimating Direct and Indirect Treatment Effect in the Presence of Spatial Interference" at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD'24) next week. Though I loved to present at the conference in person in Lithuania, I would be joining remotely to present our work. If you're attending the conference and interested to chat about spatiotemporal causal inference, I would love to get in touch. Some key highlights from the paper: 1. Our paper presents a spatiotemporal causal inference method based on U-Net architecture that has both predictive and inferential capabilities. 2. Our model can capture spatial interference in time-varying data at several lead times. 3. We generated a synthetic dataset based on diffusion model to evaluate various spatiotemporal causal inference models. Our paper is published in the "Machine Learning and Knowledge Discovery in Databases. Research Track" https://lnkd.in/es2iSVVi #ecml2024 #pkdd #causalML #deeplearning

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Our new paper, 'Data-Driven Bottleneck Detection on Tehran Highways,' presents a scalable big data solution with global applicability for addressing urban mobility challenges like traffic congestion. Elsevier Iman Gholampour https://lnkd.in/dKgSMqQX

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I am happy to share my latest article with Prof. Haythem Bany Salameh, Prof. Moussa Ayyash, PhD, and Prof. Hany Elgala published in IEEE Sensors Journal. This article introduces a novel optimized LED power management framework that utilizes the estimated locations of obstacles to improve communication performance in VLC-enabled indoor networks. The main objective of the proposed framework is to maximize the achieved data rates and power savings in blockage-rich indoor environments by optimizing the LED power allocation while adhering to predefined bit error rate (BER), permissible localization errors, and illumination constraints.

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Trading off between model complexity and horizon length is tricky in any computation-limited control setting. In this work, we get both long horizons in general and high fidelity models when needed by using our "Adaptive Complexity MPC" framework. Great job, Joe Norby, Ardalan Tajbakhsh, and Yanhao Yang! Paper: https://lnkd.in/eFcctT5E #robot #robotics #leggedrobot #mpc #quadruped #controls #controlsystem #trajectoryoptimization

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🚀 Excited to share our latest research! 🚀 Our new paper, titled "GRAAFE: GRaph Anomaly Anticipation Framework for Exascale HPC Systems", is now published! 🎉 In collaboration with an amazing team of experts—Martin Molan, Mohsen Seyedkazemi Ardebili, Junaid Ahmed Khan, Francesco Beneventi, Daniele Cesarini, Andrea Borghesi, and Andrea Bartolini—we have developed GRAAFE, a groundbreaking framework designed to anticipate anomalies in exascale high-performance computing (#HPC) systems. 🔍 Abstract: The main limitation of applying predictive tools to large-scale supercomputers is the complexity of deploying Artificial Intelligence (AI) services in production and modeling heterogeneous data sources while preserving topological information in compact models. This paper proposes GRAAFE, a framework for continuously predicting compute node failures in the Marconi100 supercomputer #CINECA. The framework consists of (i) an anomaly prediction model based on graph neural networks (GNNs) that leverage nodes’ physical layout in the compute room and (ii) the computationally efficient integration into the Marconi100’s #ExaMon holistic monitoring system with Kubeflow, an #MLOps #Kubernetes framework which enables continuous deployment of AI pipelines. The GRAAFE #GNN model achieves an area under the curve (AUC) from 0.91 to 0.78, surpassing state-of-the-art (SoA), achieving AUC between 0.64 and 0.5. GRAAFE sustains the anomaly prediction for all the Marconi100 nodes every 120s, requiring an additional 30% CPU resources and less than 5% more RAM w.r.t. monitoring only. 🔗 Link to the paper: https://lnkd.in/dhkGZ9G8 🔗 Link to Dataset: https://lnkd.in/dg-__eMX 🔗 Link to Code: https://lnkd.in/dMC2VGpZ. 🔗 Link to Code: https://lnkd.in/d37EFKhT #DECICE #DECICEproject #HPC #Research #Innovation #Exascale #GraphAnalysis #AnomalyDetection #AI #Teamwork #CINECA #kubeflow #kubernetes

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I'm glad to share our new paper, which reports on the development of an e-tongue for sensitive monitoring of neurotransmitters using four different #MXenes as sensing units. Note that the first two authors were visiting scientists from Brazil and Azerbaijan at A.J. Drexel Nanomaterials Institute. Without them, this work would not be done, and we would not even start it. This shows the importance of bringing creative international visitors who implement their original ideas. Increasing restrictions will badly hurt the scientific productivity of US research labs. #research #science #MXene, #etongue #sensors #collaboration #visitingscientists

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Join the #openscience movement in software engineering by reading our paper: "A Conceptual Framework and Recommendations for Open Data and Artifacts in Empirical Software Engineering" Yes, it is #openaccess Per Runeson, Emma Söderberg, Martin Höst

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