TLDR: Professor Sam Kwong Tak-wu, a leading AI expert at Lingnan University, has received the prestigious 2026 IEEE Transactions on Evolutionary Computation Outstanding Paper Award. The award recognizes his co-authored paper, ‘Learning-Aided Evolution for Optimization,’ which introduces a novel framework (LEO) that significantly enhances AI’s ability to find optimal solutions in complex scenarios by integrating learning components into traditional evolutionary computation methods. This achievement underscores Prof. Kwong’s international leadership in AI research and Lingnan University’s commitment to cutting-edge innovation.
Lingnan University is proud to announce that Professor Sam Kwong Tak-wu, a distinguished figure in artificial intelligence (AI) and computational intelligence, has been awarded the 2026 IEEE Transactions on Evolutionary Computation Outstanding Paper Award. This accolade, presented by the IEEE Computational Intelligence Society, recognizes his groundbreaking co-authored paper titled ‘Learning-Aided Evolution for Optimization.’ The paper was the sole recipient of this esteemed award for the year, highlighting its profound impact on the fields of evolutionary computation and AI.
Prof. Kwong currently serves in multiple pivotal roles at Lingnan University, including Associate Vice-President (Strategic Research), Dean of the School of Graduate Studies, and J.K. Lee Chair Professor of Computational Intelligence. He is also the Acting Dean of the School of Data Science, positioning him at the forefront of research, talent development, and institutional strategy in AI.
The award-winning paper, originally published in 2023, introduces a revolutionary approach that seamlessly integrates a learning component into conventional evolutionary computation methods. This innovation empowers AI systems to identify optimal solutions with greater speed and accuracy, particularly in highly intricate problem domains. The core of this research is the novel Learning-aided Evolutionary Optimization (LEO) framework. This framework enables artificial neural networks (ANNs) to learn from successful experiences throughout the evolutionary process. By observing and recording which solutions yield superior results, LEO moves beyond mere random mutation, allowing evolutionary computation methods to leverage past knowledge, thereby dramatically boosting efficiency.
Extensive experiments were conducted on international benchmark platforms, encompassing both single-objective and multi-/many-objective evolutionary optimization problems, to rigorously evaluate LEO’s effectiveness. The results consistently demonstrated LEO’s superior performance over traditional evolutionary computation methods, showcasing enhanced efficiency and accuracy in tackling complex problem-solving challenges.
Initially conceived as a highly forward-looking concept in 2023, the LEO framework has since found increasing application in diverse areas demanding complex computations. These include critical sectors such as traffic planning, smart manufacturing, drug discovery, and green energy, underscoring its broad practical potential. Prof. Kwong emphasized the relevance of this work, stating, “As global societies and industries face growing demands for rapid computation and precise prediction, traditional evolutionary optimization approaches often struggle with large datasets or multi-objective scenarios.”
Prof. Kwong’s illustrious career is marked by an exceptional blend of academic rigor and global engagement. He holds a B.Sc. in Electrical Engineering from the State University of New York at Buffalo, an M.A.Sc. from the University of Waterloo, Canada, and a Ph.D. from FernUniversität in Hagen, Germany. Before joining Lingnan University, he held significant academic positions at the City University of Hong Kong, rising to Chair Professor and Head of the Department of Computer Science. His industry experience includes roles as a Diagnostic Engineer at Control Data Canada and a Member of Scientific Staff at Bell Northern Research. His research interests span evolutionary computation, machine learning, video and image coding, pattern recognition, and AI-driven engineering solutions.
Beyond this latest award, Prof. Kwong has received numerous accolades for his contributions. He has been listed as a Highly Cited Researcher by Clarivate since 2022 and recognized as one of Stanford University’s top 2% of scientists worldwide since 2021. He is also a Fellow of the Canadian Academy of Engineering, holds 40 US patents, and has authored over 500 journal and conference papers and three monographs. He serves as an associate editor for several leading IEEE Transactions journals, actively shaping scientific discourse in AI and computational intelligence.
Professor S. Joe Qin, President and Wai Kee Kau Chair Professor of Data Science at Lingnan University, commended Prof. Kwong’s achievement: “I am pleased that Prof Sam Kwong has received this prestigious honour, which fully demonstrates Lingnan scholars’ outstanding achievements in advancing global research in artificial intelligence. Prof Kwong is one of the key pioneers driving Lingnan’s transformation into a leading comprehensive university in arts and sciences in the digital era.” This award further solidifies Lingnan University’s commitment to promoting the ‘Lingnan-60 Global Talent Recruitment’ initiative, aiming to attract 60 top international scholars by 2027, coinciding with the university’s 60th anniversary.
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This recognition not only celebrates Prof. Kwong’s individual brilliance but also highlights Lingnan University’s growing prominence as a hub for innovative AI research and its dedication to nurturing future generations of research talent.
