Young Scholar

Young Scholar TechTalk – From Grains to Landslides: An Efficient Particle Method for Simulating Large Deformation of Geomaterials

Innovation Wing Two, TechTalk / By

May 13 2024 (Tuesday) 4:30-5:30pm
Mr Shuaihao Zhang is currently a fourth-year Ph.D. candidate in the Department of Civil Engineering at the University of Hong Kong, supervised by Professor Sérgio D.N. Lourenço. He previously obtained his B.Eng. and M.Eng. degrees from Central South University. During his Ph.D. studies, he spent one year as a visiting researcher at the School of Engineering and Design, Technical University of Munich, under the supervision of PD Dr. Xiangyu Hu. His research focuses on improving the stability and accuracy of Smoothed Particle Hydrodynamics (SPH) algorithms and applying them to simulate large deformation problems in geotechnical engineering.

Young Scholar TechTalk – Learning Out-of-Distribution Object Detectors from Foundation Models

Innovation Wing Two, TechTalk / By

September 16 2024 (Monday) 4:30-5:30pm
Out-of-distribution (OOD) object detection is a challenging task due to the absence of open-set OOD data. Inspired by recent advancements in text-to-image generative models, such as Stable Diffusion, we study the potential of generative models trained on large-scale open-set data to synthesize OOD samples, thereby enhancing OOD object detection. We introduce SyncOOD, a simple data curation method that capitalizes on the capabilities of large foundation models to automatically extract meaningful OOD data from text-to-image generative models. This offers the model access to open-world knowledge encapsulated within off-the-shelf foundation models. The synthetic OOD samples are then employed to augment the training of a lightweight, plug-and-play OOD detector, thus effectively optimizing the in-distribution (ID)/OOD decision boundaries. Extensive experiments across multiple benchmarks demonstrate that SyncOOD significantly outperforms existing methods, establishing new state-of-the-art performance with minimal synthetic data usage.

Young Scholar TechTalk – Next-generation Aqueous Magnesium-ion Batteries

Innovation Wing Two, TechTalk / By

October 8 2024 (Tuesday) 4:30-5:30pm
Aqueous magnesium batteries offer a promising alternative to lithium-ion technology due to their low cost, material abundance, safety, and comparable performance. However, magnesium metal anodes are hindered by passivation, and the narrow electrochemical stability window of aqueous electrolytes significantly limit the battery voltage. My research work introduces innovative aqueous electrolyte systems to address these challenges. A dual-electrolyte magnesium-air battery was developed, achieving a 50% higher peak power density and 46% higher open circuit voltage compared to traditional single-electrolyte systems. Subsequently, a novel water-in-salt electrolyte enabled the first rechargeable aqueous magnesium-ion battery with reversible magnesium metal anode stripping and plating behavior. Furthermore, a quasi-solid-state electrolyte was formulated to regulate ion storage at the cathode, delivering a voltage plateau of 2.6-2.0 V and a remarkable energy density of 264 Wh kg−1, nearly five times higher than current aqueous Mg-ion batteries. This work demonstrates significant advancements in aqueous magnesium batteries, offering a safe and high-performance energy storage solution for a clean energy future.

Young Scholar TechTalk – Ground Characterization from Digital Drilling Data with Time Series Algorithm

Innovation Wing Two, TechTalk / By

July 30 2024 (Tuesday) 4:30-5:30pm
Drilling a hole serves as an in-situ test for assessing geomaterial strength. Digital methods like Measurement While Drilling (MWD) and Drilling Process Monitoring (DPM) have been utilized to record drilling data for ground characterization, offering advantages in data acquisition and cost-effectiveness compared to conventional methods. However, challenges lie in addressing random variations in MWD penetration rates, leading to undesirable correlations with other investigation results. This study aims to address the research gap by analyzing digital drilling data from various projects using a time-series algorithm associated with DPM. The study includes MWD depth-series data from advanced drillholes and blastholes for safe tunnelling, instrumented boreholes for site investigation, and DPM time-series data from scientific drillholes for oil shale exploration. The reliable and accurate interpretation of digital drilling data with time-series algorithm can help MWD method become common and standard method for ground characterization in the geotechnical engineering and petroleum engineering.

Young Scholar TechTalk – Empowering Pervasive Healthcare: Mobile Analytics Systems Leveraging Multimodal Data

Innovation Wing Two, TechTalk / By

June 11 2024 (Tuesday) 4:30-5:30pm
Pervasive healthcare, also sometimes referred to as ubiquitous healthcare, is a research field that focuses on developing healthcare solutions that are seamlessly integrated into everyday life, making healthcare services available anytime and anywhere. It merges concepts from pervasive computing with health and wellness care to create solutions that are woven into the daily routines of individuals. In light of the increasing availability of diverse data sources, such as user-environment contexts and ambient sensor signals, this talk will explore the new challenges and opportunities in developing mobile analytics systems to empower pervasive healthcare. We will begin by introducing these challenges and opportunities, followed by presenting two mobile analytics systems designed for personal and public health. These systems illustrate how mobile analytics can enhance pervasive healthcare. Finally, we will discuss future directions for integrating mobile analytics into the pervasive healthcare landscape.

Young Scholar TechTalk – On Causality and the Upper Limit of Sound Absorption

Innovation Wing Two, TechTalk / By

April 30 2024 (Tuesday) 4:30-5:30pm
Sound absorption across a wide range of frequencies is a focus in contemporary acoustics. Recently, integral bounds of absorption or reflection coefficients were introduced as a guide of design optimization following the footsteps of electromagnetics, where integral relations were derived based on system causality considerations. This talk carefully examines the proper formulation of physical causality and its implications on the scattering properties of the system. Taking into consideration the effects of different physical boundary conditions and the bulk absorber material, a more generalized integral bound is derived. It becomes evident that, while the bound exists, it is governed by system stiffness rather than the causality constraint. By studying the effects of various approximations made during mathematical derivations, the physics of the bound is thoroughly discussed, and the limitations in utilizing integral bounds as reference for design optimization are highlighted. The findings are expected to have significant implications for the development of effective noise reduction strategies and the advancement of smart acoustic design.

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

Innovation Wing Two, TechTalk / By

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

Innovation Wing Two, TechTalk / By

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

Innovation Wing Two, TechTalk / By

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

Innovation Wing Two, TechTalk / By

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.