Seminar

Zoom Link: https://hku.zoom.us/j/9706928305?omn=95929409545 Abstract Accurate fabric alignment is essential in garment manufacturing, yet remains a challenging and labor-intensive task. This work presents a novel automated fabric alignment system that integrates a vision-guided robotic platform and a new Global Local Weighted Iterative Closest Point (GLW-ICP) algorithm. The system estimates the pose of wrinkle-free fabric panels—even under […]

Zoom Link:  https://hku.zoom.us/j/94531714904 Abstract The rapid proliferation of AI applications in the 6G era calls for efficient support of edge intelligence, where models must be cached and executed at the network edge to deliver low-latency inference services. Unlike cloud data centers with abundant resources, edge servers are constrained in both storage and computation, creating new […]

Zoom Link: https://hku.zoom.us/j/94531714904 Abstract The next-generation mobile network aims to natively support distributed intelligence, such as federated learning, across massive wireless edge devices. Unfortunately, in the era of large models, the deployment of federated learning faces significant obstacles due to the limited resources on edge devices. In this talk, I will briefly introduce split learning […]

Zoom Link: https://hku.zoom.us/j/99378601502?pwd=bKeW5GqjRbFRaQFLBmZmTBJHPSdKBf.1 Abstract Solving complex combinatorial optimization problems is a fundamental challenge that pushes conventional digital computers to their limits. While some physics-based computing approaches offer a promising alternative, many existing systems remain trapped in a hybrid digital-analog loop, burdened by slow, power-hungry iterations and data conversions. This work presents a fully integrated memristor-based […]

Zoom Link:https://hku.zoom.us/j/97594921448?pwd=0AyvpTWODP87uNjZhADkvcGRrXh3V7.1 Abstract The recently emerged movable antenna (MA) and Fluid antenna (FA) show great potential in leveraging spatial degrees of freedom for enhancing the performance of wireless systems. In future AI-embedded 6G communication networks, MA/FA has great potential to improve the quality of service of edge AI. However, resource allocation in MA/FA-aided systems faces […]

Zoom Link: https://hku.zoom.us/j/96125660975?pwd=yg6g1tnX9xobocust8dUATRUcIan5q.1 Abstract The rapid advancement of artificial intelligence has raised concerns regarding its trustworthiness, especially in terms of interpretability and robustness. Tree-based models like Random Forest and XGBoost excel in interpretability and accuracy for tabular data, but scaling them remains computationally expensive due to poor data locality and high data dependence. Previous efforts […]

Zoom Link: https://hku.zoom.us/j/8957840635?pwd=jB4IyfmX0hTbEjn9W0LVEs31VhDw0e.1&omn=97635631185 Abstract The proliferation of distributed energy resources presents significant coordination challenges due to their scale and variability. While traditional centralized methods are hindered by high communication and computational costs, resource-constrained edge devices struggle with conventional algorithms. This paper aims to bridge this gap by developing lightweight learning approaches for edge devices, enabling […]

Zoom Link: https://hku.zoom.us/j/93194207095?pwd=se5Jt0b8jIM7nz3yy9YZdNrWJIm818.1 Abstract This seminar introduces two complementary pruning strategies implemented directly on RRAM-based compute-in-memory hardware. The first approach uses the intrinsic randomness of analog RRAM electroforming to build an over-parameterized random-weight network, where edge pruning selects an efficient sub-network without requiring precise conductance tuning. This enables robust topology optimization while minimizing programming complexity. […]

Zoom Link: https://hku.zoom.us/j/99109748447?pwd=JSHjhMjma2hylEHbOCcLr3fJRCOoJq.1 Abstract This seminar presents novel solutions to tackle instability and redundancy in modern generative models. We first address the high-variance optimization challenges in Conditional Flow Matching (CFM) by introducing the Stable Velocity framework. This includes StableVM for robust training stability and StableVS, a finetuning-free accelerator that doubles sampling speed. Second, we target […]

Zoom Link: https://hku.zoom.us/j/98873959228 Abstract Accurate load forecasting is fundamental to the stability and efficiency of modern power grids. While collaborative approaches that leverage multi-party data sharing can significantly enhance forecasting accuracy, they also introduce complex challenges. Effective collaboration is often hindered by data heterogeneity across participants, critical data privacy concerns, and the lack of clear […]

Zoom Link: https://hku.zoom.us/j/94936719507?pwd=ceXhzS1htWuwj8oG0vJGQLS3JMpVwF.1 Abstract The reliable operation and strategic planning of smart grids are critically dependent on high-fidelity time series data. However, the increasing stochasticity of both energy supply and demand challenges conventional analytical methods, exacerbated by potential extreme scenarios. This research posits Generative Artificial Intelligence (AI) as a transformative approach, empowering not only the […]

Zoom Link: https://hku.zoom.us/j/92603659701 Abstract In the context of digital transformation of the energy system, how to effectively manage and quantify the uncertainty in forecasting has become a key bottleneck that restricts its reliable operation. This report will introduce our systematic work in the field of probabilistic load forecasting, dedicated to addressing this core challenge. Our […]

Zoom Link: https://hku.zoom.us/j/99852061481?pwd=QAsfylVs3cR4U1q4B4fczaBQpbyzKl.1 Abstract With the digitalization of smart grids, data becomes vital for advanced applications like load forecasting, energy management, and demand response. To unlock its full potential, the critical challenge becomes how to build a trustworthy data-sharing framework for diverse stakeholders. Blockchain stands out as a promising solution. In this report, we introduce a […]

Zoom Link: https://hku.zoom.us/j/99712347936?pwd=P2oHpewBKizDaTJNY9m4YowNQLZfaP.1 Abstract High-throughput dynamic imaging must recover fine spatial structure under rapid motion, yet no conventional sensor can fully overcome the trade-offs between spatial resolution, temporal resolution, and motion-induced degradation. Frame sensors inevitably blur fast dynamics due to global integration, while event sensors, although extremely fast and high-dynamic-range, provide only local 1-bit temporal […]

Zoom Link: https://hku.zoom.us/j/96497087839?pwd=5X1msaxhZNiH87SuzGTPgQHZILJmgi.1 Abstract Machine learning has advanced unprecedentedly, exemplified by GPT-4 and SORA. However, they cannot parallel human brains in efficiency and adaptability due to differences in signal representation, optimization, run-time reconfigurability, and hardware architecture. To address these challenges, we introduce PRIME—a pruning optimization for input-aware dynamic memristive spiking neural networks. PRIME leverages spiking […]

Zoom Link: https://hku.zoom.us/j/92646013468?pwd=lkoH511LkjLHtW43awHeBpEVnLfZ7b.1 Abstract Supervised deep learning has revolutionized computational imaging but relies heavily on vast datasets of clean, ground-truth images, which are often challenging to acquire in practice. This seminar presents a series of methods that break this dependency by embracing weakly-supervised and unsupervised learning, directly addressing the challenge of learning without clean data. […]

Zoom Link: https://hku.zoom.us/j/97481664242 Abstract The rise of wearable and implantable bioelectronics necessitates stretchable electronic devices and systems to seamlessly integrate with soft biological environments. Stretchable organic electrochemical transistors (OECTs), based on conducting polymer poly (3, 4-ethylenedioxythiophene) doped with polystyrene sulfonate (PEDOT: PSS), have emerged as a promising candidate because of their combined high stability and […]

Zoom Link: https://hku.zoom.us/j/97206601239?pwd=ZZh3WRdq0GpwIlSkVT1UP19HuJD2XQ.1 Abstract Shear wave elasticity imaging (SWEI) is a widely-used technique for quantifying the stiffness of biological tissues. Tissue stiffness varies with pathological processes, for instance, local tissue stiffening due to increased stromal density in cancer. However, there still exist some challenges in SWEI. Specifically, on the one hand, the performance of current […]

Zoom Link: https://hku.zoom.us/j/96428082165?pwd=Ra2k3v7nAa8r90G3Ntje8n6uspb3V4.1 Abstract Nitrogen Vacancy (NV) center, an optically addressable defect in diamond, has been explored as a promising sensing platform, due to its exceptional electronic spin properties at the room temperature. The widefield quantum sensing, leveraging this special property, allows for parallel readout of spatially resolved NV fluorescence, and therefore offers enormous potential […]