|Dr. Tan conducts a thematic academic report.||Dr. Tan interacted with teachers and students.|
At the invitation of Prof. Huang Han from the School of Software Engineering, Doctor Tan Kay Chen of the National University of Singapore visited our school on May 31st and conducted an academic seminar in the Intelligent Software and Intelligent Algorithm Laboratory in the morning. In the afternoon, Dr. Tan gave an academic report onEC at Work Opportunities and Challenges to the teachers and students, introducing evolutionary computing as a problem-solving technique that applied natural selection and genetic inheritance as the main principles, and the opportunities and challenges that evolutionary computing faced in the development process. The report was hosted by Professor Huang Han from the School of Software Engineering, South China University of Technology.
Dr. Tan is a professor at the Department of Electronics and Computer Engineering at the National University of Singapore (IEEE Fellow). He is currently the editor-in-chief of the IEEE Transactionon Evolutionary Computation (TEC) and an associate editor and member of 15 international journals. He is a recipient of the Outstanding Talent Award of the 2012 IEEE Computational Intelligence Association (CIS). In this academic conference, Dr. Tan mainly introduced the reasons of evolutionary computing as the main academic research directionand the development trends of it. Evolutionary computation is a series of technical problems that solve problems based on natural selection and genetic inheritance. These techniques with semi-heuristic or stochastic optimization features are used as global optimization algorithms, and the population effect of using candidate results in the search space is better than the traditional iteration of a single point. The application of evolutionary computing is more and more extensive. From the actual industry application to the cutting-edge scientific research, the evolutionary computing can be seen everywhere. This report promoted the application of deep learning to improve the accuracy of the predicted lifespan assessment, while demonstrating better performance with the evolutionary optimization of overall optimization of hyper-parameters. Dr. Tan presented the charm of academic science research in the form of multiple features, and unified the theory and practical application. This activity was actively participated by teachers and students from many universities.