This talk presents the role of AI in science and engineering, from learning for prediction to optimization for precision, and onward to generative models that potentially reshape solution spaces. It highlights the possible shift from purely data-driven abstraction to physically grounded intelligence, where AI systems are increasingly aligned with the laws of nature. Advances in generalizable physics-informed neural networks, guided diffusion model generation, and prompt evolution are empowering AI to simulate, predict, plan, and design within real-world constraints. As language models become engines of scientific exploration, navigating complex design spaces and abstract knowledge landscapes, they converge with physics-based signals and evolutionary principles such as multifactorial optimization to achieve high-fidelity modelling and creative physical design. The talk ends with a vision of AI not merely as a tool but as a co-explorer, fusing data, theory, and imagination to uncover latent structures, accelerate discovery, and deliver real-world impact.

Brief Biography:
Professor Yew-Soon Ong received his Ph.D. in Artificial Intelligence for Complex Design from the University of Southampton, U.K., in 2003. He previously served as Chair of the School of Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. Currently, he is a President’s Chair Professor in Computer Science at NTU and the Chief Artificial Intelligence Scientist at the Agency for Science, Technology and Research (A*STAR), Singapore. His research interests encompass artificial intelligence, evolutionary computation, statistical machine learning, and optimization. He was General Co-Chair of the 2024 IEEE Conference on Artificial Intelligence and has been a keynote speaker or senior area chair or area chair of AAAI, IJCAI, ICLR, NeurIPS, KDD and others. He has received several IEEE Outstanding Paper Awards and was recognized as a Thomson Reuters Highly Cited Researcher. He is founding editor-in-chief of the IEEE Transactions on Emerging Topics in Computational Intelligence, senior associate editor or associate editor for IEEE Transactions on Neural Networks & Learning Systems, IEEE Transactions on Evolutionary Computation, and IEEE Transactions on Artificial Intelligence. He is a fellow of the IEEE and a fellow of the National Academy of Engineering, Singapore.