I’m sure you’ve heard of computer science and engineering separately, but what about computational engineering? Computational Engineering bridges the gap between engineering disciplines, applications of higher mathematics such as calculus and linear algebra, and computer science. But this combination of disciplines is more important than it seems. We can handle small-scale modeling and whip out our trusty TI-84s for linear regression models. But what about interpreting large data sets with millions of data points? What about recognizing patterns in data? What about calculating the viability of certain scientific models? This is where computational engineering comes in. With computational engineering being an interdisciplinary field computational engineers can build algorithms and make computational models that predict certain patterns and trends from large data sets. As you can imagine, the work of computational engineers is becoming more and more important, especially during the current coronavirus pandemic. In February, the GLEAM project released the beta version of EpiRisk, a computer modeling program that predicts the safest forms of transportation for infected individuals through a number of factors.
This predicts the risk of contracting the virus if an infected individual is transported through airlines through a combination of factors, including symptom onset, month of travel, travel restrictions, etc. And just recently, in June, using a combination of biology and computational engineering, MIT researchers began developing an artificial peptide protein that could destroy the virus at a cellular level. But, the benefits of computational engineering don’t stop there. Computational engineering careers can be utilized in all fields of technology, and are useful in any major. For instance, the work of computational engineers can be useful in biology labs in modeling and measuring experimental values and large data sets to find patterns. It can be used in the aerospace industry to test rocket and aeronautic design without having to build expensive models. It can even be used in business to find optimal times for product launches and modeling consumer and client data trends. Yet, computational engineering continues to attract little interest in comparison to its counterpart majors in engineering, computer science, and the natural sciences. This is in part due to how new the field is, as well as the enormous popularity of other STEM majors. In addition, the gender disparity in STEM persists even in this field.
However, one small step towards educating fellow young women about new STEM fields can go a long way. After reading this, maybe you will consider a major in Computational Engineering.