| Prof. Carlos A. Coello CoelloCINVESTAV-IPN Dr. Carlos Coello is a professor with distinction (Investigador CINVESTAV 3F) at the Center for Research and Advanced Studies of the Instituto Politécnico Nacional (CINVESTAV-IPN) in Mexico City and visiting professor at the Basque Center for Applied Mathematics in Spain. Has taught master’s and Ph.D. level courses on evolutionary computation, evolutionary multiobjective optimization, programming languages, and engineering optimization at CINVESTAV-IPN. In addition, he has taught short courses in Spain, England, India, U.S., among others. His research interests are evolutionary computation (genetic algorithms and evolution strategies), as well as engineering optimization. His main contributions have been the design of biologically inspired stochastic algorithms to solve highly complex multi-objective optimization problems (mainly non-linear). He has made pioneering contributions to this area, which is now known as evolutionary multi-objective optimization. For example, he proposed, along with his research group, the first genetic micro-algorithm for multi-objective optimization, which has been used in real-world applications in several countries, like the United States, for the design of supersonic business jets. He is member of the Foundation Advisory Board of the International AIQT Foundation, which strives to establish a highly competitive (international-level) research center in artificial intelligence and quantum technology. Among his multiple special recognitions and awards, Dr. Carlos Coello was awarded by the International Society on Multi-Criteria Decision Making (MCDM) the 2024 MCDM Edgeworth-Pareto Award. In 2023, he won the Premio Crónica in Science and Technology and was selected by Líderes magazine as part of their "300 most influential leaders in Mexico" list, taking the 69th position. He also won the SIGEVO Outstanding Contribution Award (2023) given by the Association for Computing Machinery (ACM), the IEEE Computational Intelligence Society Evolutionary Computation Pioneer Award (2021), among many others. Dr. Coello is level 3 in the National System of Researchers (SNII) in Mexico and was also ranked #289 in the world and #1 in Mexico in the 8th Edition of the Guide2Research 2022 Ranking of Top 1000 Scientists in the field of Computer Science and Electronics. Professor Carlos Coello joined Tecnológico de Monterrey as Distinguished Visiting Professor in Computer Science and Computational Intelligence for the School of Engineering and Sciences. |
| Prof. Xiaoyong LiuGuangdong Polytechnic Normal University Xiaoyong Liu, Ph.D., is a Professor and Master's Supervisor. He currently serves as the Director of the Management Committee of Heyuan Campus at Guangdong Polytechnic Normal University, Dean of the School of Data Science and Engineering, and Director of the Guangdash Heyuan Research Institute. Additionally, he holds the positions of Director of the Guangdong Provincial Big Data Engineering Technology Research Center for Industry-Education Integration Development, Vice Chairman of the Guangdong Systems Engineering Society, and Secretary-General of the Guangzhou Engineering Management Society. He was also a Visiting Scholar at the University of California, Irvine (UCI). His primary research focuses on algorithm design and applications in machine learning, remote sensing image analysis, and big data mining. In recent years, he has led over 10 research projects, including the National Natural Science Foundation of China General Program, Guangdong Provincial Natural Science Foundation General Program, Guangdong Provincial Science and Technology Plan Project, and the Ministry of Education Humanities and Social Sciences Research Special Project. He has been granted 5 national invention patents and has published more than 30 papers as the first author or corresponding author. He has also presided over and received the First Prize of Guangdong Higher Education Teaching Achievement Award and the Second Prize of the National Commercial Science and Technology Progress Award. Under his guidance, students have participated in numerous prestigious academic competitions, such as the Interdisciplinary Contest in Modeling (ICM/MCM), the National College Mathematical Contest in Modeling, and the National Graduate Mathematical Contest in Modeling. Their achievements include 1 international first prize, 2 international second prizes, 3 national second prizes, and over 30 other provincial-level awards. |
 | Prof. Feiwei QinHangzhou Dianzi University Feiwei Qin is a Professor and Ph.D. Supervisor at the School of Computer Science, Hangzhou Dianzi University. Selected for the Qianjiang Distinguished Young Scholars Program of the university in 2023 and the Zhejiang Provincial Young Talent Program in 2024. Research interests include artificial intelligence, CAD, and computer vision. More than 100 academic papers have been published in related fields, including highly cited papers, SCI Q1 journals (Chinese Academy of Sciences classification), top-tier venues, and CCF-A conferences/journals. Over 60 invention patents have been filed, and the Second Prize of the China Invention Association has been awarded. A total of 4 national-level projects and 7 provincial-level projects have been led or completed, with participation as a key member in 10 national-level and 9 provincial-level projects. Over the past five years, teaching performance evaluations have consistently been rated A. Supervision has resulted in 16 national-level undergraduate innovation and entrepreneurship projects and 12 Zhejiang“Xinmiao” projects. Students have received more than 80 international and national awards in competitions such as the China International College Students’ Innovation Competition, “Challenge Cup,” “Lanqiao Cup,” the China Collegiate Computer Design Competition, Intelligent Robotics Competition, and international medical image analysis challenges. Speech Title: Intelligent Generation of 3D CAD Models Abstract:This report explores two major technical paradigms for intelligent CAD model generation. The first paradigm is direct B-rep generation. To address the limitations of existing methods in underutilizing graph structures and the difficulty of balancing generation efficiency with topological validity, a graph diffusion-based direct B-rep generation method, BRep-GD, is proposed. Furthermore, to mitigate issues such as error accumulation, redundancy, and noise contamination caused by multi-stage cascaded approaches, a high-fidelity latent representation-based direct B-rep generation method, HiFi-BRep, is introduced. The second paradigm is sequential modeling. The Drawing2CAD framework is developed to enable cross-modal generation from 2D vector engineering drawings to parametric CAD models. By adopting a dual-decoder Transformer architecture, CAD generation is reformulated as a sequence-to-sequence learning problem. Each paradigm has distinct advantages: direct B-rep generation is more suitable for modeling complex geometric and topological relationships, while sequential modeling aligns more closely with traditional CAD design workflows and offers better interpretability. Through comparative analysis of their technical characteristics and application scenarios, future CAD generation technologies are expected to evolve toward multimodal integration and hybrid modeling, combining the strengths of both paradigms to achieve more intelligent and efficient CAD model generation. |
 | Prof. Gexiang ZhangChengdu University of Information Technology Second-Class Professor, Ph.D., Doctoral Supervisor, President of the International Membrane Computing Society, IET Fellow, New Century Excellent Talent of the Ministry of Education, and Academic and Technical Leader of Sichuan Province. He was selected as an Elsevier Highly Cited Chinese Researcher in 2020-2021 and ranked among the top 2% of scientists worldwide. In 2019, he received the Grigore Moisil Award from the Romanian Academy (as reported on the official website of the Chinese Ministry of Science and Technology: the first Chinese to receive a Romanian Academy Award as the first author, and the first Chinese to win the Moisil Award). He has led 5 National Natural Science Foundation projects and dozens of other national, ministerial, and provincial-level projects. He has published 3 Chinese and English academic books, over 100 SCI-indexed papers, and obtained more than 40 nationally authorized invention patents. His awards include the Science and Technology Outstanding Contribution Award from the China Association for Science and Technology Industrialization, the Second Prize of the Sichuan Provincial Natural Science Award, the Second and Third Prizes of the Sichuan Provincial Science and Technology Progress Award, the Annual Application Achievement Award of the International Membrane Computing Society, and Best Paper Awards at international conferences. He serves as an editorial board member of international journals such as IJPEDS and Axioms, and as a guest editor or editorial board member of international journals including IJNS and IJUC. He is also an editorial board member of the journal "Traffic Information and Safety," and has held roles as chair, co-chair, or member of organizing committees, program committees, and international conference committees. Additionally, he is a member of the Academic Committee of the Key Laboratory of Advanced Ship Communication and Information Technology of the Ministry of Industry and Information Technology and the Sichuan Provincial Key Laboratory of Power Internet of Things. He is also a committee member of the Artificial Intelligence and Electrical Application Committee of the Chinese Society of Electrotechnics, a standing council member of the Sichuan Society of Electrical Engineering, and a member of the Teaching Guidance Committee for Electrical and Automation Majors in Sichuan Province’s Regular Undergraduate Institutions. His research focuses primarily on artificial intelligence, intelligent robotics, smart grids, and intelligent control. |
