Theme-based Research Scheme 2023/24 (Thirteenth Round) Layman Summaries of Projects Funded

Theme 1: Understanding Diseases and Disease Prevention
Project Title: Single-Cell Multi-Omics Study of Atherosclerotic Vascular Disease: Narrowing the Gap Between Bench and Bedside
Project Coordinator: Prof Yu Huang (CityU)

Abstract

Atherosclerotic vascular disease (AVD) brings heavy social and economic burdens locally and globally. Every year, about 9,700 recorded deaths in Hong Kong and 18 million deaths in the rest of the world result from AVD. As a progressive chronic inflammatory disease, atherosclerosis has an extended asymptomatic phase until reaching the irreversible stage, which leads to heart attack and stroke. One of the key challenges in both basic and clinical research is our limited understanding of pathogenic mechanisms during plaque formation. This knowledge gap has hindered the development of early diagnosis and effective therapies. Therefore, exploring comprehensive molecular mechanisms of the initiation and progression of atherosclerosis, and identifying reliable, convenient and economical methods for atherosclerosis early detection is of paramount importance.

Atherosclerosis involves multiple organs and is closely associated with metabolic disorders. Traditional research approaches are incapable of fully understanding the complex nature of atherosclerosis. It is therefore an urgent need to develop and employ new innovative technologies to tackle these technical challenges.

Our collaborative team will employ cutting-edge single-cell multi-omics technologies to reveal biological information of individual cells in blood vessels and metabolic organs. Such information is vital in uncovering previously unrecognized cell subpopulations, molecular events, and most importantly, cell-cell and organ-organ communications involved during the development of atherosclerosis.

We have recently developed novel methods to trace the origin and destination of circulating proteins and cells. This innovative technique empowers us to identify the sources and target organs of promising biomarkers, explore the interaction between cells, tissues and organs in the process of disease, thus paving the way for the development of methods in early diagnosis and precision medicine.

We will strive to translate our new research findings into clinical applications through strategic collaboration with local hospitals and top pharmaceutical companies. We have established a proprietary high-throughput drug-seq platform to identify clinically sensitive biomarkers and effective therapeutics. We are determined and dedicated to achieving our goals and advancing cardiovascular and metabolic health in Hong Kong and beyond.


Theme 1: Understanding Diseases and Disease Prevention
Project Title: Investigation of the Immunosuppressive Microenvironment in Nasopharyngeal Carcinoma
Project Coordinator: Prof Xin-yuan Guan (HKU)

Abstract

Nasopharyngeal carcinoma (NPC) is a cancer of strategic importance in Hong Kong due to its high incidence among Southern Chinese. It is highly associated Epstein-Barr virus (EBV) latent infection. NPC recurrence and treatment resistance remain major challenges in the clinical management of NPC, where combination of immunotherapy and chemotherapy treatment has emerged as a promising strategy. However, despite the heavy infiltration of lymphocytes in tumor tissues, multiple single cell RNA sequencing studies have demonstrated immunosuppressive tumor microenvironment (TME) in NPC. The clinical experience showed that only 20-30% of NPC patients respond to PD-1/PDL-1 inhibitors. In addition, none of currently used target therapies showed impressive clinical efficacy for NPC due to lack of reliable preclinical models for drug evaluation and patient stratification. Hence, there is an unmet clinical need for developing patient-specific strategy to enhance treatment response against advanced and metastatic NPC based on a better understanding of tumor immune microenvironment (TIME). In Aim 1 of the proposal, the state-of-the-art technology multiomics and computational approaches will be deployed to elucidate NPC TIME in a single-cell spatiotemporal resolution. The association of immunosuppressive immune cell types and cell interactions and communications with treatment outcomes after immunotherapy will be further evaluated. In Aim 2, we will utilize the well-established humanized mice for functional and mechanistic investigation of the tumor-mediated immunosuppression. We will particularly focus on the mechanisms underlying the tumor-induced TIME remodeling and metabolism reprogramming for modulation of T cell functions. The main task in Aim 3 is to deploy multiomics approaches to investigate the impact of molecular subtyping and EBV on TME in association with treatment outcomes for immunotherapy and further elucidate the functional roles of EBV for epigenomic reprogramming and immunosuppression through 3D genome approaches. In Aim 4, we will develop novel NPC therapeutic interventions through pre-clinical studies of two new treatment strategies in combination with PD-1 inhibitors and evaluate the blood biomarkers for treatment responses. Our proposed research will lead to quantum leap in advancing personalized strategy and precision therapy in treatment based on accurate prediction of cancer progression and therapeutic responsiveness, as well as specific targets in individual NPC patient. These will ultimately result in major breakthroughs for saving more lives with greater efficacy, less toxicity, and lower cost.


Theme 2: Developing a Sustainable Environment
Project Title: INTACT: Intelligent Tropical-storm-resilient System for Coastal Cities
Project Coordinator: Prof Yiqing Ni (PolyU)

Abstract

Coastal cities face increasingly severe tropical-storm-related hazards, and the constant growth in these cities’ populations and climate change further intensify their vulnerability. Hong Kong, as one of the most densely populated and developed cities in the Greater Bay Area (GBA), suffered much greater economic losses during Super Typhoon Mangkhut in 2018 than other GBA cities. The envelopes and interiors of numerous skyscrapers in Hong Kong were destroyed, such that enterprises had to be closed, business operations were interrupted, and occupants displaced. Due to the limited understanding of the nature and generating mechanisms of tropical storm risks in complex urban environments across a wide range of scales in space and time, hardly any coastal city is truly prepared to mitigate tropical storm risks systematically through establishing an intelligent tropical-storm-resilient system. Without identification and management of future tropical storm risks, coastal cities could suffer irreversible damage, thereby greatly decreasing safety, quality of life, and economic vitality. Thus, there is a need for real-time tropical storm risk warning and urban-resilience assessment systems to ensure the long-term sustainability of Hong Kong and other coastal cities.

The project will elucidate tropical storm risk propagation in urban environments and establish an intelligent tropical-storm-resilient system to mitigate tropical storm hazards. In particular, the project will devise a framework that enables efficient and accurate assessment of turbulent flows from sparse measurements, and the quantification of urban-environment tropical storm risks arising from complex urban aerodynamics. No quantitative assessments of urban resilience have been performed, and the effects of newly emerging building clusters on airflows in adjacent areas have yet to be defined. The project will fill the research gap by exploiting the project team’s multi-disciplinary expertise in urban aerodynamics, climate modeling, wind engineering, fluid mechanics, structural engineering, and monitoring to establish a real-time urban typhoon risk early warning and management analysis framework and elucidate and model the underlying causes of tropical storm-generated turbulent flows and urban risks. This will result in the development of a new kind of damage mechanism involving wind pressure-windborne debris-rainwater chain effect that is specific to Hong Kong owing to densely spaced tall building clusters. Furthermore, the project will develop educational programs and policy recommendations for urban sustainability.


Theme 2: Developing a Sustainable Environment
Project Title: Digital Twin-empowered Landslide Emergency Risk Management
Project Coordinator: Prof Limin Zhang (HKUST)

Abstract

Landslides are among the most catastrophic natural hazards around the world. Of the many possible triggers, rainstorms and earthquakes have induced 85% of all fatal landslides in the past 40 years and killed over 180 000 people worldwide. As a densely populated mountainous metropolis, Hong Kong has suffered considerable human and economic losses from the 13 300 natural-terrain landslides and 8 200 manmade slope failures recorded since 1984. Thousands of landslides can be triggered by one extreme storm or strong earthquake alone: a rainstorm in June 2008 induced over 3 100 landslides in Hong Kong, wreaking havoc on multiple urban systems across the territory; the 2008 Wenchuan Earthquake triggered 200 000 co-seismic landslides and started a decades-long period of active landslide-centric geohazards in the seismic area. Amid the increasing frequency of extreme rainstorms under climate change and the enduring landslide activities triggered by strong earthquakes, new landslide emergency risk management theories and technologies are urgently needed to ensure public safety and sustainable development.

To scientifically manage landslide risks in the digital era, a joint university-government-industry project is proposed, engaging experts in geotechnical engineering, construction informatics, computer science, remote sensing, hydrology, geology, transportation, emergency management and public policy. The proposed project aims to (1) develop a digital twin of Hong Kong for sensing, simulating, and visualising landslide hazard processes and for coordinating societal responses, and (2) create a new paradigm for managing hazard emergency risks in the digital era. Three major research tasks are proposed: (i) digital twin infrastructure for slope safety, (ii) digital twin simulators of landslide processes and societal responses, and (iii) emergency risk management in the digital era. A unique city-scale physics-based, simulation-driven digital twin will be established and validated. Enhanced by this revolutionary computer graphics-based digital twin and an integrated sensing and communication network, a pioneering real-time landslide risk assessment method and novel emergency decision theory will be developed.

The slope digital twin will be of global impact: it can be extended to manage other types of hazards (e.g. earthquakes, floods and typhoons) and crises (e.g. pandemics and transport crisis) and to hazard-prone regions worldwide such as the corridor along the Sichuan-Tibet Railway. The outcomes of this project will augment the capacity of the existing slope safety systems in Hong Kong and other regions, form a new digital paradigm for managing hazard emergency risks, and drive urban governance transformation towards smart, sustainable and resilient urban development.


Theme 4: Advancing Emerging Research and Innovations Important to Hong Kong
Project Title: High-performance Collaborative Edge Computing Enabling Smart City Applications: Framework and Methodologies
Project Coordinator: Prof Jiannong Cao (PolyU)

Abstract

Emerging smart city applications such as autonomous vehicles and industrial Internet of Things (IoT) generate massive data and require low latency in processing the data. According to Cisco, 75% of these data will be generated and processed at the network edge by 2025. Edge computing is a promising technology to meet the low latency requirement by pushing data processing from remote cloud to edge nodes (edge servers, base stations, roadside units, etc.) closer to data sources. Gartner envisages that edge computing will be an essential driving force of technological revolutions and industrial transformations in the next decade. Edge computing is also the core enabling technology for the emerging Compute First Networks, which envisions the convergence of cloud, Artificial Intelligence (AI), and edge to form a ubiquitous computing platform.

However, existing edge computing projects focus on the vertical collaboration among cloud, edge, and end devices, while neglecting horizontal edge-to-edge collaborations. They suffer from unoptimized resource utilization, restricted service coverage, and uneven performance. Moreover, they lack sufficient support for application development, deployment, and maintenance, especially emerging smart city applications demanding AI services.

In this project, we propose a Collaborative Edge Computing Framework (CECF) enabling advanced smart city applications demanding ultra-low latency, large-scale deployment, and dynamic access. Targeting at the construction of future ubiquitous computing infrastructure by connecting and managing a large number of edge nodes, CECF provides new abstractions and functionalities for geo-distributed edge nodes to share compute and data resources and collaborate to perform application tasks.

We will systematically study challenging issues, propose architecture, methodologies and techniques and develop a high-performance system to address the challenging issues, including scalable resource management, resource heterogeneity, large-scale task scheduling and user-friendly application support. More specifically, we will 1) design and develop novel distributed resource management system for efficient resource sharing, 2) design high-performance task scheduling algorithm over large-scale edge nodes for efficient execution, 3) design general programming model and runtime support to achieve high-performance edge AI model training and inference. To evaluate CECF, we will implement and deploy CECF with a GIS-enabled intelligent transportation application with collaboration of our industry partners, including Hong Kong Science and Technology Park, Huawei, Alibaba, and Esri.

The uniqueness and novelty of this project lie in the strategical identification of the most critical scientific challenges and a systematic approach to developing innovative solutions, including new methods, algorithms, and a real-world testbed. This project is timely and has great potential to establish Hong Kong with a new-generation computing infrastructure. With a strong team of experienced world-leading researchers in the fields, we are highly confident this project will be a great success.


Theme 4: Advancing Emerging Research and Innovations Important to Hong Kong
Project Title: Overcoming Technical Limits of Copper Hybrid Bonding for Advanced Three-Dimensional Integrated Circuits
Project Coordinator: Prof Lain-jong Li (HKU)

Abstract

Fast development of Internet of Things (IoT) demands new-generation integrated circuits (ICs) that are smaller and cheaper, consume less power, and with more functionalities. Current ICs rely on dimension scaling (Moore’s Law) but it will hit the physical limit soon. Leading companies have alternatively pursued system optimization by vertically stacking Si chips using metal micro-bumps and through-silicon (Si) vias, known as three-dimensional (3D) packaging, to shorten inter-chip connections. To further boost up the performance, Cu hybrid bonding (directly connect Cu and dielectrics of two chips) with fine alignment is another emerging approach for manufacturing advanced 3DICs. It allows to mix-and-match different functional chips (called heterogenous integration), thereby enabling new chip architectures for high-end applications including artificial intelligence (AI), central processing units (CPU), graphics-processing units (GPU), field-programmable gate arrays (FPGA), mining processors, gaming processors, and image sensors.

The global 3DIC’s market is estimated to grow from USD 4,046M in 2016 to USD 10,477M by 2023 at a compound annual growth rate (CAGR) of 17.18%. The market is expected to grow faster if the technical limitation of Cu hybrid bond can be overcome. To realize the goal of making Hong Kong a technology center, it is critical to kick off the Cu hybrid bonding research.

The current main challenges of the Cu hybrid bonding are: (1) insufficient alignment accuracy only allows wide metals bonding (e.g., feature size for pick-and-place die-to-wafer bonding is ~ 3 to 10 μm); (2) misaligned bonding suffers reliability and low-yield issues; (3) Cu-Cu bonding requires high temperatures / forces leading to metal and dielectrics failures; and (4) non-destructive in-line detection of bonding defects is still not efficient for mass production.

The team aims at overcoming several technical limits of Cu hybrid bonding and helping Hong Kong’s re-industrialization. Major goals include (1) develop bonding alignment approaches with ~60 nm precision for advanced 3DICs; (2) develop Cu plating formulation and low thermal budget/stress bonding processes for enhancing productivity / yield / reliability; (3) develop an ultrasound array imaging method with AI learning for fast, non-destructive, and high-resolution in-line defect monitoring; and (4) demonstrate heterogenous 3D integration on Logic-memory systems, test chips provided by industries, and designed photonics-Si ICs.


Exploratory Project

Theme 1: Understanding Diseases and Disease Prevention
Project Title: Dysregulated Host - Gut Microbiota Co-Metabolism in Metabolic Associated Fatty Liver Disease
Project Coordinator: Prof Wei Jia (HKBU)

Abstract

Metabolic associated fatty liver disease (MAFLD) coexists and acts synergistically with type 2 diabetes mellitus (T2DM) to increase the risk of adverse clinical outcomes. Recently, the interactions between the host and gut microbiota in terms of metabolism have gained significant attention as a cutting-edge research area. The objective of this study is to shed light on the molecular connections between MAFLD and T2DM, specifically focusing on the perspective of host-gut microbiota interactions. By exploring these interactions, this research aims to establish Hong Kong as a leader in translational research on MAFLD and T2DM.


Theme 3: Enhancing Hong Kong’s Strategic Position as a Regional and International Business Centre
Project Title: Strengthening Hong Kong as a Global Financial Center by Enhancing the Overall Regtech Capacity of the Industry and Facilitating the Regulation and Infrastructure Design of CBDC and Digital Assets in Hong Kong
Project Coordinator: Prof Kar-yan Tam (HKUST)

Abstract

Regulation technology (Regtech) is a subset of finance technology (Fintech) focusing on technologies that facilitate the delivery of regulatory requirements. As a spillover benefit, Regtech can also boost efficiency and productivity with improved auditability and traceability. It lies at the intersection between policy, regulation, financial services, and technology, underpinning the continuing development of Hong Kong as a major global financial center. At this early stage of development, Regtech not only poses fundamental issues with deep intellectual merit, it also presents ample opportunities to translate intellectual insights into innovations and practices with societal impacts. The project has adopted a “problem-based and impact-driven” approach to define the scope, deliverables, and collaboration structure with key Regtech stakeholders in Hong Kong. Extensive consultations with regulators, government bureaus, a law enforcement agency, and the industry have guided the project’s conception and the definition of the research tasks. To advance the intellectual frontier and to address the immediate and future needs of the finance industry, the project team will focus on three key themes: (1) facilitating the holistic adoption of Regtech by the finance industry with attention to Small and Medium Licensed Firms (SMLFs), (2) enhancing data sharing within and across regulatory sectors, and (3) developing digital assets with a focus on Central Bank Digital Currency (CBDC) and the regulation of virtual asset exchange and services. These themes are interrelated and co-dependent. First, technology deliverables of the three themes can be shared among team members and with SMLFs through a common open-source platform. New algorithms and models developed from the various research tasks will be added to the platform over time. Second, behavioral and transaction data collected from the SMLFs using the platform in the first theme will provide useful inputs to the other two themes, allowing a positive feedback loop to be created. Third, policy papers and reports centered around adoption of Regtech will integrate the findings of different tasks in all three themes. Intellectual insights gained from the project will be disseminated through academic journals, conference proceedings and presentations, and also put into practice via novel prototypes, proof-of-concept systems, and reference analytical models to address the needs of the industry and regulators. Regtech in Hong Kong has reached a critical stage of development, yet the pace of this development is lagging behind that in other financial centers. The project can contribute significantly to this development by advancing the intellectual frontier of Regtech and improving the capacity of the finance industry to fully exploit the underlying value of Regtech.


Theme 4: Advancing Emerging Research and Innovations Important to Hong Kong
Project Title: Diamond-based Multi-modal Quantum Sensing of Nanomagnetism
Project Coordinator: Prof Renbao Liu (CUHK)

Abstract

Quantum sensing uses quantum features of probes to enhance the performance of detection and metrology. Since it requires the control and measurement of relatively small quantum systems and can tolerate moderate errors in the quantum state preparation, control and readout, quantum sensing is expected to have practical applications in 5 to 10 years. Diamond quantum sensors, thanks to their superb quantum coherence under ambient conditions and the stability of the material in harsh, complicated environments (such as liquid, acid, and high temperatures), offer a broad range of applications such as nano-magnetometry, nano-thermometry, bio-sensing, mechanical sensing, and navigation. They also have the capability of simultaneously measuring multiple parameters. This project will develop diamond-based multi-modal quantum sensing and apply it to address important open questions in the study of magnetization in nanomaterials, i.e., materials that have size, structure, or thickness down to a few millionths of millimeter. The study of magnetic nanomaterials is important to basic science (especially in condensed matter physics and materials science) and can lead to a broad range of applications (such as information storage, quantum memory, mechano-magnetic transducers, magnetic readout of thermal, structural, and mechanical properties of nanomaterials). However, it is extremely challenging to study nanomagnetism, due to the requirements of high sensitivity and spatial resolution on the sensors and the complications by the interplaying thermal, mechanical, magnetic and structural effects. The diamond-based multi-modal quantum sensing is particularly suitable to address these challenges in nanomagnetism.

We have formed a consortium of world-renowned experts from relevant fields to carry out this project. Our team has developed unique multi-modal Nitrogen-vacancy (NV) sensors and has made important discoveries in two-dimensional and supra-nano dual-phase materials. We will develop multi-parameter quantum sensing theories and deep learning algorithms for the extraction of signals from noisy and complicated environments and integrate the multi-modal diamond-based sensing with the imaging and manipulation capability of atomic force microscopy (AFM). The AFM will be employed to induce controllable and reversible deformation, strain, and structural transitions to study the mechano-magnetic effects in two-dimensional and nano-structured materials. High-temperature quantum sensing using rapid heating and cooling will be adopted to investigate transients of structural and magnetic transitions in nanometer-size particles. Higher-order correlations will be measured and analyzed to single out and characterize different types of magnetic fluctuations. With access to these unique and novel quantum sensing methods, we will address the key questions in nanomagnetism, including the magnetic transitions and fluctuations in two-dimensional, nano-structured, and nanoparticle magnets and their interplay with strains, structural transitions, and thermal responses. These effects are important not only for developing high-performance functional materials and devices but also for understanding quantum many-body physics.