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(Register Now) Efficient Strategies for Streamlining Deep Learning

You are cordially invited to attend the seminar by Prof. Wang Xinchao on “Efficient Strategies for Streamlining Deep Learning” with details as follows:   Date: 5 March 2026 Time: 17:00 - 18:00 Venue: HJ305, PolyU If you are interested, please register at: https://polyu.hk/IMCNN (Registration Deadline: 4 March 2026)   For enquiry, please contact us at dsai.enquiry@polyu.edu.hk. We look forward to seeing you at the seminar! Best regards, Department of Data Science and Artificial Intelligence  

(Register Now) DSAI Distinguished Seminar Series - From Brain-Inspired Computing to Brain-Inspired Embodied AI

You are cordially invited to attend the DSAI distinguished seminar by Prof. JIN Yaochu on “From Brain-Inspired Computing to Brain-Inspired Embodied AI” with details as follows: Date: 26 Feb 2026 Time: 11:00 - 12:00 Venue: HJ302, PolyU If you are interested, please register at: https://polyu.hk/afMJJ (Registration Deadline: 20 Feb 2026) For enquiry, please contact us at dsai.enquiry@polyu.edu.hk. We look forward to seeing you at the seminar! Best regards, Department of Data Science and Artificial Intelligence  

(Register Now) DSAI Distinguished Seminar Series - Graph Deep Learning for Irregular Spatiotemporal Data

You are cordially invited to attend the DSAI distinguished seminar by Prof. Cesare Alippi on “Graph Deep Learning for Irregular Spatiotemporal Data” with details as follows: Date: 25 Feb 2026 Time: 11:00 - 12:00 Venue: HJ302, PolyU If you are interested, please register at: https://polyu.hk/SyApD (Registration Deadline: 20 Feb 2026) For enquiry, please contact us at dsai.enquiry@polyu.edu.hk. We look forward to seeing you at the seminar! Best regards, Department of Data Science and Artificial Intelligence  

Welcome On Board – New Faculty at DSAI

The Department of Data Science and Artificial Intelligence (DSAI) is pleased to announce the addition of four distinguished scholars to our faculty: Prof. LIANG Hualou has joined as Chair Professor of Neuroscience and Artificial Intelligence, under joint appointment with the Department of Language Science and Technology (LST), effective 1 January 2026. He is also serving as Interim Head of the Division of Artificial Intelligence and the Humanities (AIH), and the Associate Director of the University Research Facility in Behavioral and Systems Neuroscience (UBSN). Prof. CHEN Zhen has joined as Assistant Professor, effective 12 January 2026. Prof. WU Xingyu has joined as Assistant Professor, effective 15 January 2026. Prof. HU Yao has joined as Research Assistant Professor, effective 6 January 2026.   Prof. LIANG Hualou Prof. Liang is a renowned scholar in neural data science, machine learning, and biomedical natural language processing. He is recognized for pioneering the application of causal functional connectivity measures, such as Granger causality, to the analysis of complex, high-dimensional neuroscience data. His recent research on large language models for early detection of cognitive decline has been featured in media outlets such as Psychology Today, Jerusalem Post, The New York Times, and IEEE Spectrum. In recognition of his significant contributions to the development of advanced signal processing methods for analyzing functional brain networks, he has been elected a Fellow of the American Institute for Medical and Biological Engineering (AIMBE).   Prof. CHEN Zhen Prof. Chen’s research bridges AI innovation and clinical practice, with a focus on generalizable and multimodal AI systems for healthcare. He has received several prestigious awards, including the Hong Kong Young Scientist Award 2023, and has published in leading journals and conferences. Prof. Chen is also active in the academic community as an area chair and reviewer.   Prof. WU Xingyu Prof. Wu’s research focuses on autonomous AI systems, causality-based machine learning, and large foundation models. He serves as Vice Chair of the IEEE Computational Intelligence Society Task Force on LLMs and Computational Intelligence for General-Purpose AI Systems. Prof. Wu has also received multiple international awards in recognition of his research excellence.   Prof. HU Yao Prof. Hu specializes in medical multimodal artificial intelligence, focusing on integrated systems for patient care and advanced clinical decision support. His research includes vision-language models, privacy-preserving domain adaptation, federated learning, and deep learning for medical image analysis. He has published in top AI and biomedical venues.   We warmly welcome Prof. LIANG, Prof. CHEN, Prof. WU, and Prof. HU to DSAI and look forward to their valuable contributions to our department.

DSAI Celebrates First Cohort of Graduates at PolyU’s 31st Congregation

The Department of Data Science and Artificial Intelligence (DSAI) proudly celebrated its inaugural cohort of graduates at The Hong Kong Polytechnic University’s 31st Congregation, held on 18 November 2025 at 2:30pm at the Jockey Club Auditorium. This milestone event marked the graduation of 74 students from the Master of Science in Artificial Intelligence and Big Data Computing programme and 46 students from the Bachelor of Science in Financial Technology and Artificial Intelligence programme. The ceremony was a significant moment for the department, reflecting its commitment to nurturing future leaders in data science, artificial intelligence, and financial technology. Prof. TAN Kay Chen, Head of Department, delivered a congratulatory speech, commending the graduates as pioneers who have set the standard for future cohorts. He highlighted their adaptability, resilience, and achievements, and encouraged them to use their expertise, creativity, and ethical responsibility to make a positive impact in the rapidly evolving fields of data science and artificial intelligence. LIU Chengju, a graduate of the Bachelor programme, represented the graduating class with a heartfelt Valedictory Speech, expressing gratitude to the faculty and peers, and sharing hopes for the future. The Department extends its warmest congratulations to all graduates and looks forward to their continued success as they embark on their professional journeys.

(Register Now) DSAI Distinguished Seminar Series - Statistics at the Crossroads: Challenges and Opportunities

You are cordially invited to attend the DSAI distinguished seminar by Prof. Tony Cai on “Statistics at the Crossroads: Challenges and Opportunities” with details as follows: Date: 8 Jan 2026 Time: 15:00 - 16:00 Venue: FJ302, PolyU If you are interested, please register at: https://polyu.hk/YPVIa  (Registration Deadline: 7 Jan 2026) For enquiry, please contact us at dsai.enquiry@polyu.edu.hk. We look forward to seeing you at the seminar! Best regards, Department of Data Science and Artificial Intelligence  

Welcome On Board – Assistant Professor Prof. HUANG Jiaxing

The Department of Data Science and Artificial Intelligence (DSAI) is delighted to announce that Prof. HUANG Jiaxing has joined us as Assistant Professor, effective 15 December 2025. Prior to joining DSAI, Prof. HUANG was a Research Scientist at the College of Computing and Data Science, Nanyang Technological University (NTU). He received his Ph.D. from NTU in 2023, and holds Bachelor’s degrees from the University of Glasgow (Distinction First Class Honours) and the University of Electronic Science and Technology of China. His research focuses on multimodal artificial intelligence, especially vision and multimodal foundation models, with the goal of building intelligent systems that can effectively assist humans. Prof. HUANG’s work has been published in leading AI venues, and he serves as an Area Chair for major conferences such as ICLR and NeurIPS. He has also been recognized among the World’s Top 2% Scientists by Stanford University. Please join us in warmly welcoming Prof. HUANG Jiaxing to DSAI.

(Register Now) DSAI Distinguished Seminar Series - Some Current and Future Challenges in Evolutionary Multi-Objective Optimization

You are cordially invited to attend the DSAI distinguished seminar by Prof. Carlos Artemio Coello Coello on “Some Current and Future Challenges in Evolutionary Multi-Objective Optimization” with details as follows: Date: 18 Dec 2025 Time: 11:00 - 12:00 Venue: FJ302, PolyU If you are interested, please register at: https://polyu.hk/WNYQM  (Registration Deadline: 15 Dec 2025) For enquiry, please contact us at dsai.enquiry@polyu.edu.hk. We look forward to seeing you at the seminar! Best regards, Department of Data Science and Artificial Intelligence  

Prof. ZHANG Chengqi Elected as IEEE Fellow 2026

Prof. ZHANG Chengqi, Director of the Hong Kong Polytechnic University Shenzhen Research Institute (SZRI) and Chair Professor of Artificial Intelligence at the Department of Data Science and Artificial Intelligence (DSAI), has been elected as a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) for the Class of 2026. This prestigious recognition is awarded in tribute to Prof. ZHANG’s outstanding contributions to graph neural networks and time series analysis.  IEEE Fellow is the highest grade of membership in IEEE, the world’s largest technical professional organisation dedicated to advancing technology for the benefit of humanity. The distinction is reserved for select IEEE members whose extraordinary accomplishments in any of the IEEE fields of interest are deemed fitting of this prestigious grade elevation. Less than 0.1% of voting members are selected annually for this member grade elevation, following a rigorous evaluation procedure by the IEEE Fellow Committee. Prof. ZHANG is a leading scholar in artificial intelligence and data mining, with a particular emphasis on graph neural networks and time series analysis—fields that are transforming the landscape of data science. He has published over 400 research papers in top international journals and conference proceedings, with more than 35,000 citations. His research excellence has been recognised with numerous awards, including the NSW Science and Engineering Award, the UTS Vice Chancellor Research Excellence Award, and the IEEE ICDM Outstanding Service Award. The DSAI community is honored to share the news of Prof. ZHANG’s well-deserved recognition for his outstanding contributions. His elevation to IEEE Fellow not only highlights his individual achievements but also reflects the department’s commitment to excellence in research and innovation in artificial intelligence and data science.

DSAI Team "EvoClass Nexus" Crowned Champion at Huawei Developer Competition 2025 Asia Pacific Region

The Department of Data Science and Artificial Intelligence (DSAI) is proud to announce that its research team, EvoClass Nexus, has emerged as the Champion and Grand Prize Winner at the Huawei Developer Competition 2025 Asia Pacific Region, earning a reward valued at US$5,000 (approx. HK$39,000). The project was developed by a dedicated team of researchers from DSAI, led by Prof. CHENG Ran (Associate Professor, DSAI/COMP) alongside core members and PhD students HUANG Beichen, LIANG Zhenyu, and ZHENG Bowen, whose combined expertise in AI agents was instrumental in this success. The competition involved multiple rigorous stages, including preliminary rounds, re-evaluations, and semi-finals, filtering through nearly 1,000 developers and 192 high-quality submissions from 10 countries and regions. Ultimately, only 15 elite teams successfully advanced to the Asia Pacific Final, where they were divided into two distinct tracks: Society and Sustainability, and Finance. With only one Grand Prize awarded per track, the EvoClass Nexus team secured the Championship for the Society and Sustainability sector, distinguishing themselves as the top innovators in AI for social impact. The championship-winning project, EvoClass, is an AI-empowered multi-agent education platform designed to bridge the "Cognitive Chasm" in modern education. The platform moves beyond traditional EdTech by creating a "Co-evolutionary" ecosystem where AI agents grow alongside students. The system has already been successfully deployed in the DSAI subject DSAI2201 Data Structures and Algorithms, demonstrating significant effectiveness in enhancing student engagement and reducing educator workload. This victory highlights the team's commitment to "Technology Equity"—using advanced AI to make private-tutor-level education accessible to all. By automating repetitive tasks and providing context-aware feedback, EvoClass empowers teachers to focus on pedagogical innovation.