Zoe Liu’s Post

🌐"Dose of New Engineering Ideas" on Quora: Refocused Direction and Latest Post! I am pleased to share that I have shifted my focus to summarizing technical research papers and exploring their practical applications. Initially, my discussions revolved around broad applications such as integrating quantum computing, neuromorphic computing, cybersecurity, IoT, and geospatial engineering, with an emphasis on their potential strategic implications. Moving forward, I will be summarizing research papers licensed under CC BY 4.0, highlighting open-source publications. Recently, I examined hybrid classical-quantum compute systems in a paper authored by Muhammad Nufail Farooqi and Martin Ruefenacht from the Leibniz Supercomputing Centre in Germany .I want to emphasize that this summary is based on a comprehensive review of the papers before being authored by me, without the use of ChatGPT or any AI tools, and I will maintain this standard for all future articles. 📄 Discover how these advancements are shaping computing paradigms and driving innovation across various sectors. Whether your interest lies in quantum computing or emerging technologies, this summary provides valuable insights. https://qr.ae/psdjeO Join the discussion on Quora to learn more about my written work on Science, Computer Science, Artificial Intelligence, Space Science, Simulations, Statistics, Research, Machine Learning, Neural Networks, Math, Physics, Chemistry, and Nanotechnology! #EngineeringIdeas #Quora #CuttingEdgeResearch #TechInnovation #Technology #QuantumComputing #ComputerScience #Nanotechnology #ArtificialIntelligence #SpaceScience #Simulations #Statistics #MachineLearning #NeuralNetworks #Physics #Chemistry #Science #OpenSource #TechSummaries #ScientificBreakthroughs

We encourage you to read the recently published article, "Towards Scalable Digital Modeling of Networks of Biorealistic Silicon Neurons." 📖 It has results in OPEN SOURCE! 📝 Authored by: Swagat Bhattacharyya; Praveen Raj Ayyappan; Jennifer O. Hasler Volume: 13, Issue: 4, December 2023 Digital implementations of biorealistic neuron circuits for network computation have a trade-off between computational efficiency and biorealism. This work introduces efficient digital approximations for coupled Hodgkin-Huxley (HH) neurons using transistor-channel neural modeling and implements these models in C with both floating-point and 32-bit fixed-point arithmetic. This approach, which has been made open-source (https://loom.ly/7u6iNY4), allows for large-scale simulation of HH-like neurons, offering a scalable solution for digital modeling and paving the way for analog computing. 🔗 Read more on IEEE Xplore: https://loom.ly/7s34jWs 📖 This article has OPEN SOURCE results! https://loom.ly/7u6iNY4 #IEEE #IEEEXplore #JETCAS #PopularArticles #ReadMore #CircuitsandSystems #graphicalabstract #ReadMore #OpenSource

Dear Connections, Excited to share that I recently published two conference papers at the IEEE 3rd IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2023 Paper 1: Faster Region-Convolutional Neural Network with ResNet50 for Video Stream Object Detection Paper 2: Enhancing Secret Image Authentication Through Encryption-Based Steganography with Reversible Watermarking

I am delighted to share that our paper, titled "Deep Reinforcement Learning Strategies for Noise-Adaptive Qubit Routing," has been published and is available on IEEE Xplore (https://lnkd.in/d9w9Gb7D). Based on the research conducted during my Master's thesis, this work explores the use of deep reinforcement learning to compile quantum algorithms more efficiently than existing heuristic approaches, helping mitigate the harmful impact of noise on computations. We specifically focus on the qubit routing problem, which consists of adapting programs to the qubit connectivity constraints of a target device by inserting additional operations. The paper was presented at the 2024 IEEE International Conference on Quantum Software (https://lnkd.in/d97WBEdY), part of the IEEE World Congress on Services (https://lnkd.in/dSrUKxpn), held in Shenzhen, China, from July 7 to 13. I thank my supervisors and co-authors, Professors João Paulo Fernandes and Rui Maranhao Abreu, for their guidance and feedback during the process. Seeing the value and significance of this line of research recognized has been incredibly gratifying, especially in the context of a field as rich and exciting as quantum computing.

Exciting News! Our paper titled “MOCAS: A Multimodal Dataset for Objective Cognitive Workload Assessment on Simultaneous Tasks” has just been published in IEEE Transactions on Affective Computing (#TAFFC)! This paper introduces #MOCAS, a multimodal dataset dedicated to human cognitive workload (CWL) assessment. MOCAS represents a valuable addition to current research in multimodal fusion CWL assessment. To our knowledge, MOCAS is the first open-access dataset to include both physiological and behavioral data, along with CWL and emotion annotations, including personal traits and background information of subjects from realistic closed-circuit television (CCTV) monitoring tasks. This increases its applicability for real-world human-robot/machine interaction scenarios. All data were collected using off-the-shelf, user-friendly sensors; thus, models built from our dataset can be easily applied in everyday applications with efficiency. Publication (IEEE Xplore): https://lnkd.in/gcWP6aBN Open-access preprint (arXiv): https://lnkd.in/gZWh_SJ4 Supplementary video: https://lnkd.in/gyd7rNJ6 Dataset: https://lnkd.in/gE3Kt3kE Kudos to all co-authors, especially the co-first authors, Wonse Jo and Ruiqi Wang! #MultimodalDataset #CognitiveWorkloadAssessment #HumanRobotTeams #HumanMachineSystems #AffectiveComputing #Purdue #PurdueSMARTLab

Artificial synapses made of H2O: The new frontier in neuromorphic computing Theoretical physicists at Utrecht University in the Netherlands and experimental physicists at Sogang University in South Korea built an artificial synapse based on a mix of water and salt. This new type of computing device uses fluidic ion channels, just like the neurons in our brains. This “neuromorphic” approach promises to be much more energy efficient than traditional computers. https://lnkd.in/e28Q2yKe

Bridging Human Minds with Computers Ray emphasizes the quest to augment human intelligence by integrating the power of computers directly with our brains. He highlights the current limitations, such as the delay in accessing information through external devices, and envisions a future where queries are instantly resolved within our minds. This concept of 'marrying' human brains with computers aims to accelerate the exchange of information, potentially revolutionizing how we interact with technology. Ray's vision reflects the ongoing pursuit of achieving the singularity, where the boundaries between human and artificial intelligence blur, opening new frontiers in human cognition and technological advancement.

My recent talk at the University of Maryland is now available online. If you’re interested in exploring algorithm-inspired quantum metrology and its fascinating intersection with analog computation, check it out! Happy to connect and chat more about the insights and questions sparked by this topic. #quantumcomputing #quantummetrology #analogcomputation #research

I am thrilled to share that my previous work with Yen Jui Chang and other fellow quantum machine learning researchers has been accepted as a poster session at the 2024 IEEE #quantum week conference #quantumai #qubo #isingmachine #rbm #quantumml