PolyU drives impactful and collaborative interdisciplinary research, with nine projects awarded over HK$50 million by Research Grants Council

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Project Coordinator

Project Details

Spatial and High-throughput Immunopeptidomics Enabled by Integrated Microfluidics and Proteogenomics (MAP)

Prof. ZHAO Qian, Associate Professor of the Department of Applied Biology and Chemical Technology

By integrating proteomics, genomics and microfluidics, the project will enable ultra‑sensitive profiling of tumour peptides from minimal samples, thereby reducing tissue use and allowing parallel personalised analysis. The proposed technology will be applied to spatial immunopeptidomics for mapping immune peptides and cell niches, as well as high‑throughput immunopeptide profiling of glioblastoma to uncover tumour neoantigens. These outcomes will deepen understanding of tumour‑immune interactions and identify new targets for advancing cancer immunotherapy.

Towards Life-Cycle Intelligent Predictive Maintenance for Railway Tracks: Advancing with Deep Learning Algorithms and Digital Twin Technology

Prof. DONG You, Associate Professor of the Department of Civil and Environmental Engineering

This project will advance intelligent railway maintenance through the development of a collaborative health-monitoring and robotic system that integrates ultrasonic guided waves, vision systems, VLA (vision–language–action) models, and artificial intelligence (AI), together with the creation of a performance‑oriented life‑cycle management framework. A dynamic digital twin will combine real‑time data with AI models to enable predictive maintenance, reduce disruptions and extend service life, thereby delivering transformative impacts for modern rail systems and transportation globally.

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Project Coordinator

Project Details

Collaborative Research Project Grant

AIoT-powered Multi-modality Underwater SOS System

Prof. ZHENG Yuanqing

Associate Professor of the Department of Computing

(Collaborating universities: CityUHK, HKUST)

The project will develop an innovative communication channel enabling swimmers to send SOS signals via waterproof smartwatches. By integrating multi-modal sensor data, such as motion and biosensors, along with hydrophones and cameras, this system strengthens situational awareness, improves detection rates and localisation accuracy, and empowers lifeguards to respond swiftly to potential drowning incidents.

Privacy Infrastructure Design for Web3

Prof. XIAO Bin

Professor of the Department of Computing

(Collaborating universities: CUHK, HKUST)

The project will pioneer user‑centric blockchain systems for secure data sharing and analytics. Fundamentally redefining data sovereignty in decentralised networks, it empowers users to retain full control while enabling reliable verification without exposing sensitive information. The research aims to rebuild digital trust, making privacy invisible yet unbreakable, and ensuring fraud prevention and effective regulatory enforcement.

Endothelins in mechanoaging and osteoarthritis: biomarker discovery and drug development

Prof. WEN Chunyi
Associate Professor of the Department of Biomedical Engineering

(Collaborating universities: CUHK, HKU)

The project aims to deepen understanding of osteoarthritis (OA) molecular endotypes and theratypes to advance novel disease‑modifying drug discovery. With the team’s recent breakthrough in identifying endothelin as one of the most upregulated genes in injured murine cartilage, this project explores endothelins as novel biomarkers of joint mechanoaging and investigates endothelin receptor targeting as a promising senotherapeutic strategy for OA.

Collaborative Research Equipment Grant

Advanced Single-Particle Mass Spectrometer to Uncover Hidden Aerosol Complexity Impacting Health and Climate

Prof. JIN Ling

Assistant Professor of the Department of Civil and Environmental Engineering and the Department of Health Technology and Informatics

(Collaborating universities: CityUHK, HKBU, CUHK, HKUST)

This project aims to develop a single‑particle mass spectrometry platform to precisely reveal the mixing state of aerosols at single‑particle resolution. It will generate new insights into how hazardous aerosol components influence health, toxicity, and climate impacts, addressing critical gaps left by conventional techniques and supporting more accurate predictions for policymaking.

A trimodal PET/SPECT/CT animal imaging system for molecular imaging and radiopharmaceutical research

Prof. YOO Jung Sun

Associate Professor of the Department of Health Technology and Informatics

(Collaborating universities: CityUHK, HKU)

This project aims to establish Hong Kong’s first nuclear molecular imaging facility by acquiring a trimodal PET/SPECT/CT animal imager. It will accelerate new drug development through real‑time monitoring of biodistribution, pharmacokinetics, and pharmacodynamics, while serving as an indispensable tool to study in vivo whole‑body cellular and biochemical dynamics in impactful biomedical research.

Young Collaborative Research Grant

Smart Environment Engineering via Beyond Diagonal Reconfigurable Intelligent Surface for Future Wireless Networks

Prof. ZHANG Shuowen

Assistant Professor of the Department of Electrical and Electronic Engineering

(Collaborating universities: CityUHK, CUHK)

This project aims to advance BD‑RIS technology for the future wireless networks. It will characterize data rate limits, devise efficient channel state information acquisition schemes, and develop novel wireless sensing strategies, paving the way for large‑scale deployment of BD‑RIS in future networks. This will deliver enhanced wireless service at low cost and help narrow the “digital divide”.

Digital Solutions to Manage the Risks of Electric Vehicle Batteries and A Deep Learning Based Index Insurance Contract Design

Prof. WANG Qin
Associate Professor of the Department of Electrical and Electronic Engineering

(Collaborating universities: HKUST, HKU)

This project aims to develop innovative digital solutions for assessing electric vehicle (EV) battery health without disassembly and to design deep learning‑based index insurance contracts. It will create AI‑powered diagnostic platforms, risk evaluation models, and insurance tools that enhance battery management, optimise EV operations, and support sustainable, risk‑averse adoption of EV technologies.