Nature-inspired computing and knowledge engineering for embedded system design and information processing

我的研究结合了知识工程与基于生态学和自然启发的技术，用于系统设计和分析-无论是在硬件和软件层面-以及整体数据处理。 它依赖于这样一个假设，即大多数设计和分析问题可以转换为分类或优化问题，这些问题存在自然等价物，并在进化过程中得到解决，或者它们可以用新的形式主义（例如混沌理论，模糊逻辑等）来处理。在这样做的时候，我打算补充现有的形式化技术，当它们容易出现组合爆炸时， 容易开发（即封闭形式）的解决方案，或只是太慢（例如，设计基本的射频和微波电路的电流手段可能需要几个小时的设计师没有丰富的经验）。

My research combines knowledge engineering with heuristics-based and nature-inspired techniques for system design and analysis - both at the hardware and software levels - and overall data processing. It relies on the postulate that most design and analysis problems can be converted to classification or optimization problems for which natural equivalents exist and have been solved over the course of evolution, or that they can be handled with new formalisms (e.g. chaos theory, fuzzy logic, etc.). In doing so, I intend to supplement the existing formal techniques when they are prone to combinatorial explosion, cannot lead to readily exploitable (i.e. closed form) solutions, or are simply too slow (for example, the design of basic RF and microwave circuits by current means may take hours for a designer without extensive experience).