Young Scholar

Young Scholar TechTalk – Customizable Acoustic Metamaterials on Frequency and Spatial Dimensions

March 12 2024 (Tuesday) 4:30-5:30pm
Acoustic metamaterials are artificially designed structured ‘atoms’. Initially, scientists discovered that these meta-atoms can exhibit extraordinary properties beyond those found in natural materials, such as negative density and negative modulus, through localized resonance, which sparked significant interest in the academic community. Subsequently, it was confirmed that these unique narrow-band frequency responses can be extended to broadband impedance designs, leading directly to the emergence of absorption metamaterials and opening up large-scale applications in noise reduction. In recent years, the potential of customizable metamaterials has gradually been realized. We will present our latest works from two complementary perspectives: customized frequencies and spatial non-uniformity, which may open up new applications such as directional emission, stealth cloaking and automotive acoustics.

Young Scholar TechTalk – GRAINS: Proximity Sensing of Objects in Granular Materials

October 17, 2023 (Tuesday) 4:30-5:30pm
Proximity sensing is a method of detecting the presence of objects without making physical contact. However, this concept has not been widely explored in the context of granular materials, which are materials composed of small particles like sand or gravel. This is because granular materials have complex properties and the sensing needs to work without the aid of vision. In this presentation, I will introduce a system called GRAINS (Granular Material-Embedded Autonomous Proximity Sensing). GRAINS is designed to sense objects buried within granular materials by utilizing fundamental principles related to the behavior of granules, such as how they flow like a fluid, how they can become jammed. GRAINS uses force signals to determine the proximity of buried objects. It achieves this by analyzing force anomalies that occur when granules become jammed due to their proximity to objects. These force anomalies are learned in real-time by the system using a mathematical technique called Gaussian process regression. To capture these patterns, a probe is moved along a spiral trajectory within the granular material. The results of our experiments demonstrate that GRAINS can adaptively adjust its parameters to effectively work with different types of granules. It can perceive objects in the nearby vicinity, approximately 0.5 to 7 cm ahead, without the need for direct contact with the buried obstacles.
(project page: https://sites.google.com/view/grains2/home)

Young Scholar TechTalk – Secure and High-performance AI Serving: Protecting AI Secretes, Accelerating AI Insights

September 19, 2023 (Tuesday) 4:30-5:30pm
Driven by the remarkable success of artificial intelligence (AI) and edge computing, the deployment of well-trained private AI models on third-party edge devices for mission-critical applications has become increasingly prevalent. Safeguarding these private models on untrusted devices, while simultaneously speeding up model serving (i.e., inference) through accelerators like GPUs, has escalated in urgency.
We introduce SOTER, a new AI serving system that, for the first time, achieves both high security and high performance. Harnessing the associativity property of AI operators, SOTER presents an innovative approach—transforming computationally expensive AI operators into parameter-morphed equivalents for secure execution on untrusted but fast GPUs, and losslessly restoring inference results within trusted execution environments (TEEs) in CPUs. Experimental results on six prevalent AI models in the three most popular categories show that, even with stronger model protection, SOTER achieves comparable performance with baselines while retaining the same high accuracy as insecure AI model inference.

Young Scholar TechTalk – Chip-scale Sensing: From Classical to Quantum Regime

Miniature optoelectronic sensors which have features of convenient, reliable, economic, ultra sensitive, and capable of real-time measurement are highly desirable nowadays. However, currently reported optical and electronic sensing devices are still hindered with complex optical components and bulky equipment. Hence, we hope to further minimize the volume of the sensing system and get rid of the dependence on complex, expensive and bulky sensing components. In particular, we demonstrate a micro-scale III-nitride chip that integrates a light emitter (LED) and a photodetector (PD) together, realizing the emission and detection of signals in a single miniature chip. Thus, we have applied the device into some classical sensing, such as pressure, salinity content and cell activities sensing. Additionally, we also conduct integration on the diamond based quantum sensing system, and demonstrate a compact chip architecture (sub ~mm3 volume) being capable of on-chip quantum sensing.

Young Scholar TechTalk – HOF2 – Interact with Device through Simple and Robust Hand-Over-Face Gesture

Mobile devices have been like an extended part of ourselves, but can we really operate a mobile device just as naturally as how we control our fingers or body? We present HOF2, a novel input modality that uses simple gestures over your face to interact with your device. Unlike other gesture-based modalities, HOF2 is highly robust and can avoid false triggering caused by many unconscious gestures like scratching or wiping, while is still easy, comfortable and natural to use. Moreover, HOF2 is highly available and can be implemented on any mobile phone/tablet/computer with a single camera and without remote servers. In this TechTalk, we will present a live demo on iOS/iPadOS demonstrating the performance of HOF2 scheme in practice and explore some real-life use cases such as virtual conferencing, selfie, or TV controller. We believe there are far more possibilities waiting to be explored with this novel interaction scheme.

Young Scholar TechTalk – High-throughput Cell Mechanics Characterization with Microfluidics

Cells can sense mechanical stimuli and convert them to biochemical signals for various specific cellular responses, such as stem cells differentiation, initiation of transcriptional programs, and cell migration. Cell mechanics focuses on the mechanical properties and behaviours of living cells and how cell mechanics relates to various cell functions. Currently, traditional cell mechanics measurement methods are cumbersome, low-throughput, and expensive to deploy. By exploiting microfluidic technology, Dr. Johnson Cui is investigating the cancer cell mechanics and developing an accurate, easy-to-use cell mechanics measurement platform for cell mechanics research and also for cancer diagnosis and therapeutics in the future.

Young Scholar TechTalk – Learning to Control and Coordinate Hybrid Traffic Through Robot Vehicles at Complex and Unsignalized Intersections

Intersections are essential road infrastructures for traffic in modern metropolises; however, they can also be the bottleneck of traffic flows due to traffic incidents or the absence of traffic coordination mechanisms such as traffic lights. Thus, various control and coordination mechanisms that are beyond traditional control methods have been proposed to improve the efficiency of intersection traffic. Amongst these methods, the control of foreseeable hybrid traffic that consists of human-driven vehicles (HVs) and robot vehicles (RVs) has recently emerged. We propose a decentralized reinforcement learning approach for the control and coordination of hybrid traffic at real-world, complex intersections–a topic that has not been previously explored. Comprehensive experiments are conducted to show the effectiveness of our approach. We show that using 5% RVs, we can prevent congestion formation inside the intersection under the actual traffic demand of 700 vehicles per hour. When there exist more than 50% RVs in traffic, our method starts to outperform traffic signals on the average waiting time of all vehicles at the intersection.

Young Scholar TechTalk – Blowing Bubbles in Membranes for More Efficient Freshwater Production

Global scarcity and contamination of freshwater pose a significant threat to sustainable development. To address this crisis, reverse osmosis (RO) technology has been playing a pivotal role in desalination and water reuse for freshwater production. The effectiveness of the RO membrane filtration is highly dependent on its surface functional rejection layer. My research focuses on shaping this rejection layer to be a voids-bearing structure, resembling blowing bubbles within the layer. This technique will result in a thinner rejection layer with a larger surface area, favoring water transport. On this basis, shaping branch bubbles to resemble a tree or coral can potentially achieve an exponential increase in water filtration efficiency, resulting in faster production of freshwater with significantly lower energy consumption.

Young Scholar TechTalk – Understanding Rainfall-induced Slope Failures from an Integrated Perspective

Climate change increases the frequency and intensity of extreme rainfall events and magnifies the threat of rainfall-induced slope failure. The consequences of these failures can be dramatic and devastating if flow slides are triggered. While considerable efforts have been made in the past decades to understand the failure mechanisms and develop techniques to mitigate the hazards, the complexity of interplays of various factors causes it to remain an area of uncertainty and difficulty in geotechnical engineering. This talk will briefly review and discuss the main factors affecting rainfall-induced slope failures from a perspective integrating the geotechnical, hydrological, and climatological aspects. The two deadly landslides in Sau Mau Ping, Hong Kong, in June 1972 and August 1976, which caused 165 casualties, are revisited. We raise an intriguing question that has long been overlooked: why were the slopes able to withstand the 1972 rainfall but failed in the 1976 rainfall event, given that the rainfall intensity of the latter event was only half of the former. We explore the roles of geological and hydrological settings and the rainfall characteristics to look into the causes and mechanisms of these failures. Implications of the new findings for practice will also be discussed.

Young Scholar TechTalk – Flexible Learning of Quantum States with Generative Query Neural Networks

Deep neural networks are a powerful tool for the characterization of quantum states. Existing networks are typically trained with experimental data gathered from the specific quantum state that needs to be characterized. In this talk, Mr. Yan Zhu, from Department of Computer Science, will introduce a model of network that can be trained with classically simulated data from a fiducial set of states and measurements, and can later be used to characterize quantum states that share structural similarities with the states in the fiducial set. With little guidance of quantum physics, the network builds its own data-driven representation of quantum states, and then uses it to predict the outcome statistics of quantum measurements that have not been performed yet. The state representation produced by the network can also be used for tasks beyond the prediction of outcome statistics, including clustering of quantum states and identification of different phases of matter.