December 13 2023 (Wednesday) 4:30-5:30pm
Complex, three dimensional (3D) micro/nanostructures in biology provide sophisticated, essential functions in even the most basic forms of life. Compelling opportunities exist for analogous 3D structures in man-made devices, but existing design options are highly constrained by comparatively primitive capabilities in fabrication and growth. Recent advances in mechanical engineering and materials science provide broad access to diverse, highly engineered classes of 3D architectures, with characteristic dimensions that range from nanometers to centimeters and areas that span square centimeters or more. The approach relies on geometric transformation of preformed two dimensional (2D) precursor micro/nanostructures and/or devices into extended 3D layouts by controlled processes of substrate-induced compressive buckling, where the bonding configurations, thickness distributions and other parameters control the final configurations. This talk reviews the key concepts and focuses on the most recent developments with example applications in areas ranging from mesoscale microfluidic/electronic networks as neural interfaces, to bio-inspired microfliers as environmental sensing platforms.
TechTalk is a series of forums and dialogues given by engineering researchers of diverse academic backgrounds to share their insights on innovation-related topics.
December 13 2023 (Wednesday) 4:30-5:30pm
TechTalk – Doing the Right Thing for the Wrong Reason: How a Vision for Ubiquitous Computing Can Be Reconciled to Have Better Impact
November 27 2023 (Monday) 4:00-5:00pm
Professor Gregory Abowd have been speaking and writing about the idea of an Internet of Materials (IoM) for nearly a decade. It started as a way to rethink Mark Weiser’s vision of ubiquitous computing in a more modern context, with the same hopeful zeal that Weiser presented in his writings from the late 1980s and early 1990’s. Professor Abowd will summarize how that re-interpretation has inspired his work, and the work of a growing community, for nearly a decade. From those involved in the fundamental understanding of computation to those involved in the practical development and deployment of computation, the future seems bright. We are moving towards a world of increased ubiquity of computation. There appears to be no end in sight for the increased ubiquity of all things computational. From a technical perspective, this is wonderful. More recently, professor Abowd have been forced to think about this vision through a different lens. How we justify any new vision of a technological future must be better grounded in the human motivation and potential impact. After explaining the “successes” of IoM, he will explain why he has fallen far short of a compelling motivation. But there are more compelling motivations, having to do with health, usable security and privacy, and, most importantly, sustainability. We MUST begin questioning a lot of the assumptions on how to make, operate, and dispose of computational objects. IoM is no longer a journey for a hopeful “visionary” to play out his fanciful predictions for the future. It is a mandate to address the fundamental hazards of our current trajectory towards ubiquitous computing.
Since Heinrich Hertz developed the first antenna in 1887 to demonstrate the existence of radio waves, the antenna has become the linchpin in countless wireless systems and devices. With the increasing demand for faster wireless connectivity, rising adoption of smartphones for consumer electronics, and accelerating digitization, stringent requirements, such as wide bandwidth and compact size, are imposed on antenna technology. The magneto-electric (ME) dipole is proposed to tackle the new challenges. It has been developed for mobile communications, global navigation receivers, radars, sensors, medical imaging systems and wireless power transfer systems. Compared with conventional antennas such as dipoles, slots and microstrip antennas, the ME dipoles have many distinguished features including wide bandwidth, low cross-polarization, low back radiation and stable gain and beamwidth over the operating frequencies. An overview of the theory and applications of the ME dipoles will be presented.
TechTalk – Environmental Geomechanics: Towards a Minimised Chemical Footprint in Geo-energy Engineering
November 23 2023 (Thursday) 4:30-5:30pm
Cracking is ubiquitous in a geomaterial when it is subject to an environmental perturbation. Controlling environmentally assisted subcritical crack growth is the key enabler to a safe and active geo-energy adaptation to Climate Change, particularly in the domain of e.g., unconventional shale hydrocarbon recovery, Carbon Capture Utilisation and Storage (CCUS) and enhanced geothermal systems (EGS). The aim of these applications is commonly to achieve an enhanced permeability and injectivity in the formation by the stimulation of hydraulic fracturing. In order to maximize the effectiveness of the technique and meanwhile limit the extent of chemical footprint, a sophisticated understanding of the feedback between the mechanics of a geomaterial and the surrounding environment it is subject to is required. In this talk, modelling approaches on the effect of chemical environment on subcritical cracking in a stressed geomaterial at multiple scales and an extension to an alternative non-destructive shear stimulation will be presented.
November 13 2023 (Monday) 3:00-4:00pm
The number of colors in fluorescence microscopy is far less than the types of intracellular compartments. I will present our recent progress in super resolution imaging and deep convolutional neuronal networks to segment 15 subcellular structures. This approach bypasses the limitations of multi-color imaging, accelerates the imaging speed by one order of magnitude, and can accurately segment vesicle organelles with similar shapes and sizes. The super-resolution advantages were demonstrated in resolving the 3D anatomic nanostructures at different mitotic phases and tracking the fast dynamic interactions among nine intracellular compartments in live cell. We show transfer learning ability of our networks among different microscopes, different cell types, and even complexed system of living tissues.
November 16 2023 (Thursday) 3:00-4:00pm
Land reclamation is one of the most effective solutions to address the severe problem of land shortage. By 2023, the total reclaimed area in Hong Kong is nearly equivalent to the whole area of Hong Kong Island. In Lantau Tomorrow Vision, there will be over 1700 hectares of new reclaimed land in the next 20-30 years, in which, the shortage of fill material will be a great challenge. Dredged marine deposits as a major solid waste are a potential fill material after stabilization. Chemically, waste ashes from industry were recycled, activated, and mixed with marine deposits to serve as fill material. The other biological method is also used, in which bacteria are adapted to induce calcium carbonate in marine deposits. The environmental impact and performance of the methods are evaluated. Without using cement, these green technologies could reduce carbon emissions, contributing to carbon neutrality, and promoting green and sustainable reclamation.
November 3 2023 (Friday) 9:00am -12:30pm
This Special TechTalk is the collaborative event with Department of Mechanical Engineering, The University of Hong Kong. The theme of the symposium is about Sustainable Environment for the Greater Bay Area. Experts in this field from various universities and institutes are joined together to share their insight.
November 2 2023 (Thursday) 4-5pm
The Hong Kong Harbour Area Treatment Scheme (HATS) serves a population of over 5 million. It ensures protection of the Tsuen Wan beaches and good water quality in Victoria Harbour. In the Stonecutters Island treatment works, 300 tonnes of 10 percent sodium hypochlorite solution (6 L/s) are dosed into a river of sewage (1.8 million m3/d) every day. In actual operation it is found that most of the chlorine is actually consumed without being used for disinfection. This talk presents an engineering innovation on how to mix the small chlorine dose with the large sewage flow, resulting in up to 30 percent reduction of chlorine demand – with significant savings of chemicals and reduction of carbon footprint of 1170 tonnes/year. The technology is generally applicable to chlorine disinfection of primary effluent in many developing countries.
October 18 2023 (Wednesday) 9:35-11:05 am & October 19 2023 (Thursday) 3:00-4:40 pm
This Special TechTalk is fully supported by GPPS Hong Kong23 (Global Power & Propulsion Society). All are welcome to join two sessions of plenary lectures with the topics of Advanced Computing and Future Energy on 18th October (Wednesday) and 19th October (Thursday) respectively.
October 12 2023 (Thursday) 3-4pm
To avoid catastrophic consequences of climate change, our current carbon-emitting energy infrastructure needs to be replaced with an energy system free from atmospheric carbon emissions. The enormous scale of this energy transition requires multiple energy sources to be developed, including carbon-free wind, solar, geothermal, and nuclear as well as fossil-fuel-based systems where the carbon dioxide from the waste stream is captured and stored securely in deep subsurface geologic formations, in a technology known as Carbon Capture and Storage, or CCS. Subsurface geologic formations are also likely to be used to provide short-term storage for energy-carrying fluids like hydrogen and natural gas, making the subsurface environment critical to the energy transition. In this talk, I will discuss practical computational approaches to analyze geological storage systems as well as economic and political issues associated with CCS. I will also briefly discuss basic climate change facts, as part of a proposed general curriculum for Environmental Literacy.
September 21 2023 (Thursday) 4:30-5:30pm
Can machines sense without cameras or sensors? Computer vision allows machines to “see,” but their perception capabilities based on cameras are fundamentally limited to a specific field of view and good lighting conditions – they cannot see through any occlusions or in the dark. In this talk, I will introduce Wireless AI Perception that opens a new sense for machine perception to decipher the physical world, even in absolute darkness and through walls and obstacles. To achieve this, Wireless AI leverages ambient wireless signals for sensing and turns any Wi-Fi devices from a pure communication medium into a ubiquitous all-in-one sensing platform. We will first introduce the concepts, principles, and grand challenges of Wi-Fi sensing, and then share our unique solution of Wireless AI, which has been commercialized and deployed as real-world products, such as motion sensing, sleep monitoring, fall detection, indoor tracking, just to name a few. We foresee that Wi-Fi Sensing will enter billions of devices and millions of homes, and today is just the beginning of this revolution.
TechTalk – Simulation, Optimization and Artificial Intelligence for On-demand Ride Service Operations
September 14, 2023 (Thursday) 4:30-5:30pm
On-demand ride services or ride-sourcing services, offered by transportation network companies like Uber, Lyft and Didi, have been experiencing fast development and steadily reshaping the way people travel in the past decade. Various mathematical models and optimization algorithms, including reinforcement learning approaches, have been developed in the literature to help ride-sourcing platforms design better operational strategies to achieve higher operational efficiency. However, due to cost and reliability issues (implementing an immature algorithm for real operations may result in system turbulence), it is commonly infeasible to validate these models and train/test these optimization algorithms within real-world ride sourcing platforms. Acting as a useful test bed, a simulation platform for ride-sourcing systems will thus be very important for both researchers and industrial practitioners to conduct algorithm training/testing or model validation through trails and errors. While previous studies have established a variety of simulators for their own tasks, it lacks a fair and public platform for comparing the models/algorithms proposed by different researchers. In addition, the existing simulators still face many challenges, ranging from their closeness to real environments of ride-sourcing systems, to the completeness of different tasks they can implement. To address the challenges, we propose a novel multi-functional and open-sourced simulation platform for ride-sourcing systems, which can simulate the behaviors and movements of various agents (including drivers and passengers) on a real transportation network. It provides a few accessible portals for users to train and test various optimization algorithms, especially reinforcement learning algorithms, for a variety of tasks, including on-demand matching, idle vehicle repositioning, and dynamic pricing. Evaluated by experiments based on real-world datasets, the simulator is demonstrated to be an efficient and effective test bed for various tasks related to on-demand ride service operations.
TechTalk – Quantitative Predictive Theories through Integration of Quantum, Statistical, and Irreversible Thermodynamics
August 28, 2023 (Monday) 2-3pm
Thermodynamics is a science concerning the state of a system, whether it is stable, metastable, or unstable. Its derivatives to natural variables give fundamental physico-chemical properties of the system. It is historically divided into four categories: equilibrium thermodynamics by Gibbs, statistical thermodynamics by Gibbs and Landau, irreversible thermodynamics by Onsager and Prigogine, and quantum mechanics. The development of density function theory (DFT) enabled the quantitative prediction of properties of the ground state of a system from quantum mechanics. Their integration into predictive theories will be discussed in this presentation along with future perspectives. It will be shown that the zentropy theory combines the bottom-up DFT predictions with the revised top-down statistical thermodynamics, while the theory of cross phenomena keeps the entropy production due to irreversible processes in the combine law of thermodynamics to revise the Onsager flux equations. The zentropy theory is capable of quantitatively predicting free energy landscape, singularity and emergent divergences of properties at critical point free of parameters, while the theory of cross phenomena can predict the coefficients of internal processes between non-conjugate variables.
August 3, 2023 (Thursday) 4:30-5:30pm
Mouse embryonic stem cells (ESCs) derived from the epiblast contribute to the somatic lineages and the germline upon reintroduction to the blastocyst but are excluded from the extraembryonic tissues in the placenta that are derived from the trophectoderm (TE) and the primitive endoderm (PrE). By inhibiting signal pathways implicated in the earliest embryo development, we established cultures of mouse expanded potential stem cells (EPSCs) from individual 4-cell and 8-cell blastomeres, by direct conversion of embryonic stem cells (ESCs) and through reprogramming somatic cells. Bona fide trophoblast stem cell (TSC) lines, extra-embryonic endoderm stem (XEN) cells, and ESCs could be directly derived from EPSCs in vitro. The knowledge of mouse EPSCs has enabled the establishment of EPSCs of human, pig, bovine and additional mammalian species. EPSCs of these species share similar molecular features and developmental potentials. They are genetically and epigenetically stable, can be maintained in homogenous long-term cultures and permit efficient precision and complex genome editing. EPSCs thus provide new tools for studying normal development and open up new avenues for translational research in biotechnology, agriculture, and regenerative medicine. For example, we find that early syncytiotrophoblasts produced from human TSCs are highly susceptible to coronavirus infection. This finding has enabled the development of a new stem cell-based antiviral drug discovery technology. I will discuss our thoughts on collaborations with engineering colleagues.
Global responses to the COVID-19 pandemic have largely been suboptimal due to significant underdevelopment of infrastructure, human capital and analytics in pandemic prevention, preparedness, and response (PPR). In particular, epidemic nowcasting has been universally challenging because it requires distilling informative or actionable insights from diverse range of real-world data which are often biased. Misinterpretation, misrepresentation or otherwise misuse of these nowcasts will fuel infodemics, as we have learned to our detriment during the COVID-19 pandemic. We will discuss some lessons learned from COVID-19 and how we can strengthen pandemic PPR in the Age of Information.
TechTalk – Theoretical Concepts and Innovative Laboratory Techniques for Estimating the Effective Permeability of Rocks: Applications to the Longyou Claystone
The Longyou Caves represent an important historical site in China that has undergone periodic water level changes over several centuries. The ground water flow through the intact rock and fractures is an important factor in the geotechnical assessment of the site. The Environmental Geomechanics Laboratory at McGill University has focused on the development of innovative theoretical approaches and experimental facilities for wide range of rocks including Indiana Limestone, the Cobourg Limestone, the Vermont Granite and the Lac du Bonnet Granite, using both steady state and transient techniques. In this Teck Talk, Professor Selvadurai will present a range of experimental techniques, their theoretical interpretations that can be used to estimate of fluid transport processes through intact rocks that can be described by Darcy’s law. The theoretical and experimental techniques are used to determine the intact permeability of Longyou claystone recovered from the site.
Emerging infectious diseases, such as COVID-19 and pandemic influenza, have a significant impact on the healthcare system and the society. Rapid diagnostic tests are essential for guiding patient management and infection control measures, which lead to improvement in patient outcome and prevent outbreaks in the community and in hospitals. In recent years, fully automated testing has greatly reduced the complexity of diagnostic testing and shortened the turn-around time. Despite their potential benefits, several challenges need to be addressed. In this talk, Professor To will present the advances in rapid diagnostic testing, and will discuss about the hurdles in implementing these novel technologies in real-life settings.
By integrating sensing, memory and processing functionalities, biological nervous systems are energy and area efficient. Emulating such capabilities in artificial systems is, however, challenging and is limited by the device heterogeneity of sensing and processing cores., Here, we present a universal solution to simultaneously perform multi-modal sensing, memory and processing using organic electrochemical transistors. The device has a vertical traverse architecture and a crystalline–amorphous channel that can be selectively doped by ions to enable two reconfigurable modes: volatile receptor and non-volatile synapse. As a volatile receptor, the device is capable of multi-modal sensing, and as a non-volatile synapse, it is capable of 10-bit analogue states, low switching stochasticity and good state retention. Homogeneous integration of such devices enables functions such as conditioned reflex and real-time cardiac disease diagnose via reservoir computing, illustrating the promise for future edge AI hardware.
Biological tissues are soft, dynamic, and water-rich, while abiotic tools are typically rigid, static, and dry. These differences in physical properties have presented challenges for the development of advanced biomedical systems that require interfacing with the human body. In this presentation, I will introduce our recent work on biomimetic soft composites as a platform for engineering bio-integrated devices that can potentially bridge this gap. These synthetic materials capture important structural features of natural soft tissues and exhibit tissue-mimetic reconfigurability, robustness, and functionality, making them advantageous for constructing bio-interfaces. Soft electronic components were also integrated into the biomimetic materials platform, enabling multifunctional systems for physiological sensing and targeted stimulation. Examples of these smart biomedical tools include artificial cartilage and tendons, electroconductive hydrogels, and organ-integrated 3D electronics, which create exciting opportunities in advanced biomedicine.
TechTalk – A “Programmable” Cell Niche Engineering Platform – Multiphoton Microfabrication and Micropatterning (MMM) Technology
In native tissues, cells reside in a complex microenvironment (niche) consisting of factors including neighbor cells, soluble factors, extracellular matrices, topological and mechanical signals. Cell niche is critical in maintaining their phenotype and determining their fates and functions. Reconstituting complex cell niche factors in vitro, either individually or in combinations, in a quantitatively and spatially controllable manner, is critical for investigating the interactions between cells and their niches and hence deriving designing strategies for optimal conditions during cell culture applications and optimal scaffolds for tissue engineering applications. Our lab has developed a multiphoton microfabrication and micropatterning (MMM) technology. Here, the technical capability of the MMM platform in fabricating complex protein microstructures and micropatterns with pre-designed topological features, mechanical properties, extracellular matrix, cell interaction molecules and soluble factors, and biomedical applications including cell niche factor screening for phenotype maintenance and engineering cell niche for cell fate determination will be discussed.
Artificial Intelligence (AI) has been revolutionizing numerous fields within science and engineering, giving rise to “AI for Science” – a new paradigm for both academia and industry. In this seminar, we will explore how AI algorithms and tools empower researchers to tackle intricate scientific challenges, strengthen collaboration, and expedite the discovery process. We will also envision the future of this field in the era of cloud-native infrastructures and large language models, emphasizing the crucial role of platform engineering in nurturing the growth and development of the entire scientific community. Lastly, we will provide examples to illustrate the potential appearance of such platforms and discuss the path towards their realization.
The design of optimal auctions for revenue maximization is a central topic in Economics. Classical optimal auction theory assumes that bidders’ values are drawn from a known distribution. In reality, the source of such prior information is really past data. Cole and Roughgarden (2014) modeled past data as i.i.d. samples from the value distribution and asked: How many samples are sufficient/necessary to learn a near optimal auction? This TechTalk will introduce a unified theory that yields sample-efficient algorithms with optimal sample complexity for auctions with homogeneous goods, and state-of-the-art sample complexity for auctions with heterogeneous goods. Unlike conventional statistical learning theory which focuses on the complexity of hypothesis classes, our new theory relies on the simplicity of data distributions and a monotonicity property of these problems.
Current AI cannot provide a complete solution for robotics, although AI is a useful tool for real-world challenges that cannot be solved by traditional methods. We will discuss how AI can be applied to solve real-world problems using robotic systems developed by our team so far. Inspired by a dance partner robot developed for the Aichi Expo in 2005, a co-worker robot “PaDY” was developed for the automotive assembly process. Intention estimation was a key to these collaborative robots. AI has also led to the development of robotic applications in manufacturing, such as computer vision for bin picking, grasp planning, robot motion planning, and assembly of textureless industrial parts using visual servoing. Recent advances in AI are making it possible to tackle the manipulation of soft materials. The JC STEM Lab of Robotics for Soft Materials funded by the Hong Kong Jockey Club Charities Trust covers this new field.
The Artificial Intelligence of Things (AIoT) is the combination of Artificial intelligence (AI) with the Internet of things (IoT) to enable autonomous decision-making, data analytics, and system optimization. AIoT for smart cities allows the collection of enormous sensor data for a better understanding of the environment, human behaviors, and city operations, which leads to more efficient resource management and promotes a sustainable and healthier society. The Smart Water Auditing project aims to use IoT and machine learning to provide insights into how water is being used in the households of Hong Kong to reduce the consumption of water and raise awareness of people’s water consumption habits. Our talk will present our design workflow, IoT infrastructures, machine learning algorithms, and experimentation for water end-use disaggregation in Hong Kong.
Soils are vital for several sectors of the economy: transportation, energy, water, food security, historical heritage. Soils deteriorate over time, in response to cyclic processes (seasonal effects) and extreme events (from heatwaves to heavy rainfall). Mitigation is frequently based on intrusive and heavy engineering solutions. In this Tech Talk, Dr. Sérgio Lourenço will focus on how soil properties can be controlled or tuned as needed. Recent advances which borrow on ideas from allied fields, will be presented, from bioengineering to surfaces and interfaces. The potential of adaptable, sensing and self-healing soils as the way forward, will be discussed.
Metals usually exist in form of polycrystalline solids, in which the networks of disordered grain boundaries tend to get eliminated through grain coarsening upon heating or straining, or to transform into metastable amorphous states when the grains are small enough. This is why nano-grained structures in metals are much more unstable relative to their coarse-grained counterparts. Through experiments and molecular dynamic simulations, we recently discovered a novel metastable structure in metals with grains of few nanometers in size, namely Schwarz crystal structure. The GB-network of the metal is characterized by 3D minimal interfaces structure with a zero-mean-curvature constrained by twin boundaries. The unique structure is thermally stable against grain coarsening at temperatures close to the equilibrium melting point and exhibits a hardness in vicinity of the theoretical value. The across-boundary diffusion is so effectively suppressed that the diffusion-controlled processes such as intermetallic precipitation are inhibited. In this presentation, Professor Ke Lu will introduce the formation process, structure characteristics, and some properties of the Schwarz crystal structures in a number of pure metals and alloys.
TechTalk – Rational Approach for Seismic Analysis of Long Underground Tunnels Based on 2.5D Formulation
This lecture presents a rational procedure for the seismic analysis of underground tunnels using recorded free-field earthquakes based on the 2.5D finite/infinite element approach. The near and far fields of the half space are modeled by finite and infinite elements, respectively. Using the 1D wave theory, the nodal force and displacement on the near-field boundary are computed for each spectral frequency of the earthquake. Then, equivalent seismic forces are computed for the near-field boundary for the imposition of earthquake spectrum. By assuming the soil-tunnel system to be uniform along the tunnel axis, the 2.5D approach adopted can duly account for the wave transmission along the tunnel axis, which reduces to the 2D case for infinite transmission velocity. The horizontal and vertical components of the 1999 Chi-Chi Earthquake (TCU068) are adopted as the free-field motions in the numerical analysis. The maximal stresses and distribution patterns of the tunnel section under the P- and SV-waves are thoroughly studied by the 2.5D and 2D approaches, which should prove useful to the design of underground tunnels. Comments on the idea to extend the present approach to include the effect of overlying water, such as the case for the sites below reservoirs, rivers, or sea, will also be pointed out.
Photonic platforms with multiplexing capabilities are of profound importance for high-dimensional information processing. In this talk, Professor Nicholas X. Fang will present their recent effort on advancing scalable nanoprinting methods compatible with nanophotonic computing platforms. In the first part, Professor Nicholas X. Fang will discuss an efficient and cost-effective grayscale stencil lithography method to achieve material deposition with spatial thickness variation, for spatially resolved amplitude and phase modulation suitable for flat optics and metasurfaces. The design of stencil shadow masks and deposition strategy offers arbitrarily 2D thickness patterning with low surface roughness. The method is applied to fabricate multispectral reflective filter arrays based on lossy Fabry–Perot-type optical stacks with dielectric layers of variable thickness, which generate a wide color spectrum with high customizability. Grayscale stencil lithography offers a feasible and efficient solution to overcome the thickness-step and material limitations in fabricating spatially thickness-varying structures. In the second part, they show that selective ion doping of oxide electrolyte with electronegative metals shows promise to reproducible resistive switching that are critical for reliable hardware neuromorphic circuits. Based on density functional theory calculations, the underlying mechanism is hypothesized to be the ease of creating oxygen vacancies in the vicinity of electronegative dopants due to the capture of the associated electrons by dopant midgap states and the weakening of Al-O bonds. These oxygen vacancies and vacancy clusters also bind significantly to the dopant, thereby serving as preferential sites and building blocks in the formation of conducting paths. They validate this theory experimentally by implanting different dopants over a range of electronegativities in devices made of multiple alternating layers of alumina and WN and find superior repeatability and yield with highly electronegative metals, Au, Pt, and Pd. These devices also exhibit a gradual SET transition, enabling multibit switching that is desirable for analog computing.
It may not be an overstatement that most of us using the internet has heard of metaverse. The term ‘metaverse’ has seen to stir up global hype for business opportunities and fantasy for mankind, if not became the Oxford Word of the Year 2022 – a word reflecting the ethos, mood, or preoccupations, one that has potential of lasting cultural significance. Metaverse describes a virtual reality environment in which users interact with one another’s avatars and their surroundings in an immersive way. We are going to explore what metaverse meant for us, its fantasy and reality, and the development in the current hype. Experience of exploration and creation of the metaverse is shared and lesson learnt, and takeaway is discussed.
Micro/nanostructured materials offer significantly new opportunities for high-efficiency devices and systems for energy harvesting, conversion and storage. There is, however, a tremendous gap between the proof-of-principle demonstrations at the small scale and the intrinsically large-scale real-world energy systems and sustainable applications. In this talk, Professor Yin will give an overview of our research and, more specifically, present our recent development on how structured photonic materials address the challenge of the tremendous power hungry for space cooling and promote photosynthesis and crop yield in greenhouses.
This year MRI celebrates the 50th anniversary of P. Lauterbur’s seminal discovery paper on MR imaging published on March 16, 1973. The first human sized scanners producing ‘proof of principle’-images were based on homemade magnets with a typical field strength of ~ 0.05 Tesla. First commercial MRI machines appeared in the early 80s with field strength approaching 0.5 Tesla. Sounds familiar ? Today MRI at 0.05 and at 0.5 Tesla are back as ‘hot topics’ in the current developments. The presentation will present the ‘then and now’ of MRI and discuss opportunities from ongoing technological developments to demonstrate that these trends are not just a revival of previous work, but open up new ways into the future of MRI.
TechTalk – Understanding the Turkey-Syria Earthquakes with Methane Gas Refined Fault Theory of Tectonic Earthquakes
At 4:17 am (Turkey time), Feb. 6, 2023, a damaging Mw 7.8 (or 8.0) earthquake struck southern and central Turkey and western Syria and was followed by many aftershocks including an unusually powerful Mw 7.8 (or 7.5) that occurred at 13:24. The earthquakes caused widespread damage including collapsing of many buildings. So far over 11,000 deaths were reported. Figures were projected to rise dramatically by World Health Organization.
In this Teck Talk, Professor Yue will present his understanding of the causes of the earthquakes and the associated building collapses using his methane gas refined fault theory of tectonic earthquakes. Each earthquake involved a rapid release of highly compressed methane gas expansion energy that was previously stored in deep aperture of rock fault zone. The highly compressed gas mass can rapidly expand, rupture, penetrate, and flow from the deep fault zone to shallow ground at a speed of 3 to 1 km/s. The rapid gas flow and expansion in fault rock zone generate massive seismic waves and induce huge concentrated damage to localized grounds and buildings. The earthquake is a cooling process since the gas expansion absorbs heat and cools the surrounding materials in the ground and sky, which can cause local weather changes including the occurrence of air temperature drop-down, rainfall and/or snow.
TechTalk – Adaptable AI-enabled Robots to Create a Vibrant Society – Moonshot R&D Program in Japan –
This talk introduces our Moonshot project which is a project in the National Research and Development (R&D) program in Japan. The Moonshot program promotes high-risk, high-impact R&D aiming to achieve ambitious Moonshot Goals and solve issues facing future society such as super-aging populations. Our project is accepted under the Moonshot Goal 3: Realization of AI robots that autonomously learn, adapt to their environment, evolve in intelligence, and act alongside human beings, by 2050. Our project aims to create adaptable AI-enabled robots available in a variety of places. We are now developing a variety of assistive robots called the Robotic Nimbus which can change their shape and form according to the user’s condition, environment, and the purpose of the task, and provide appropriate assistance to encourage the user to take independent action.
Disaster response is an important area where robotics has to be applied intensively. Residents are sometimes left in rubble piles in destroyed buildings and soils in many natural disasters like earthquakes and landslides. The search-and-rescue process is slow and inefficient because of high-risk and demanding situations. This talk will introduce the achievement of research and development of serpentine robots led by the speaker. Active Scope Camera (ASC) is a soft serpentine robot that adapts its configuration to the complex shape of debris and moves by ciliary vibration drive. It was used at some disaster sites in the world. The new version of the ASC levitates and moves by adding an air-jet drive. Its vision, auditory and tactile sensing capability supports the teleoperation of its long body. Its performance was tested at first responder’s training sites and actual disasters.
Human brain can perform many tasks much better than classical electronic computers, such as face recognition, reasoning based on vague information, and learning from experience, to name a few. Recently, brain-inspired algorithms have promoted in the rapid development of artificial intelligence, however, they cannot work well in classical computers. In this talk, Dr. Can Li will present his recent works on building brain-inspired computers to fit better with brain-inspired algorithms. Those computers are based on an emerging nanoelectronics device – a memristor – which can store information and compute simultaneously, similar to synapses and neurons in our brain. The built hardware can function similar to human brains, for example, it can tolerate hardware defects, make full use of the nonlinearity of devices, learn from rare samples, and so on.
TechTalk – Non-Fourier Phonon Heat Conduction: Ballistic, Coherent, Localized, Hydrodynamic, and Divergent Modes
Beyond the Fourier diffusion theory on heat conduction, the classical size effects—the Casimir regime—caused by phonon boundary scattering is well known and extensively studied. However, over the last three decades, new regimes beyond the Fourier and the Casimir pictures of heat conduction have been demonstrated. In this talk, I will discuss different phonon heat conduction regimes, including the Knudsen regime, the hydrodynamic regime, the quantization regime, the coherence and localization regimes, and the divergence regime. The Knudsen regime expands Casimir’s picture to many other quasi-ballistic transport geometries, and is being exploited to develop phonon mean free path spectroscopy techniques. Phonon hydrodynamic transport happens when the normal scattering dominates over the resistive scattering, which is a condition difficult to satisfy and only observed at a narrow temperature range less than 20K. However, our recent experiments have observed second sound—a consequence of phonon hydrodynamic transport—at as high at 200K, while simulations point to possibility of observing hydrodynamic heat conduction even at room temperature. Quantized phonon transport was observed at very low temperatures. Signatures of coherent heat conduction, including localization, will be discussed, together with experimental evidences. Divergent thermal conductivity, implying thermal superconductors, is predicted to be possible in low-dimensional materials, although no experiments have provided conclusive evidence. These different phonon heat conduction regimes will be summarized in a regime map, demonstrating the rich phonon transport physics rivaling that of electrons.
TechTalk – (RE)-Ba-Cu-O Single Grain Bulk Superconductors with Improved Superconducting and Mechanical Properties
Extensive research has been carried out over the last three decades, in general, and over last 10 years, in particular, to produce single-grain, high-performance RE-Ba-Cu-O [(RE)BCO bulk superconductors, where RE is a rare earth element or yttrium, for a variety of high field engineering applications. Sample assemblies of bulk (RE)BCO bulk superconductors reinforced under different configurations, remarkably, have enabled trapped fields of more than 17.5 T to be achieved, which is the current world record. More recently, hybrid (RE)BCO bulk superconductors containing Ag, composite and fibre-reinforcements are being developed specifically for both conventional, static devices and more challenging engineering applications where the presence of large electromagnetic stresses has been of concern for the operation of these ceramic-like materials. This seminar will describe the key developments in the processing and properties of high-performance, state-of-the-art (RE)BCO bulk superconductors with a view to develop practical applications over the next 5 years.
The classical subjects of solid mechanics, structural mechanics and mechanics of materials have played important roles in helping develop structural and functional materials, giving rise to recent advances in nanostructured materials, biomedical materials, mechanical metamaterials, soft actuators, flexible electronics, tunable mechanochromics, regenerative mechanomedicine, etc. While these classical subjects often focus on passive access to mechanical properties of materials in existing forms, a paradigm shift, referred to as mechanomaterials, is emerging toward proactive programming of materials’ properties and functionalities during the manufacturing process by leveraging the force–geometry–property relationships. Here, we provide a couple of examples that illustrate this emerging paradigm, which include overcoming some of the long-standing or recent challenges in the developments of fatigue-resistant metals, mechanics-guided shape morphing electronics, strong and switchable adhesives, epicardial patches for the treatment of heart attack and membrane-active nanomedicine.
TechTalk – An Innovative Way of Water Resources Management for Sustainable Development: Utilization of Atmospheric Water Resources
Due to rapid population growth and climate change, there are severe spatiotemporal variations of water resources in the globe, and our society is facing serious challenges in securing sufficient water. To tackle the water shortage, we need to find other water sources. An effective and possible way is to utilize atmospheric water resources, which are the precipitable water in the atmosphere. With relatively stable temporal and spatial distribution, this part of water resources can be exploited and utilized through artificial precipitation enhancement operations which is also known as cloud seeding. In this talk, Professor Chen will introduce the situation of atmospheric water resources and the method that implements low frequency acoustic waves to stimulate and enhance precipitation. Through indoor experimental analysis and a large number of field tests, the effect has been tested. The development and utilization of atmospheric water resources would provide an innovative measure to obtain more freshwater for a certain region. He will also discuss the atmospheric water resources in the Greater Bay Area.
Substantial material resource recovery opportunities exist in the urban environment to support more sustainable urban development. However, the ability to produce safe and quality recoverable requires in-depth environmental materials studies and state-of-the-art fabrication and characterization technologies. For example, the quantitative X-ray diffraction (QXRD) technique has accurately monitored the transfer and behavior of targeted hazardous metals when being beneficially used for ceramic products in the construction industry. The work of recovering metallic lead from waste cathode ray tube (CRT) glass serves as an excellent example to reflect how environmental materials techniques assisted the development of transforming urban electronic waste into new metal resources. Lastly, the demonstration of recovering phosphorus from wastewater streams as quality slow-releasing fertilizer for agriculture applications leads to new solutions to tackle critical resource challenges with the fast-developing urban mining concept around the world.
Machine learning and deep neural networks have revolutionized various fields, most obvious examples are computer vision and natural language processing. Apart from the surging sizes of sophisticated models, an emerging trend is to go down the opposite route of deploying lightweight models on the edge (terminal or user end) for relatively simple AI tasks. This is named edge AI which is often constrained to run under restrictive compute and storage resources. In this talk, we will explore the latest theory in neural network modeling that allows the total avoidance of AI training that used to be slow, daunting or even impossible for the edge. Specifically, we will scratch the surface of the neural tangent kernel, and try to establish (well…. qualitatively) the equivalence of data and network, such that once the data are ready, the network is instantly ready, too.
Many large earth structures (e.g. slopes, dams, and artificial islands) are made up of sand or sandy soil. The stability of these structures is a major concern of the public as well as the professional. The bitter memories of the deadly slope failures in Hong Kong in 1972 remind us of the importance of proper stability evaluation. The difficulty in predicting the mechanical behavior of sand and sandy soil mainly comes from the granular nature of these materials. A sand or sandy soil is an assembly of numerous small grains of varying size, shape and even mineral composition. It can exist over a spectrum of states that corresponds to a variety of responses, ranging from fluid-like flow to solid-like strain hardening. The groundwater brings additional difficulty and uncertainty. This talk will present some results and findings yielded from our long-term research endeavor at HKU, which is aimed to advance scientific understanding of the complex behaviors of granular earth materials and thereby provide better engineering solutions. Focus will be placed on the fascinating roles played by the small constituent particles. The significance of these findings to engineering practice will be open to discussion.
Identifying cause-effect relations is a fundamental primitive in a variety of areas of science and technology. The identification of causal relations is generally accomplished through statistical trials where alternative hypotheses about the causal relations are tested against each other. Traditionally, such trials have been based on classical statistics. But while classical statistics effectively describes the behavior of macroscopic variables, it becomes inadequate at the microscopic scale, described by quantum mechanics, where a richer spectrum of causal relations is accessible. In the past years, there has been an increasing interest in the study of causal relations among quantum variables. In this talk, Professor Giulio Chiribella will show that the counterintuitive features of quantum mechanics can be turned to our advantage, providing speed-ups in the identification of causal relations. These speed-ups have applications to the design of automated quantum machines and new quantum communication protocols.
Engineers traditionally construct networks of drains and pipes to efficiently divert rainwater away from urban areas. However, such conventional approaches do not focus on addressing environmental issues caused by urbanization, such as water quality degradation and reduced groundwater recharge. Nature-based solutions (NBS) are urban rainwater management approaches that support the natural cycle of water and utilize ecosystems’ functions. Commonly used NBS include bioretention cells, porous pavements, and river hyporheic restoration measures. NBS can simultaneously provide multiple benefits in addition to rainwater quantity and quality management, such as promoting biodiversity, increasing aesthetic values, and reducing urban heat island effects. In this TechTalk, Dr. Chui will introduce some NBS and discuss the opportunities and challenges of implementing them in Hong Kong.
This TechTalk panel discussion will first brief the participants on the basic information on the exciting National Manned Space Programme Recruitment of Payloads Specialists in HKSAR. This will be followed up by panel discussion on overseas experience of payload specialists and potential aerospace experiment ideas.
More information about the programme can be found in https://www.itib.gov.hk/en/psrecruitment/.
A rapidly aging population is one of the grand challenges facing the society. It is estimated that by 2050, the global population of people aged 65 or older will reach 1.6 billion. This is a major difficulty that many elders are experiencing severe limitations in mobility and manipulability in their daily lives, resulting in tremendous social and economic challenges. This talk will discuss a User-Centric Co-Creation (UC³) approach to develop intelligent robotic systems to assist mobility and manipulability as well as prevent falls. The UC³ methodology lays down a theoretical foundation for multi-disciplinary approach to the development of personalized wearable assistive systems. It will pave a new avenue to advance the ergonomics and gerontechnology beyond current horizons.
Autonomous excavators are an essential part of the goal of “building the robots that build the world”. One unique problem in autonomous excavation is how to deal with the granular materials like soils and sands, which is seldom studied in robotics. In this talk, Dr. Pan will present his team’s recent work about how to achieve efficient manipulation of soils by optimizing the trajectory of the excavator’s bucket, and how to enable the excavator to be aware of the objects buried in the soils by using a proximity sensing mechanism based on jamming in granular materials.
Conventional mechatronic, hydraulic and pneumatic motors and actuators are used for large-scale robots from ≥10 cm to the human size. At the other, nanometric end of the length scale, nano-robots are powered by molecular motors. However, a number of applications in compact environments require robotic devices in the size range of 10 µm to 10 mm, but these are too small to be powered by the conventional mechatronic systems, and too large for molecular motors. Such a length scale ideally suits a few types of high-performance stimuli-responsive actuating materials that are emerging out of a very active research field in the past two decades, with examples including shape-memory polymers and metals, nanoporous noble metals, reactive polymers and liquid-crystal elastomers, carbon-based materials and transitional metal oxides. In addition to high actuating power densities, some of these materials also offer built-in sensory functions such as resistivity responses to mechanical, heat and humidity changes in the environment, and even energy generation capabilities. Integration of these materials and their signal flows in compact designs thus poses a novel strategy for robotics at the micro length scale. This talk will review some recent progress in this field.
The vision of “Cyber-Physical Internet (CPI)” is to establish a new paradigm for sending and receiving manufactured goods just like sending and receiving instant messages over the internet using online chatting platforms. Four innovations are critical to achieve this ultimate vision: (1) digitization architecture for entangling the flows of information and materials into one flow of cyber-physical objects for manufacturing and logistics operations; (2) network services for configuring local aera network (LAN), wide area network (WAN) and catchment area network (CAN); (3) value mechanisms to motivate and facilitate participation and collaboration between multiple stakeholders including shippers, carriers, forwarders; and (4) decision analytics for synchronized logistics planning, scheduling and execution. These innovations are based upon some fundamental breakthroughs of CPI routers and TCP/PIP protocols that are yet to be developed.
Tech Talk – Innovation of Originality for Solving Sand Shortage Crisis around the World including Hong Kong
Sand is the most exploited raw solid material in the world and used for construction of buildings, roads, railways, bridges, tunnels and beaches. It is also used to make the glass and silicon chips. The annual consumption for use in glass, concrete and construction materials has reached 50 billion tones, which is extremely high. Consequently, according to United Nations’ reports, the world is facing a shortage crisis of sand, as one of the greatest sustainability challenges of the 21st century. Such sand shortage crisis around the world has affected the use of sand in Hong Kong since Hong Kong does not produce any sand and all the sand used in Hong Kong is imported from Mainland China. In this Teck Talk, Professor Yue will present his technological innovation of originality. His innovation can solve this global sand shortage crisis. More importantly, his innovation can provide a stable supply of quality sand for construction and industry and offer new raw material resources for developing new industry in Hong Kong. Professor Yue has discovered that the local ordinary soil in Hong Kong can be converted into the materials of sand and clay. The sand is silica sand and mainly quartz mineral. The clay is mainly kaolinite mineral. Both materials can be used as the raw solid materials in construction and other industry. Professor Yue will demonstrate that his technical innovation is simple, environmental-friendly, sustainable and cost-effective and can be applied to many places around the world for producing quality sand materials.
In the past 10+ years, laser microscopy has successfully made it permeated not only in biochemistry and cell/molecular biology research, but also in numerous preclinical and clinical applications. However, our understanding of health and disease is still very limited. This lecture will introduce the latest breakthrough in laser microscopy technologies developed at HKU that can address some of these challenges. Especially these technologies can generate unprecedented views and understanding of the living biological cells. They include: capturing high-resolution motion picture of the swift-flying brain signals in a living animal; visualizing the inner workings of biological cells and organisms in 3D without killing them; and detecting rare cancer cells in millions of blood cells. Not only can these technologies impact new biological discovery (e.g. neuroscience), but also creating many new opportunities in cost-effective clinical diagnosis, especially cancer screening.
The diamond has been well known as the gem stones in jewellery market, and the same material with various atomic defects, i.e., fluorescent impurities in diamond lattice, shows unique quantum behaviors even at ambient conditions. A diamond, not just a best friend of ladies, but also the best friend of scientists. Due to their unique quantum properties, these atomic defects has been demonstrated to achieve nanometric measurement of various physical quantities such as electromagnetic fields, temperature and etc. with unprecedented precision. Here, I will firstly review the development of diamond-based science and technology, and discuss its potential applications in diverse fields. Specifically, I will introduce the on-going research activities in my group, mainly including the high figure-of-merit diamond materials synthesis, advanced quantum diamond microscope development and diamond quantum sensing in single living cells. In addition, I will also share my journey in exploring beyond academics, e.g., we apply quantum diamond microscope for authenticity identification in local jewellery industry.
Membrane separation technology is increasingly used for water and energy related applications. Pressure-driven membrane processes, such as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO), have received great attention, fueled by the increasing needs for water purification, wastewater treatment and reclamation, and seawater desalination. In parallel, many novel membranes and membrane processes are being developed. In this TechTalk, Prof. Chuyang Tang will share his personal journey in the amazing membrane world. He will highlight some of his previous and ongoing research works covering topics on water reuse, seawater desalination, resource recovery, energy production, and beyond.
Precision manipulation of various liquids is essential in many fields, including DNA analysis, proteomics, cell assay and clinical diagnosis, chemical synthesis, and drug discovery. Their divisible, sticky, and sometime infectious features impose, however, great challenges on processing them, particularly when their volume is down to nano-/subnano-liter. A blood droplet from an Ebola patient can for example infect medical workers through the skin. For diagnosis, medial workers have to crash, filter, and purify a patient’s blood sample to obtain the virus’s genetic materials. This series of operations, very often in a fluidic medium, is highly infectious. Moreover, fluids stick to surfaces, which will contaminate containers and handling tools, causing potential dangers if the medical wastes are not properly managed. In this talk, Prof. Wang shall demonstrate how a simple light or fiber touch functions as a “magic” wetting-proof hand to navigate, fuse, pinch, and cleave fluids on demand, being capable of reducing and even replacing the usage of disposable plastics in the biomedical and pharmaceutical industries.
In Hong Kong, the number of elderly citizens is estimated to rise to one third of the population, or 2.37 million, in year 2037. As they age and become more frail, the demand for formal support services (e.g., providing domestic or escort services) will increase significantly in the coming years. However, there is a severe lack of manpower to meet these needs. Some elderly-care homes reported a 70% shortage of employees. There is thus a strong need of voluntary or part-time helpers for taking care of elders.
In this talk, Prof. Cheng will introduce HINCare, a software platform that encourages mutual-help and volunteering culture in the community. HINCare uses the HIN (Heterogeneous Information Network) to recommend helpers to elders or other service recipients. The algorithms that use HINs and AI technologies for matching elders and helpers are based on our recent research results. This is the first time that HIN is used to support elderly care.
HINCare is now downloadable in Apple and Google Play Store, and has been serving more than a thousand of elders and helpers in NGOs (e.g., SKH and CSFC). The app is originally designed for elderly users, but has now expanded its services to support the Community Investment and Inclusion Fund (CIIF) and 10 NGOs engaged in teenage and family services. The system won the HKICT Award 2021, Asia Smart App Award 2020, and the HKU Faculty Knowledge Exchange Awards 2021 HKU.
In recent years, there has been a trend towards integrating small, soft and deformable structures into surgical robot systems. Target applications include endoscopy or magnetic resonance imaging (MRI)-guided intervention, where researchers take advantage of soft and flexible robots for their inherent mechanical compliance. However, these flexible robotic systems are often controlled in an open loop or with positional feedback from 3D tracking devices. Not only the real-time feedback of flexible/soft robot configuration or morphology itself is of importance, but also the robot manipulation modelling, as well as its intelligent control, become an area of interest in the field. To this end, this talk will present various robot prototypes, which attempt to resolve unmet clinical and technical challenges for image-guided intervention or surgery, either in strong magnetic field (1.5-3T) by magnetic resonance imaging (MRI) scanner or in confined anatomical space through endoscopy. Machine intelligent approaches, and also the recent advances in continuum robot design and learning-based sensing/control will also be overviewed. These robots have to incorporate with efficient mechanical transmission, thus enabling delicate mechanical force/motion transmitted from actuators to surgical tools in a long and flexible route. The ultimate goal is to provide high-performance control of robotics instruments for safe, precise and effective surgical manipulation. The speaker will not only share his research outcome, but also various difficulties in his up-and-down research journey, from R&D in university, (pre-)clinical trials in hospital, then technology transfer for clinical applications.
Living cells need to undergo significant shape changes during processes such as cell division, migration and tissue formation. Therefore, it is commonly believed that the deformability of cells is intimately related to their capability in executing different biological duties as well as the progression of diseases. In this talk, I will discuss how irreversible deformation of cells ensures proper axial extension of embryos during their development and how the plastic response of tumor cells can be used in monitoring the progression of cancer. Specifically, I will show that the presence of active intracellular/intercellular contraction will trigger the severing and re-bundling of actin filaments in cells (leading to cellular anisotropy and plasticity), elevate the internal hydrostatic pressure of embryo and eventually drive its elongation. In particular, the gradual re-alignment of F-actins must be synchronized with the development of intracellular forces for the embryo to elongate, which is then further sustained by muscle contraction-triggered plastic deformation of cells. In addition, I will also introduce a microfluidic setup developed in our lab allowing us to impose precisely controlled cyclic deformation on cells and therefore probe their plastic characteristics. Interestingly, we found that significant plastic strain can accumulate rapidly in highly invasive cancer cell lines and circulating tumor cells (CTCs) from late-stage lung cancer patients with a characteristic time of a few seconds. In comparison, very little irreversible deformation was observed in the less invasive cell lines and CTCs from early-stage lung cancer patients, highlighting the potential of using the plastic response of cells as a novel marker in future cancer prognosis and monitoring.
The conventional understanding of active volcanoes is based on the theory of hot magma (molten rock) from mantle. Although this magma theory has been widely believed in Earth Science, the prediction of volcano eruption can be incorrect. For example, the recent massive eruption of the Tonga Hunga volcano was not predicted. The devastating eruption of the Mount Ontake volcano in Japan on Sept. 27, 2014 was also not predicted and/or warned at all, consequently caused 55 fatalities, 9 missing and more than 60 injured.
In this Tech Talk, Professor Yue will present his re-understanding of active volcanoes using his methane gas theory. This methane gas theory of active volcanoes is original and can interpret all the observed phenomena associated with active volcanoes. It can be used to correctly predict and effectively reduce the occurrence of damaging volcano eruptions. It can be further used to obtain the huge amount of natural gas resources from gas chambers of active volcanoes at several kilometers below the ground rocks
Tech Talk – Unravelling the transmission of vertical outbreaks: Each drainage stack is an aerosol factory
More than 10 vertical outbreaks of COVID-19 have been observed in high-rise housing in Hong Kong. Together with the 2003 SARS Amoy Garden outbreak, these outbreaks suggest the roles of building drainage pipes in the transmission of infection, probably not limited to SARS and SARS-CoV-2. In collaboration with the Environmental Protection Department (EPD), we conducted field measurements in some of the infection venues and explore the transmission mechanisms. In this Tech talk, Professor Yuguo Li, Chair Professor of Building Environment, shall demonstrate how his proposed chimney effect explains most of these infections, how the drainage pipe was poorly ventilated, what one can do to protect our family, and what society can do to provide healthy housing.
The Managing Directors of two Health@InnoHK and AIR@InnoHK projects at the Faculty of Engineering, Professor Anderson Shum and Professor Norman C. Tien gave the Inaugural Tech Talk with the theme “Digitization” and introduced insightful research projects and their future development plan.
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 – Modeling Uncertainty of Connected Vehicle Penetration Rate: Theory and Application
September 12, 2023 (Tuesday) 4:30-5:30pm
The rapid development of communication technologies enables real-time information exchange between vehicles, thus being virtually connected. However, the full connected vehicle (CV) deployment will take a long time and may never be achievable, due to privacy, security, and willingness. Knowledge of the CV penetration rate is thus crucial for realizing numerous beneficial applications during the prolonged transition period. Although several novel models have been proposed for CV penetration rate estimation, they are solely point estimators. Direct use of these point estimators without considering their variability can lead to biased models or suboptimal solutions. To bridge this research gap, this study proposes a series of analytical models to accurately estimate the variability of CV penetration rate. Comprehensive VISSIM simulations, real-world applications, and a simple CV-based adaptive signal control scheme demonstrate the readiness of the models for use in real-world situations and the potential of the models to improve system optimizations.
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.
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.
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.
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.
Spare parts management is a vital supporting function in aviation Maintenance, Repair,and Overhaul (MRO). Spare parts intralogistics (SPI), the operational perspective of spare parts management, significantly affects performance of MRO activities. This study proposes Cyber-Physical Spare Parts Intralogistics System (CPSPIS) to address the synchronization problems associated with the SPI business process and SPI resources. The proposed system applies Internet-of-Things technologies and unified representations to provide resources and operations traceability and visibility. Further, CPSPIS contributes several services with self-X abilities for real-time synchronization throughout the SPI process. In addition, CPSPIS develops applications and visualization tools for real-time cooperation between execution and decision-making. Finally, this study conducts a real-life case study in one of the largest aviation MRO organizations in Hong Kong, and discusses the quantitative and qualitative improvements of CPSPIS.
In computer science, a graph is a network modeling objects and their unique interactions. The graph learning model is a specialized machine learning model that learns on graphs. Similar to traditional machine learning models, a well-performed graph learning model can capture the global data distribution with sufficient and unbiased training data. However, in a distributed subgraph system, most data owners only possess small amounts of the data (small subgraphs) in their local systems and can have unpredictable biases.
In this talk, the speaker will introduce this novel yet realistic setting – subgraph federated learning, which aims to let distributed data owners collaboratively train a powerful and generalized graph learning model without directly sharing their subgraphs. Towards this setting, two major techniques are proposed by the research team. (1) FedSage, which trains a GraphSage model based on FedAvg to integrate node features, link structures, and task labels on multiple local subgraphs; (2) FedSage+, which trains a missing neighbor generator along FedSage to deal with missing links across local subgraphs. Empirical results and theoretical analysis of proposed models respectively demonstrate the effectiveness and prove the generalization ability.
Stainless steel (SS) is one of the most extensively used materials in many public areas and hygiene facilities but has no inherent antimicrobial properties. Additionally, the SARS-CoV-2 exhibits strong stability on regular SS surfaces, with viable viruses detected even after three days. Undoubtedly, this has created a high possibility of virus transmission among people using these areas and facilities. Here, this talk presents the inactivation of pathogen microbes (especially the SARS-CoV-2) on SS surface by tuning the chemical composition and microstructure of regular SS. It is discovered that Pathogen viruses like H1N1 and SARS-CoV-2 exhibit good stability on the surface of pure Ag and Cu-contained SS of low Cu content, but are rapidly inactivated on the surface of pure Cu and Cu-contained SS of high Cu content. Significantly, the developed anti-pathogen SS with 20 wt% Cu can distinctly reduce 99.75% and 99.99% of viable SARS-CoV-2 on its surface within 3 and 6 h, respectively. Lift buttons made of the present anti-pathogen SS are produced using mature powder metallurgy technique, demonstrating its potential applications in public areas and fighting the transmission of SARS-CoV-2 and other pathogens via surface touching.
Tech Talk – dPRO: A Generic Performance Diagnosis and Optimization Toolkit for Expediting Distributed DNN Training
Distributed training using multiple devices (i.e., GPU servers) has been widely adopted for learning DNN models over large datasets. However, the performance of large-scale distributed training tends to be far from linear speed-up in practice. Given the complexity of distributed systems, it is challenging to identify the root cause(s) of inefficiency and exercise effective performance optimizations when unexpected low training speed occurs. To date, there exists no software tool which diagnoses performance issues and helps expedite distributed DNN training, while the training can be run using different machine learning frameworks. This paper proposes dPRO, a toolkit that includes: (1) an efficient profiler that collects runtime traces of distributed DNN training across multiple frameworks, especially fine-grained communication traces, and constructs global data flow graphs including detailed communication operations for accurate replay; (2) an optimizer that effectively identifies performance bottlenecks and explores optimization strategies (from computation, communication and memory aspects) for training acceleration. We implement dPRO on multiple deep learning frameworks (PyTorch, TensorFlow, MXNet) and representative communication schemes (AllReduce and Parameter Server architecture). Extensive experiments show that dPRO predicts performance of distributed training in various settings with<5% errors in most cases and finds optimization strategies with up to87.1%speed-up over the baselines.
Prefabricated construction is an emerging construction approach to produce prefabricated components in the off-site factory and transport them to the construction site for assembly, which provides enhanced quality, productivity, and sustainability. On-site assembly is an uncertain and complex stage in prefabrication projects, due to high variability of outside conditions, organization of multi-contractors, and geographic dispersion of activities. Information technology is adopted for the management of precast on-site assembly, such as Internet-of-Things (IoT), Cyber-Physical Internet (CPS), and cloud computing, which generate massive digital twins of construction resources and activities. This tech talk introduces a digital twin-enabled real-time synchronization system (DT-SYNC) with a robotic testbed demonstration for smart prefabricated on-site assembly. On-site resources are converted into Smart Construction Objects (SCOs) attaching with UWB and RFID devices to collect and integrate real-time nD data (e.g. identity, location, cost, and construction progress). Through smart mobile gateway, various on-site resources and activities could be real-timely interoperated with their corresponding digital twins. Cloud-based services are provided for real-time monitoring through high-fidelity virtual models, and robotic control with automatic navigations and alerts. Supported by the cyber-physical visibility and traceability provided by digital twins, a real-time synchronization model is designed to organize and coordinate operations and resources with simplicity and resilience, which guarantees that the appropriate resources are spatiotemporally allocated to the appropriate activities.
Balance ability is human’s basic physiological ability that ensures stable standing and walking. Falls are major threats to the health and independent living of the elderly. 10% of the falls in the elderly are associated with fractures, and some can lead to head injuries and deaths. A highly effective human balance sensor is invented, which can capture high-resolution dynamic pressure distribution under human feet. The variation of the pressure distribution can be used to solve the dynamics of human motion while standing on the balance sensor. The algorithms using artificial intelligence are developed to assess the risk of falling for elderly people to help them prevent falls. Furthermore, this sensor can be used to measure balance ability of athletes, such as weightlifting, golf and gymnastics. In medical diagnosis, balance ability tests can provide important information for diagnostics of neural disease. It can also be used to identify drunk driving.
Debate and scientific inquiries regarding airborne transmission of respiratory infections such as COVID-19 and influenza continue. Exposure was investigated under a face-to-face scenario, where people experience the highest risk of respiratory infection. The short-range airborne route was found to dominate exposure during close contact. Based on the fact that most of the outbreaks occurred in indoor environments, we built the link between long-range airborne transmission and short-range airborne route. Results suggest that effective environmental prevention strategies for respiratory infections require appropriate increases in the ventilation rate while maintaining a sufficiently low occupancy.
The application of stainless steel (SS) as an alternative construction material has been developing in the last decade. SS construction has an outstanding structural performance, excellent corrosion resistance, and long-term durability. Moreover, the SS construction has a relatively low maintenance cost with possibility of a longer occupancy period, and thus it promotes sustainability in the construction industry. In combination with the cold-forming technique during the fabrication process, SS structures offer additional strength and a faster construction speed. However, the available international design standards for cold-formed stainless steel (CFSS) structures have not been developed thoroughly, specifically on the strength prediction of a member under concentrated bearing loads, which causes a web crippling. Therefore, a series of laboratory testing and computational simulations were conducted in this research to evaluate the existing design standards. The reliability analysis shows that the available strength predictions in the design standards are not safely used even though they are conservative. This research proposes new strength predictions that are safe and conservative, and it can be used for an improvement of the design standards.
Diamond, the most famed of all gemstones, is unique in many ways. However, beyond the sparkle, diamonds have many unique properties for copious applications. In particular, nanoscale diamond particles, generally known as nanodiamonds (NDs), have several outstanding material qualities, offering a wide range of potential for basic science and industrial applications. The practical applications of the quantum NDs are highly dependent on obtaining a well-defined surface through cleaning. Here, this talk will first present a simple, reliable, and reproducible purification method, namely, the salt-assisted air oxidation treatment, which enables scale-up manufacturing of clean NDs. At the same time, it is discovered that NDs could work as an effective agent against oral infections. These findings will significantly enhance the scope of these little gemstones in diverse scientific and industrial fields, particularly in demanding areas such as biomedical and quantum sensing.