merging computer science and academia
Over the past year, I keep seeing stories in which scientists are using more and more sophisticated software and computer systems to continue their research. For example, in Nature’s huge retrospective on the Human Genome Project, Craig Venter’s editorial asked for more computing power and new software. And with his experiments in synthesizing living things, he’s going to need more and more advanced machinery to stitch together longer and longer strands of DNA. New applications are fueling a rise in citizen science, allowing anyone passionate and knowledgeable enough about astronomy and space exploration, as well as a variety of other topics, to help classify a growing library of data, and even make their own scientific discoveries. The government is also taking computers seriously, counting exascale computing as one of the big goals to be met to ensure the nation’s leadership in R&D. Oh and did I mention AI? Because that’s pretty popular too…
In some ways, the growing reliance on computers and the people who know how to program them in science isn’t all that surprising. Many researchers today deal with huge amounts of data, far more than any small team could process in a realistic amount of time. But computers are great at sorting huge volumes of data for neat, to the point summaries of the patterns it contains and distributing these immense volumes of data to people who are able and willing to sort through things computers have a hard time analyzing, things like images. So it’s perfectly natural that academia would want to leverage such handy tools and as they do, they need experts in everything from robotics to web development to keep the streams of data coming and to make sense of all of it at a steady pace. And this means that computer sciences will continue to be in high demand, especially as schools are losing comp sci students so much that DARPA is getting worried. After all, the military has a lot of money, a lot of hardware, and relies on more and more automated systems. Who’s going to maintain all their legacy resources and build new ones if there are fewer comp sci grads?
And here’s another thing to consider. As computer science programs become more and more entwined with biologists, physicists, astronomers, and ever neuroscientists, often requiring those who design and code the applications used for research programs to learn a great deal about the science at hand to write software that produces meaningful results, can the discipline still be considered primarily an engineering endeavor rather than a scientific one or a hybrid of both? In other words, are computer scientists engineers in the same way a mechanical or electrical engineer would be, are they closer to scientists like astronomers, especially when it comes to matters of artificial intelligence and designing new types of hardware, or are they a combination of both worlds? When someone like me finishes grad school, what would you consider him or her to be?
