News

PAAI OpenClaw Forum at PolyU Concludes: From OPENCLAW to Future Agentic AI Systems

On 29 April 2026, the inaugural academic forum “From OPENCLAW to Future Agentic AI Systems” hosted by the PolyU Academy for Artificial Intelligence (PAAI) was successfully held at The Hong Kong Polytechnic University. Focusing on the rise of agentic AI, the forum held in-depth discussions on key topics including OPENCLAW, security and privacy, human-AI collaboration and federated AI agents, attracting many participants. The forum opened with a speech by Professor Christopher Chao, Senior Vice President (Research and Innovation) of The Hong Kong Polytechnic University. He stated that the forum marked an important milestone for PAAI since its establishment in December 2025. The newly founded Research Institute for Federated Learning will focus on data privacy, security and collaborative intelligence, and promote the development of responsible artificial intelligence. Professor Qiang Yang, Director of the PolyU Academy for Artificial Intelligence and the Research Institute for Federated Learning, delivered the keynote speech “On Future of AI and Federated AI”. He reviewed the challenges in AI development, such as data shortage, privacy leakage and multi-agent collaboration. He pointed out that federated learning and federated agents are key solutions, providing a framework for next-generation decentralised and privacy-preserving AI systems. Professor Di Jiang, Associate Director of the Research Institute for Federated Learning, gave a presentation entitled “Building Robust AI Agents with OpenClaw”. He introduced OPENCLAW in detail, including its core architecture, technical advantages and application scenarios, explained why it has grown popular rapidly, and showed its value in teaching, research and daily assistance. Professor Yang Liu, Co-Director of the Research Institute for Federated Learning, gave a presentation entitled “Federated Agents: A Future Private and Collaborative Paradigm”. She explained the federated agent technology thoroughly. She proposed this new privacy-preserving and decentralised paradigm, which keeps data and models local and realises multi-party intelligent collaboration without privacy leaks, offering a feasible path for the large-scale and secure use of agentic AI. During the industry session, Dr Christine Huang, Founder of Quantum Life and Fellow of the Royal Society of Medicine (UK), gave a talk “Longevity Claw: Full-lifecycle healthy longevity concierge”, introducing the personalised health management system built on OPENCLAW. Dr Wang Hao, Senior Research Engineer at Huawei Hong Kong Research Center (HKRC), delivered a speech “Security of Agentic AI Systems: Taming the hybrid unicorn”, focusing on AI agent security and suggesting building a trusted scaffold to balance intelligence and controllability. Dr Chen Zhitang, Senior Researcher of Huawei Noah’s Ark Lab, presented “Science Flow: A data science agent for new material design”, showing the automation and intelligentisation of material research. After the three industry talks, Professor Qiang Yang presented commemorative medals to each speaker. At the end of the forum, Professor Qiang Yang delivered the closing speech. He summarised the key outcomes and looked forward to the future development of OPENCLAW, federated agents and fully autonomous agents. He hoped academia and industry would continue to work together to drive technological breakthroughs and practical applications of agentic AI.   The forum successfully built a communication platform for academic research and industrial practice, showed the development path of agentic AI from innovation to application, and laid a solid foundation for future research and co-operation in related fields.   ******END******

PolyU and Anker Innovations establish joint laboratory to accelerate commercialisation of smart home products

[Please enter your news content, below is the sample content] he Hong Kong Polytechnic University (PolyU) will offer 90 taught postgraduate programmes in 2019/20, and is now inviting applications. Addressing the evolving needs of the society and the industries, PolyU remains committed to providing dynamic and high-quality programmes for nurturing talents to be capable of facing challenges of the times. In the coming academic year, PolyU is going to launch new programmes such as Master of Science in "Global Food Safety Management and Risk Analysis", "Accounting and Finance Analytics", and "Business Analytics". There are also programmes with restructured curriculum, such as "Industrial and Systems Engineering" and "Management and Marketing". PolyU's "Info Day for Taught Postgraduate Programmes" will be held on 12 January 2019 (Saturday) from 2pm to 6pm on PolyU campus to provide prospective applicants first-hand information and consultations on their further studies. More than 80 information seminars and consultation sessions will be organised by the eight Faculties/Schools of PolyU: Faculty of Applied Science and Textiles; Faculty of Business; Faculty of Construction and Environment; Faculty of Engineering; Faculty of Health and Social Sciences; Faculty of Humanities; School of Design; and School of Hotel and Tourism Management. For more details of the Info Day, please visit:-http://www.polyu.edu.hk/tpginfoday.

Prof. XIE Yuan delivered the PAAI Distinguished Lecture: Déjà Vu: From 3D to Chiplet and PIM/NDP — A Historical Perspective

PAAI Distinguished Lecture: Déjà Vu: From 3D to Chiplet and PIM/NDP — A Historical Perspective Date: 17 April 2026 | Time: 9:00-10:30 am | Venue: CD301, PolyU   The PolyU Academy for Artificial Intelligence (PAAI) successfully hosted a PAAI Distinguished Lecture on 17 April 2026, featuring Prof. XIE Yuan, Fang Professor of Engineering, Director of the Institute of Integrated Circuits and Systems (IICS), and Chair Professor of the Department of Electronic & Computer Engineering at The Hong Kong University of Science and Technology (HKUST).   The lecture, entitled “Déjà Vu: From 3D to Chiplet and PIM/NDP — A Historical Perspective”, attracted faculty members, researchers, and students across disciplines, and sparked active discussions on the evolution of computing architectures driven by emerging technologies.   Drawing from his extensive career spanning both academia and industry, Prof. Xie revisited key moments in the development of 3D integration, chiplet-based architectures, and Processing‑in‑Memory (PIM) / Near‑Data Processing (NDP) paradigms. Through a historical lens, he illustrated how technological advances and architectural innovation have continuously influenced each other — often in recurring patterns that resurface under new system constraints and application demands.   Prof. Xie also reflected on his own professional journey across leading institutions and organisations, including Princeton University, IBM Microelectronics, AMD Research, the University of California, Santa Barbara, Pennsylvania State University, Alibaba DAMO Academy, and T‑Head Semiconductor. His insights highlighted the importance of cross‑sector experience in shaping system‑level thinking and advancing practical, scalable solutions in modern computing systems.

Spotlight on Innovation: Prof. Yang Hongxia's Work on Democratising AI Featured by Croucher News

In a feature interview with Croucher News, Prof. Yang Hongxia, Executive Director of the PolyU Academy for Artificial Intelligence, Associate Dean (Global Engagement) of the Faculty of Computer and Mathematical Sciences, and Professor at the Department of Computing, discussed her Co-GenAI project. The initiative is designed to democratise generative AI by significantly reducing GenAI development barriers and enabling broader participation in the AI era.  Challenging the Centralised AI Paradigm Professor Yang describes the current race to build increasingly large AI models as a "rich people's game," exclusively pursued by a handful of well-funded companies. Her research at The Hong Kong Polytechnic University challenges this paradigm. She advocates for a future where multiple stakeholders collaborate to develop high-quality AI, comparing today's centralised labs to the era of mainframe computers before the rise of the personal device.   Key Technological Advances: Co-GenAI and Model Fusion Her proposed solution, Collaborative Generative AI (Co-GenAI), introduces practical innovations that significantly reduce development barriers: Advanced Model Fusion: Her team successfully fused four top-tier reasoning models using only around 160 GPU hours, a fraction of the 1-2 million GPU hours typically required to train a similar model from scratch. The resulting model achieved state-of-the-art performance, with average success rates in the mid-80% range across 11 challenging reasoning domains. Theoretical Breakthrough: Professor Yang's team is the first to theoretically derive the "Model Merging Scaling Law." This pivotal finding suggests that decentralised, collaborative approaches are not just practical but are also a feasible pathway toward more advanced AI systems, offering a viable alternative to pure centralisation. Real-World Impact: Empowering Healthcare and Beyond The research has immediate applications in specialised fields such as medicine. Co-GenAI enables hospitals to train AI models on private, high-quality data without ever sharing raw data externally. Multiple local models can then be fused to create a stronger, more knowledgeable foundation model. Enhanced Privacy, Accuracy & Efficiency: This method ensures patient data remains completely private while reducing inaccuracies common in general-purpose models. Running models locally provides millisecond-speed responses, a critical improvement over cloud-based systems for time-sensitive decisions in clinical settings. Professor Yang emphasizes that the goal is to support, not to replace, human experts: "The final decision-maker is still the doctor." A Call for Collaborative and Responsible AI Development Looking ahead, Professor Yang envisions building comprehensive "science foundation models" by integrating contributions from leading domain experts worldwide. She remains optimistic about AI's potential to revolutionize industries while advocating for smart regulation that promotes responsible use without stifling technology.   Read the full feature article on the Croucher Foundation website: Making powerful generative AI cheaper and more collaborative via https://croucher.org.hk/en/news/making-powerful-generative-ai-cheaper-and-more-collaborative 

PolyU establishes Academy for Artificial Intelligence to develop a world-class AI innovation hub

The Hong Kong Polytechnic University (PolyU) today held the PolyU Academy for Artificial Intelligence (PAAI) Inauguration, demonstrating its support to the Nation’s “Artificial Intelligence (AI) Plus” initiative under the 15th Five-Year Plan to support high-quality development across industries. Leveraging PolyU’s cross-disciplinary strengths in computer science, mathematics and data science, the PAAI strives to foster international collaboration and help position Hong Kong and the Greater Bay Area as a globally influential AI innoation hub. On the same day, PolyU hosted a series of forums, bringing together experts from around the world to advance cutting-edge AI technologies and their innovative applications in healthcare. The Inauguration took place at the PolyU Chiang Chen Studio Theatre, officiated by Prof. SUN Dong, Secretary for Innovation, Technology and Industry of the HKSAR Government of the People’s Republic of China, and Prof. Jin-Guang TENG, President of PolyU. Prof. Sun Dong remarked, “The country’s Recommendations for Formulating the 15th Five-Year Plan reaffirm Hong Kong’s strategic position as the international innovation and technology centre. Our vision to become a global hub for AI development was underscored in the 2025 Policy Address delivered by our Chief Executive, with promotion of AI being top of our agenda, taken forward through multi-pronged measures on key enablers, including talent, data and industry applications.” “The inauguration of the PAAI marks not just a milestone, but a new chapter in our city’s united efforts to expedite the AI development. This Academy will inspire ideas, foster collaboration and fuel Hong Kong's AI ecosystem,” he added. Prof. Jin-Guang Teng elaborated: “Leveraging PolyU’s strong foundation in AI, computer science, mathematics, data science and other globally recognised disciplines, the PAAI will foster interdisciplinary and international collaboration to drive AI development, positioning Hong Kong and the Greater Bay Area as a leading AI innovation hub. It will deliver sustainable, efficient and impactful solutions for key sectors – ranging from healthcare and finance to education and beyond. It will also cultivate a talent ecosystem that can drive future innovation by leveraging Hong Kong’s international research environment and its government-industry-academia-research network.” Prof. Qiang YANG, PAAI Director, and Prof. Hongxia YANG, PAAI Executive Director, delivered keynotes on “The AI Revolution: Challenges and Opportunities” and “Co-Generative AI (Co‑GenAI)” respectively, elaborating on the University’s key tasks in advancing AI and how related projects are being translated into real-world applications that benefit diverse industries. Addressing future AI challenges, Prof. Qiang Yang noted that the PAAI will continue to advance key technologies including Co‑GenAI, Federated Learning and Edge Foundation Models, while setting out robust technological roadmaps in the priority fields of healthcare, education, finance and robotics. He highlighted Hong Kong’s dual positioning as an international financial centre as well as an international innovation and technology hub. Together with the extensive clinical networks and strong industry demand in the Guangdong-Hong Kong-Macao Greater Bay Area, the PAAI will seek to expand decentralised AI infrastructure, enabling more institutions to use advanced AI technologies under safe and controllable conditions. Prof. Hongxia Yang added that traditional AI training faces hurdles such as high thresholds for computing capacity and data privacy protection. By aggregating the strengths of hundreds of industry-specific models, Co‑GenAI can reduce reliance on centralised computing resources and build high-quality foundation models that better reflect real-world application scenarios. The PAAI is working with various medical institutions to implement the “Cancer GenAI” project, while also exploring the potential of AI in infectious disease prevention and control, robotic systems and finance. In the “International Forum on AI 2025”, moderated by Prof. Qiang Yang and the “Intelligent Oncology Forum” moderated by Prof. Jing CAI, Head of the PolyU Department of Health Technology and Informatics, convened leading experts from academia and clinical medicine. Participants engaged in in-depth discussions on the deep integration of AI and healthcare, innovative applications and cross-disciplinary technological breakthroughs, contributing insights to further propel AI technologies. The PAAI will contribute to building Hong Kong into a global testing ground that drives AI innovation in healthcare and smart city development, fostering world-class technologies and talent. It will also strengthen collaboration with industry, medical institutions, schools and government departments to apply AI solutions in public health and education systems. In ShanghaiRanking’s Global Ranking of Academic Subjects announced last month, PolyU ranked first in Hong Kong and 16th worldwide in the newly introduced “Artificial Intelligence” subject area, underscoring the University’s forward-looking strategy and achievements in facilitating AI in education. Officiating the PAAI Inauguration, Prof. Sun Dong, Secretary for Innovation, Technology and Industry of the HKSAR Government of the People's Republic of China, said that the PAAI marked not just a milestone, but a new chapter in the city’s united efforts to expedite the AI development. PolyU President Prof. Jin-Guang Teng said that the PAAI would cultivate a talent ecosystem to drive future innovation by leveraging Hong Kong’s international research environment and its government-industry-academia-research network. During the media interview session, PolyU Senior Vice President (Research and Innovation) Prof. Christopher Chao (2nd from left); PAAI Director Prof. Qiang Yang (2nd from right); PAAI Executive Director Prof. Hongxia YANG (1st from left); and Prof. Jing Cai, Head of the Department of Health Technology and Informatics (1st from right), outlined the PAAI’s strategy and the development and applications of AI across industries. ***END***  

PolyU reshapes AI training paradigm, significantly reducing costs and democratising AI research

The Hong Kong Polytechnic University (PolyU) Academy for Artificial Intelligence (PAAI) has announced achieving several milestones in Generative AI (GenAI) research. The PAAI team is pushing the boundaries of AI with a novel collaborative GenAI paradigm known as Co-GenAI, which has the potential to transform frontier model training from a centralised, monolithic approach into a decentralised one. Significantly lowering training resource requirements, protecting data privacy and removing resource barriers such as graphics processing unit (GPU) monopolies paves the way for a more inclusive and accessible environment for global institutions to participate in AI research. Advances in GenAI research are presently constrained by three major barriers: training foundation models being so computationally prohibitive that only a few organisations can afford it, effectively excluding global academia from frontier model development; domain knowledge and data remaining siloed due to privacy and copyright concerns, particularly for sensitive information in healthcare and finance; and foundation models being static and unable to evolve with emerging knowledge, while retraining each frontier model ab initio consumes an enormous amount of resources and makes rapid iteration impossible. To tackle these challenges, the PAAI team has developed a novel model training framework that enables ultra-low-resource training and decentralised model fusion. The framework is theoretically grounded and has been validated through extensive real-world applications. PolyU is the first academic institution to open-source an end-to-end FP8 low-bit training solution that covers both continual pre-training (CPT) and post-training stages. This approach will set a new standard for training models with FP8 ultra-low resources while maintaining BF16 precision, in turn revolutionising the practice of model training and positioning PolyU among the few institutions worldwide to master this advanced training technique. Compared with BF16, FP8 delivers over 20% faster training, reduces peak memory by over 10% and dramatically lowers training overheads while maintaining performance. The pipeline integrates CPT, supervised fine-tuning (SFT) and reinforcement learning (RL) to achieve BF16 quality while shortening training time and reducing memory footprint. The team has begun exploring even lower-cost FP4 precision training, with initial results reported in academic publications1. In medical applications, the models trained by these pipelines outperform all peer models on diagnosis and reasoning across all key areas2. In research agent application, the models also demonstrate exceptional performance in complex task handling, generalisation and report quality3. Until now, foundation model training has followed scaling laws: more parameters yield broader knowledge and stronger performance. However, centralised training typically requires millions of GPU hours—a resource available to only a few organisations. The PolyU InfiFusion model fusion achieves a key milestone in model fusion research: it uses only hundreds of GPU hours to fuse large models that would otherwise require 1–2 million GPU hours to train from scratch. The team has merged four state-of-the-art models in 160 GPU hours4-5, avoiding million-scale training budgets while delivering fused models that significantly outperform the originals across multiple key benchmarks. The team has published the first theoretical validation of model fusion—a concept championed by Thinking Machines Lab. Through rigorous mathematical derivation, they proposed the “Model Merging Scaling Law,” suggesting there is another viable pathway to artificial general intelligence (AGI)6. Prof. YANG Hongxia, Executive Director of PolyU PAAI, Associate Dean (Global Engagement) of the Faculty of Computer and Mathematical Sciences, and Professor of the Department of Computing, stated, “Ultra-low-resource foundation model training, combined with efficient model fusion, enables academic researchers worldwide to advance GenAI research through collaborative innovation.” The team has also demonstrated the potential of its training pipelines through applications across specific domains, including state-of-the-art medical foundation and cancer AI models that achieve best-in-class performance. With the integration of high-quality domain-specific data, these models can adapt to medical devices for different scenarios, including personalised treatment and AI-based radiotherapy for oncology. In this context, the team is now collaborating with Huashan Hospital affiliated to Fudan University, Sun Yat-sen University Cancer Center, Shandong Cancer Hospital and Queen Elizabeth Hospital in Hong Kong. PAAI has also introduced a leading agentic AI application in deep search and academic paper assistance—a graduate-level academic paper writer with agentic capability that supports a multimodal patent-search engine for end-to-end research and manuscript drafting. Prof. Christopher CHAO, Senior Vice President (Research and Innovation) of PolyU, stated, “AI is a key driver in accelerating the development of new quality productive forces. The newly established PAAI is dedicated to expediting AI integration across key sectors and developing domain-specific models for diverse industries. These initiatives will not only solidify the leading position of PolyU in related fields, but also help position Hong Kong as a global hub for GenAI.” The research project led by Prof. Yang Hongxia is supported and funded by the Theme-based Research Scheme 2025/26 under the Research Grants Council, the Research, Academic and Industry Sectors One-plus Scheme under the Innovation and Technology Commission of the HKSAR Government, and the Artificial Intelligence Subsidy Scheme under Cyberport. It marks a significant step forward for Hong Kong in global AI innovation and accelerating the democratisation and industrial implementation of AI technology.   1InfiR2: A Comprehensive FP8 Training Recipe for Reasoning-Enhanced Language Models,  https://arxiv.org/html/2509.22536v3 2InfiMed: Low-Resource Medical MLLMs with Advancing Understanding and Reasoning, https://arxiv.org/html/2505.23867 3InfiAgent: Self-Evolving Pyramid Agent Framework for Infinite Scenarios, https://arxiv.org/html/2509.22502 4InfiGFusion: Graph-on-Logits Distillation via Efficient Gromov-Wasserstein for Model Fusion, https://arxiv.org/html/2505.13893 5InfiFPO: Implicit Model Fusion via Preference Optimization in Large Language Models, https://arxiv.org/abs/2505.13878 6Model Merging Scaling Laws in Large Language Models, https://arxiv.org/html/2509.24244   ***END***

Prof. Yang Qiang gave an in-depth presentation on federated learning at the ICML'25 Vision and Learning Workshop

The Vancouver Vision & Learning Workshop @ ICML 2025, jointly organized by Simon Fraser University (SFU), the University of British Columbia (UBC), and the Vector Institute, was successfully held on July 14, 2025. As a key affiliated event of the prestigious International Conference on Machine Learning (ICML 2025), the workshop brought together leading scholars and industry experts to explore cutting-edge advancements in computer vision and machine learning. Among the highlights of the event was a keynote presentation by Professor Qiang Yang, Director of the Hong Kong Polytechnic University’s PolyU Academy for Artificial Intelligence (PAAI), titled “Federated Learning meets Large Language Models.” Professor Yang's talk attracted significant attention for its in-depth exploration of federated learning—an emerging paradigm in distributed AI that enables collaborative model training across multiple devices or institutions without sharing raw data. This approach plays a pivotal role in building privacy-preserving and efficient cross-domain AI systems. Professor Yang further discussed several promising directions and applications of federated learning, including: Federated Foundation Models that integrate pre-trained large language models with domain-specific models; Agentic Federated Learning, which leverages large language models to develop intelligent edge agents; Industry Collaborations, especially in the financial sector, involving both domestic and international institutions to promote real-world applications; Scientific Research, enhancing cross-institutional collaboration through privacy-preserving AI techniques; And the development of open-source tools to support technology implementation and ecosystem growth. In addition to Professor Yang, the workshop featured insightful presentations by leading researchers including Kelsey Allen (UBC, Vector Institute), Jamie Shotton (Wayve), Masashi Sugiyama (RIKEN AIP, University of Tokyo), Alane Suhr (UC Berkeley), and Arash Vahdat (NVIDIA). Their talks covered a wide array of topics spanning vision, learning, and language, highlighting groundbreaking intersections between artificial intelligence, the physical world, and cognitive science. The workshop not only served as a high-level platform for academic exchange but also underscored the importance of cross-institutional collaboration in advancing the frontiers of AI research. These explorations continue to inject new momentum into the field and demonstrate the vast potential of interdisciplinary integration.

Prof. YANG Qiang co-authored the paper “Federated Machine Learning: Concept and Applications”, which received the Frontiers of Science Award at ICBS 2025.

The 2025 International Congress of Basic Science (ICBS) officially opened in Beijing on July 13 and will run through July 25. Since its inception in 2023 under the leadership of Academician Shing-Tung Yau, ICBS has become a premier international platform in the field of basic science. The Congress focuses on three major areas—mathematics, physics, and information science and engineering—and gathers global elites to drive disciplinary breakthroughs. This year’s event features an esteemed lineup, including Nobel, Turing, and Fields Medal laureates such as Samuel C. C. Ting and Steven Chu. Two major awards—the Lifetime Achievement Award in Basic Science and the Frontier Science Award—were presented during the Congress.   One of the highlights of this year’s event was the recognition of the paper "Federated Machine Learning: Concept and Applications," co-authored by Professor Qiang Yang (Chair Professor and Director of the Academy of Artificial Intelligence, The Hong Kong Polytechnic University), Associate Professor Yang Liu (Department of Computing and Department of Data Science and Artificial Intelligence), Dr. Tianjian Chen, and Professor Yongxin Tong. The paper was honored with the 2025 Frontier Science Award.   Professor Yang Liu accepted the award on behalf of all the authors and delivered a speech on behalf of the awardees in the field of information science and engineering. The Congress recognized the paper for “addressing the framework of federated machine learning for privacy preservation, introducing a decentralized training paradigm without data sharing, and pioneering horizontal and vertical federated learning methods. This work has tackled critical issues such as data heterogeneity and security, with wide applications in healthcare, finance, and the Internet of Things, paving new paths for integrating AI with the real economy.”   This prestigious award highlights the strong capabilities of the research team and reflects the deep academic foundation of the PolyU Academy of Artificial Intelligence (PAAI) and its Research Institute for Federated Learning (RIFL).   Federated learning is an advanced distributed AI technology that enables multiple devices to collaboratively train models without sharing raw data. By protecting data privacy, it facilitates secure and efficient cross-domain intelligent collaboration. It has become a core paradigm of privacy-preserving artificial intelligence.   Established in 2025, the PolyU Academy of Artificial Intelligence (PAAI) is co-led by Professor Qiang Yang and Professor Hongxia Yang. It focuses on developing industry-specific large language models and exploring decentralized generative AI, contributing to Hong Kong's leadership in innovation.   Under PAAI, the Research Institute for Federated Learning (RIFL) is one of the world’s first research institutes dedicated to federated learning. Co-directed by Professor Yang Liu and Professor Qiang Yang, RIFL aims to advance fundamental research and real-world applications in this cutting-edge area.   Moving forward, RIFL will continue to work closely with PAAI under the leadership of Professor Yang Liu and Professor Qiang Yang, striving to advance the global development of federated learning to new heights.

Prof. Yang Hongxia secures RGC Theme-based Research Scheme funding to develop cost-effective and sustainable Co-GenAI model

Prof. YANG Hongxia, Executive Director of the PolyU Academy for Artificial Intelligence, Associate Dean (Global Engagement) of the Faculty of Computer and Mathematical Sciences, and Professor of the Department of Computing, has received funding from the Theme-based Research Scheme 2025/26 under the Research Grants Councilfor her pioneering project, “Collaborative Generative AI (Co-GenAI)”.   Professor Wing-tak Wong, Deputy President and Provost of PolyU, remarked, “We are delighted that our scholars have received this significant recognition and support. This visionary project highlights PolyU’s strategic commitment to advancing cutting-edge AI research, with a strong emphasis on inclusivity and sustainability. The establishment of the PolyU Academy of Artificial Intelligence will further enhance interdisciplinary collaboration and open up new frontiers in AI applications.”  

PolyU secures RGC Theme-based Research Scheme funding to develop cost-effective and sustainable Co-GenAI model

The Hong Kong Polytechnic University (PolyU) is committed to driving cutting-edge research that creates societal impact and technological advancement. Prof. YANG Hongxia, Executive Director of the PolyU Academy for Artificial Intelligence, Associate Dean (Global Engagement) of the Faculty of Computer and Mathematical Sciences, and Professor of the Department of Computing, has received funding from the Theme-based Research Scheme 2025/26 under the Research Grants Councilfor her pioneering project, “Collaborative Generative AI (Co-GenAI)”. The project has been awarded total funding of HK$62.6 million, with HK$41.79 million provided by the RGC and the remaining amount matched by PolyU and other participating universities. This initiative is aimed at reshaping the landscape of GenAI through a decentralised way. The research holds significant potential to strengthen Hong Kong’s position as a global leader in GenAI development,with real-world applicationsin healthcare and technology. Prof. Christopher CHAO, PolyU Vice President (Research and Innovation), said, “We are delighted that our scholar has received this significant support. This pioneering project exemplifies the University’s commitment to advancing cutting-edge AI research, alongside our emphasis on inclusive and sustainable technological development. PolyU will continue to leverage its world-class research capabilities to make a profound impact on the future development of Hong Kong and the global community. With the launch of the PolyU Academy for Artificial Intelligence, we are poised to foster interdisciplinary collaboration and unlock new frontiers in AI applications.” The project, led by Prof. Yang Hongxia, aims to develop a novel collaborative GenAI paradigm known as Co-GenAI. The system evolves through the integration of several hundred domain-specific models to create a foundation model designed to achieve artificial general intelligence (AGI) with significantly reduced centralised computational demand. By addressing the current constraints imposed by graphics processing unit (GPU) monopolies, this innovative approach is set to democratise AI development and enable broader participation in GenAI research and deployment. Co-GenAI is tailored to enhance different domains and collaborations, with the long-term goal of creating a versatile platform for the next generation of GenAI ecosystem. The project’s key tasks include the development of domain-adaptive continual pre-training infrastructure and the design of a robust, generalisable model ranking methodology. In addition, an advanced model fusion approach will be implemented to merge heterogeneous top-ranked domain-specific models. Prof. Yang expressed her gratitude for the RGC’s support and said, “Backed by a team of world-renowned researchers with extensive expertise, we believe Co-GenAI will play a transformative role in advancing the democratisation of AI, expanding its accessibility across disciplines and enhancing cost-effectiveness. We are confident that this novel paradigm will spark greater innovation and diversity in the field, ultimately paving the way for the development of a global foundation model that is both sustainable and inclusive.” To evaluate Co-GenAI, the research team will implement and deploy the system across a wide range of applications in collaboration with industry partners including Cyberport, Hong Kong Science and Technology Park, Alibaba, and leading hospitals such as Huashan Hospital affiliated to Fudan University, Shandong Cancer Hospital, and Sun Yat-sen University Cancer Center. The RGC’s Theme-based Research Scheme aims to pool the academic research efforts of UGC-funded universities to conduct researchon topics of strategic importance to Hong Kong’s long-term development. Evaluation criteria include qualification as world-leading by international standards and the potential impact on Hong Kong.