HKUST Secures Funding for Five Research Projects Under First RAISe+ Scheme Batch

Five projects from The Hong Kong University of Science and Technology (HKUST) were among the first batch of 24 projects awarded funding under the “Research, Academic and Industry Sectors One-plus (RAISe+) Scheme” by the Innovation and Technology Commission of the Government. The new funding will help speed up commercialization of research discoveries that benefit the society, creating a win-win outcome among industry, academic, and research sectors. These research projects, led by professors at the HKUST School of Engineering and School of Science, cover a wide range of topics, including genome-editing, cancer tumor imaging, wastewater treatment, sensing chips, and artificial intelligence robots.

In no particular order, details of the projects:

Project 1: Genome-editing Strategy for Familial Alzheimer’s Disease Therapy

A research team led by Prof. Nancy IP, President of HKUST and Director of the Hong Kong Center for Neurodegenerative Diseases (HKCeND), Prof. Amy FU, Research Professor from Division of Life Science, and Dr. Fanny IP, Chief Scientific Officer of HKCeND, has developed a novel “one-for-many” genome-editing approach for familial Alzheimer’s disease (FAD). This innovative strategy ablates the expression of the gene that carries distinct disease-causing mutations in different individuals using only a few tools, which is unfeasible with existing strategies.

This novel strategy can reduce levels of the pathological proteins that cause FAD. As a result, this approach has great potential as a long-lasting, disease-modifying treatment for FAD, which affects 2–3 million people worldwide and lacks effective treatments. It is also applicable to other familial diseases that afflict over 160 million patients worldwide. The technology will be licensed to a HKUST startup for clinical development and commercialization.

Project 2: Fast microscopic imaging to save time and medical resources 

Prof. Terence WONG, Associate Professor of the Department of Chemical and Biological Engineering at the School of Engineering, led a research team to develop an advanced artificial intelligence (AI)-based microscopic imaging system named CHAMP (Computational High-throughput Autofluorescence Microscopy by Pattern Illumination), which revolutionizes the assessment of tumor tissue during cancer surgeries. Designed to enhance surgical precision on the spot, CHAMP allows direct and high-quality cancer cell visualization rapidly, minimizing the need for repeat surgeries and offering clinical and cost-effective benefits.

CHAMP enables the detection of cancer cells in just three minutes, with an accuracy of higher than 90% — comparable to the gold standard of the one-week conventional test. This is achieved by using ultraviolet (UV) light excitation to image the surface of the tissue at a specific wavelength. The CHAMP microscope first generates a greyscale image of the patient’s tissue sample. A deep learning algorithm the team develops will then transform the greyscale image into a histological image convenient for doctors’ instant interpretation, enabling them to make sure all cancer cells have been cut in the operation. More importantly, the CHAMP technology does not require any tissue processing. Therefore, it should apply to all organ types as a platform technology. The team has generated six related US provisional invention patents so far.

Prof. Wong has founded a MedTech start-up, PhoMedics Limited, to translate his research. The current focus is on the lung and breast cancer. Other than these, the team is also conducting tests on smaller scales on the liver, colorectal, kidney, skin, and prostate. With the support of the RAISe+ scheme, the team is preparing to launch a large-scale multi-center clinical trial in five hospitals, including Queen Mary Hospital and Prince of Wales Hospital in Hong Kong, and three hospitals on the Mainland — Peking University Shenzhen Hospital, the People’s Hospital of Guangxi Zhuang Autonomous Region, and Anyang Tumor Hospital.

Project 3: Electrochemical technology for wastewater and sludge treatment 

Prof. CHEN Guanghao, Chair Professor of the Department of Civil and Environmental Engineering at the School of Engineering, led a research team that has applied two electrochemical technologies for sludge and wastewater treatment.

For sludge management, sludge from sewage treatment plants produces highly toxic hydrogen sulphide (H2S) gas with a strong odor during the treatment process, which poses a great potential hazard. LEEO® was designed to eliminate H2S gas production through electrochemical oxidation, which removes toxins and odors while costing 20% less than existing technologies.

In addition, ECO® was developed to treat organic pollutants from landfills. By combining electrochemical and photochemical processes, ECO® improves degradation efficiencies and aims to reduce carbon emissions and cut costs by half than existing technologies.

The advantages of the patented LEEO® and ECO® are their fast and reliable performance, zero chemical addition, and absence of secondary pollutants.

The team has established ElequaNova Limited with the aim to putting these technologies into action. The team actively collaborates with the Drainage Services Department and the Environmental Protection Department to launch demonstration projects.

Project 4: Smart Ubiquitous Sensors with Unlimited Potential

A research team led by Prof. George Jie YUAN, Associate Dean of Engineering (Research and Graduate Studies), and Professor of the Department of Electronic and Computer Engineering has created three families of sensing chips. The high-performance chips are designed to achieve similar or better performance compared to leading US chip makers. Improving integration level is one of the team’s main focuses. They achieve this goal by integrating all analog circuit components and digital processor into one single chip. Its smaller than average size allows it to fit into much smaller electronic gadgets and save customers’ development costs.

Established by the team to commercialize their inventions, Atom Semiconductor Technologies Limited is mass-producing the chips and has secured major customers. The chip family consists of high precision data converter, digital temperature sensor, and interactive sensor can meet the needs of different IoT electronic customers in various sectors, such as consumer, medical, industrial, and ICT markets. AtomSemi’s chips are a perfect fit for wearables, consumer electronics, industrial electronics, smart homes, and the broader IoT field. The company also got funding from venture capital firms, and the RAISe+ funding will further support the company’s development.

Project 5: AI Robotics for Precision Operations

Prof. SHEN Yajing of the Department of Electronic and Computer Engineering at the School of Engineering, led a robot research project that commercializes a high-precision, multi-dimensional, and flexible tactile sensing solution with low costs. It combines tactile sensors, tactile digital equipment, and robot dexterous operating terminals. The “Agile Executive Terminal for Robots” project uses neural network force calculation methods and patented hardware design, providing an ultra-fine digital tactile sensing solution that can improve control and accuracy, while increasing work efficiency and add value to users in different application scenarios.

This project showcases a series of three transformative flexible tactile sensors that can precisely measure the force signals of robotic fingertips from multiple directions, empowering it with sensations akin to human touch, with a wide range of technological applications. In manufacturing and assembly processes, tactile sensors help the production line automatically detect and adapt to delicate variations, enhancing efficiency and quality, and contributing to industrial automation. When tactile data analysis is combined with AI algorithm, sensory data can be analyzed and standardized to improve consistency of product texture; and robots can more accurately perceive their environment and understand human actions through, enabling safer and more natural human-machine interactions.

Besides getting government and capital investment for AgileReach Robotics, a start-up established by the team, they have already been cooperating with research institutes in Hong Kong, industrial automation production lines, medical health centers, and robot-related industries.

Dr. Shin Cheul KIM, HKUST Associate Vice-President for Research and Development (Knowledge Transfer) said, “As a research-focused University, HKUST has placed great emphasis on promoting our knowledge transfer efforts. By sharing research outcomes with industry and business sectors, HKUST aims to translate our research achievements into practical solutions that can tackle global challenges. We are honored that five HKUST projects received new funding through the RAISe+ scheme, which demonstrated the University’s research excellence and fostered further developments of these projects. We look forward to strengthening the collaborations with industry and government to jointly promote innovation to support economic development.”