On June 22, 2023, Professor Juan Aparicio from Miguel Hernandez University of Elche (UMH) in Spain was invited to give an online academic report titled "The use of machine learning techniques to estimate technical efficiency". The report will be chaired by Professor Wang Ke, with over 30 teachers and students from the center and college attending.

Professor Juan Aparicio discussed the overfitting problem of the Free Disposal Hull (FDH) and Data Envelopment Analysis (DEA) methods in his report, and proposed a solution based on Classification and Regression Tree (CART). This scheme is named Efficiency Analysis Trees (EAT). Professor Juan Aparicio also demonstrated the superiority of EAT method over existing models by comparing with FDH, DEA and other methods in Mean squared error (MSE), Absolute Bias and other indicators. In addition, Professor Juan Aparicio also proposed that EAT models can be optimized through methods such as pruning and random jungle. After the report, the teachers and students of the center and college had in-depth exchanges and discussions with Professor Juan Aparicio on the improvement plan and empirical application of the EAT model.

Juan Aparicio is a professor in the Department of Statistics, Mathematics and Information Technology of Miguel Hernandez University of Elche (UMH) in Spain, and also the director of the Operations research Center. He was co chairman of the Chairman of Efficiency and Productivity of Banco Santander (with Professor Knox Lovell). His research interests include efficiency and productivity analysis combined with machine learning and data science. In cooperation with Springer Press, he has independently or jointly edited several books, mainly focusing on the use of Data envelopment analysis for performance evaluation and benchmarking; And published about 150 scientific articles in different international journals. These journals include European Journal of Operational Research, OMEGA, Annals of Operations Research, International Journal of Production Economics, Journal of Optimization Theory and Applications, Journal of Productivity Analysis, Operational Research, Social Economic Planning Sciences, as well as Computers and Operations Research and Computers and Industrial Engineering. In particular, he has recently published several articles on the improvement of different machine learning technologies to estimate the Production function and technical efficiency from the perspective of methodology. In addition, he also applied the new method to real databases in different departments such as education and banking. He has served as a keynote speaker at multiple conferences such as DEA International Conference in 2020. He is currently the deputy editor in chief of Omega The International Journal of Management Science and Journal of Productivity Analysis.