In the first week’s lectures, I have emphasized the difference between mentally reproducible and experimentally reproducible research (more or less: theory vs. experiment). Mathematical theories are mentally reproducible objects – you can understand them if you have the required background and think hard enough. From this perspective, mathematics is no different from art such as Van Gough’s painting – you can appreciate its beauty because you can mentally reconstruct the mathematical or artistic sensation from the objects presented to you. This is the simple reason why Gaussian distribution or Da Vinci’s Mona Lisa can become the cultural heritage and passed on from generation to generation (called “meme” by Richard Dawkins’ words in his book “Selfish Genes”).
Engineering deal with experimentally reproducible objects – the make of a car, a smartphone, a telescope etc. According to wikipedia, the ultimate goal of engineering is to “safely realize improvements to the lives of people”. Therefore, it is not surprising to see engineering inventions often have much less life expectations than scientific theories or artistic products. We see cassette replaced by CDs, film cameras replaced by digital ones, dial-up modem replaced by high-speed internet connections. It is Darwin’s evolutionary law applied to the technological world. If your hero is someone like Bill Gates or Steve Jobs, their greatness simply lies in their vision in creating the right products. Experimental reproducibility is a necessary (but not sufficient) condition for a product’s commercial viability.
What is good engineering? There are various aspects – sometimes being the first is important (think of the invention of telephone by Bell – that is why patent or intellectual property is valued by industry); sometimes you do not need to lead the race (think of the invention of iphone – as long it is good design, you can still catch up). I emphasize the importance of experimental reproducibility to good engineering because it is still a sad fact that research reproducibility has not become the standard norm for all technical communities (please refer to the supplementary reading I have posted to the course website). So it has become difficult (especially for young minds entering the field) to tell the real progress from the bogus one from the bulk of published papers every year.
