I am a Ph.D. student currently doing research at a top engineering school in North America.
I am becoming more and more jaded at the fact that a sizable portion of the research conducted at my university as well as publications to engineering conferences seem to have very limited practical relevance, and with no attempts to address implementation concerns. Many of these papers seem to be published just for the sake of it.
One glaring example is power engineering. The methodologies proposed by recent graduates from power engineering are so extremely far-fetched from practical implementation, it raises the question as to why any such research should be continued.
Power is a very safety critical field: people can die after going for too long without power (case in point), and the industry itself is highly government regulated. The algorithms that have been proposed from my research department as well as many like it completely ignore things like safety guarantees. Furthermore, it is highly unlikely that government employees in the power industry would rely on some biology motivated or learning based algorithm to arrange the power supply to millions of actual people. There are decades old well-regulated power markets for that!
But power is just one example out of many. I have read many papers on signal processing and control theory. Most of the papers are completely math and proof based; their proposed methods are so mathematical, with extremely limited robustness or safety guarantees, etc. These researchers are more concerned with epsilons and deltas than how their proposed methods can be realistically implemented in people's cars or mobile phones.
An "implementation" nowadays is just a MATLAB simulation, a few equations, and a graph. Even during undergraduate engineering training, we have seen how difficult it is to go from simulation to actual software/hardware that people can use. I can easily show you highly technical papers from these fields published by people who do not even care about the readability of their notation, let alone practical implementation.
So it is a legitimate question as to why anyone would ever use these highly-theoretical, and assumption laden research results. It is unclear what "the small-gain signal must belong to a Hilbert space on the extended half-line" actually means in real life cache design. Furthermore, many papers are completely without any mention of practical implementation of the algorithms, so it is completely unknown if anyone would actually be able to use these research results.
Engineering research is ultimately used to create new technologies that promise to improve the lives of people. However, it is unknown to me at this point how a "bat-echolocation based meta-heuristic algorithm for nuclear generator dispatch" could benefit anyone.
So my question boils down to how we as researchers should attempt to bridge the gap between the highly mathematical, highly theoretical modern engineering research and the practical implementation of research results. What good is engineering research with no practical relevance?