Symposium on Mathematical Engineering
The topic of this conference is the application of mathematical engineering to solve complex engineering problems using mathematical methods and data-driven methods. Mathematical engineering is the art of solving engineering problems using mathematical means. Mathematical laws characterize many physical and natural phenomena. The same holds for many engineering problems.
The need of original mathematical analysis of engineering problems has greatly increased in recent times, in parallel with the massive development of new engineering fields, especially in the very wide area of information generation and management. The rapid increase in the complexity of the systems we use, and the need to use more refined intelligence (such as the ability to gather information, evaluate it, derive conclusions from observations and putting in place effective controls) in a large variety of areas requires the development of more refined mathematical means.
Modern fields of endeavor requiring novel mathematical efforts include the handling of large data sets, sensor networking, deep learning, autonomous systems, large scale environmental modeling, and many more. In all these cases, mathematical engineering starts out with the development of effective models (the accurate but simple modeling of engineering phenomena is a major issue in itself), followed by the development of adequate mathematical tools to handle the models and to steer their evolution. This process is perhaps best exemplified by autonomous driving, which still has a long way to go before it can rival the cognitive abilities of a driving human (the reliability of an automatic car driver is still a factor of a thousand off mark, and it will require major mathematical effort to solve just this problem).
This conference assembles a limited number of research-oriented engineers, many of them among the pioneers in the development of this crucial field, and who want to exchange their ideas, present experiences and share views on how to deal with novel problem challenges in the field.
This international conference gathers world-class experts in engineering and applied mathematics to address the challenges of solving complex engineering problems using mathematical and data-driven methods. It serves as a platform for fostering collaboration and exchanging cutting-edge knowledge, bringing together both domestic and international participants to drive innovation and advance research in this field.
Recent advancements have heightened the demand for innovative mathematical analysis, particularly in the areas of information generation and management. The ability to efficiently handle large data flows, evaluate sensor networks, and develop autonomous systems requires advanced techniques. This conference will explore these state-of-the-art methods, focusing on their applications across various engineering domains.
Key topics include the challenges of managing large data sets, sensor networks, deep learning, autonomous systems, and environmental modeling. Mathematical engineering plays a vital role in these areas, starting with the development of models that simplify engineering phenomena and continuing with the creation of tools to manage these models effectively. Autonomous driving will be highlighted as a prime example, where mathematical advancements help bridge the gap between human and machine performance.
Through this conference, we aim to significantly contribute to the development of mathematical engineering, promoting deeper international collaboration and creating opportunities for innovation that will benefit both academia and industry.
The need of original mathematical analysis of engineering problems has greatly increased in recent times, in parallel with the massive development of new engineering fields, especially in the very wide area of information generation and management. The rapid increase in the complexity of the systems we use, and the need to use more refined intelligence (such as the ability to gather information, evaluate it, derive conclusions from observations and putting in place effective controls) in a large variety of areas requires the development of more refined mathematical means.
Modern fields of endeavor requiring novel mathematical efforts include the handling of large data sets, sensor networking, deep learning, autonomous systems, large scale environmental modeling, and many more. In all these cases, mathematical engineering starts out with the development of effective models (the accurate but simple modeling of engineering phenomena is a major issue in itself), followed by the development of adequate mathematical tools to handle the models and to steer their evolution. This process is perhaps best exemplified by autonomous driving, which still has a long way to go before it can rival the cognitive abilities of a driving human (the reliability of an automatic car driver is still a factor of a thousand off mark, and it will require major mathematical effort to solve just this problem).
This conference assembles a limited number of research-oriented engineers, many of them among the pioneers in the development of this crucial field, and who want to exchange their ideas, present experiences and share views on how to deal with novel problem challenges in the field.
This international conference gathers world-class experts in engineering and applied mathematics to address the challenges of solving complex engineering problems using mathematical and data-driven methods. It serves as a platform for fostering collaboration and exchanging cutting-edge knowledge, bringing together both domestic and international participants to drive innovation and advance research in this field.
Recent advancements have heightened the demand for innovative mathematical analysis, particularly in the areas of information generation and management. The ability to efficiently handle large data flows, evaluate sensor networks, and develop autonomous systems requires advanced techniques. This conference will explore these state-of-the-art methods, focusing on their applications across various engineering domains.
Key topics include the challenges of managing large data sets, sensor networks, deep learning, autonomous systems, and environmental modeling. Mathematical engineering plays a vital role in these areas, starting with the development of models that simplify engineering phenomena and continuing with the creation of tools to manage these models effectively. Autonomous driving will be highlighted as a prime example, where mathematical advancements help bridge the gap between human and machine performance.
Through this conference, we aim to significantly contribute to the development of mathematical engineering, promoting deeper international collaboration and creating opportunities for innovation that will benefit both academia and industry.
组织者
康家熠
,
丘成栋
日期
2025年12月15日 至 19日
位置
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| 周一,周二,周三,周四,周五 | 09:00 - 18:00 | TSIMF | - | - | - |